desilike¶

Framework to specify DESI (clustering) likelihoods¶

Tutorial #2: bindings with external inference codes¶

Goals¶

At the end of the tutorial you will know:

  • how to write likelihoods in terms of compressed parameters (e.g. based on forecasts), optionally with covariance between different measurements
  • how to write full shape likelihoods, and emulate their theory
  • how to run inference within desilike, or Cobaya, CosmoSIS, and MontePython.

For real-life examples, see application to mock Y1 cosmological inference.

This is the continuation of the first tutorial, accessible here: desilike tutorial #1.

Environment¶

Easiest is to use the cosmodesi environment at NERSC:

source /global/cfs/cdirs/desi/users/adematti/cosmodesi_environment.sh main  # source the environment
${COSMODESIMODULES}/install_jupyter_kernel.sh main  # this to be done once

NB: to remove the previous kernel:

rm -rf $HOME/.local/share/jupyter/kernels/cosmodesi-main

To see these slides in a browser, e.g.:

firefox desilike_bindings.slides.html

Compressed likelihoods¶

Let's first focus on compressed likelihoods = only depend on the cosmological model (nuisance = bias, stochastic and counterterms already marginalized out).

=> sampling of these likelihoods is typically fast enough that they do not need to be emulated.

BAO likelihood¶

BAO likelihoods are built from a "BAO observable", that compares a data vector to a theory, typically $\alpha_{\perp}$ and $\alpha_{\parallel}$ or $D_{M}/r_{d}$ and $D_{H}/r_{d}$.

In [2]:
import numpy as np

from desilike import utils, setup_logging
from desilike.likelihoods import ObservablesGaussianLikelihood
from desilike.observables.galaxy_clustering import BAOCompressionObservable

setup_logging()

# fiducial cosmology is DESI's by default
observable1 = BAOCompressionObservable(data=[1., 1.],
                                       covariance=np.diag([0.01, 0.01]),
                                       quantities=['qpar', 'qper'],
                                       z=1.)
# Let's define the likelihood from this observable
likelihood = ObservablesGaussianLikelihood(observable1)

Reminder¶

In [3]:
# Likelihood parameters
print('varied likelihood parameters are', likelihood.varied_params.names())
# To evaluate the likelihood (return the logposterior)
print('logposterior is {:.3f}'.format(likelihood(Omega_m=0.29)))
[000000.16] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['qpar', 'qper'].
varied likelihood parameters are ['Omega_m']
logposterior is -0.005

Why do we bother about "observables"?

... because we can join them in a likelihood!

In [4]:
# We want to share the same cosmological calculation among all observables
# so let's give it explicitly
from desilike.theories import Cosmoprimo
cosmo = Cosmoprimo(fiducial='DESI')
# Set Cosmoprimo calculator's parameters
cosmo.init.params = {'Omega_m': {'prior': {'limits': [0.1, 0.9]},
                                 'ref': {'dist': 'norm', 'loc': 0.3, 'scale': 0.002},
                                 'latex': '\Omega_m'}}
# Let's reuse the first observable we have defined, just updating the cosmo
observable1.init.update(cosmo=cosmo)
# Let's be fancy and rather define our observable in terms of DV_over_rd
# We provide a dictionary to "data": the theory vector will be generated automatically
observable2 = BAOCompressionObservable(data={}, quantities=['DV_over_rd'], z=1.5, cosmo=cosmo)
# Let's join the two observables, and provide the joint covariance
likelihood = ObservablesGaussianLikelihood([observable1, observable2], covariance=np.diag([0.01, 0.01, 1.]))
print('likelihood is {:.4f}'.format(likelihood()))
[000000.86] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['qpar', 'qper'].
[000001.13] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['DV_over_rd'].
likelihood is -0.0000

We can also sum (log-) likelihoods!

In [5]:
likelihood2 = likelihood + likelihood
likelihood(Omega_m=0.29)
likelihood2(Omega_m=0.29)
assert np.allclose(likelihood2.loglikelihood, 2. * likelihood.loglikelihood)

Bindings¶

To generate desilike bindings, let's start by writing a callable (~ "function") that returns the desilike likelihood.

In [6]:
def BAOLikelihood(cosmo='external'):
    # cosmo = 'external' to tell desilike that cosmo will be provided externally
    observable1 = BAOCompressionObservable(data=[1., 1.], quantities=['qpar', 'qper'], z=0.5, cosmo=cosmo)
    observable2 = BAOCompressionObservable(data=[1.], quantities=['qiso'], z=1., cosmo=cosmo)
    likelihood = ObservablesGaussianLikelihood([observable1, observable2],
                                               covariance=np.diag([0.002, 0.002, 0.005]))
    return likelihood

Cobaya¶

'Dynamic' bindings¶

Cobaya is built such that we can provide likelihoods defined on-the-fly (i.e. not in a Python script), and run inference from Python directly.

In [7]:
from desilike.bindings.cobaya import CobayaLikelihoodFactory

# CobayaBAOLikelihood is a Cobaya Likelihood object
CobayaBAOLikelihood = CobayaLikelihoodFactory(BAOLikelihood, params=True)
[000001.73] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['qpar', 'qper'].
[000001.81] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['qiso'].
[000002.03] [0/1] 07-02 10:22  numexpr.utils             INFO     NumExpr defaulting to 8 threads.
In [8]:
from cosmoprimo.fiducial import DESI
cosmo = DESI()

# No magic here, this is all Cobaya stuff
params = {'Omega_m': {'prior': {'min': 0.1, 'max': 1.},
                      'ref': {'dist': 'norm', 'loc': 0.3, 'scale': 0.01},
                      'latex': '\Omega_{m}'},
          'omega_b': cosmo['omega_b'],
          'H0': cosmo['H0'],
          'A_s': cosmo['A_s'],
          'n_s': cosmo['n_s'],
          'tau_reio': cosmo['tau_reio']}

info = {'params': params,
        'likelihood': {'bao_likelihood': CobayaBAOLikelihood},
        'theory': {'classy': {'extra_args': {'N_ncdm': cosmo['N_ncdm'], 'N_ur': cosmo['N_ur']}}}}

from cobaya.model import get_model
model = get_model(info)
model.logposterior({'Omega_m': cosmo['Omega_m']})
[000002.27] [0/1] 07-02 10:22  classy                    INFO     `classy` module loaded successfully from /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/classy-3.2.0-py3.9-linux-x86_64.egg
[000002.35] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['qpar', 'qper'].
[000002.44] [0/1] 07-02 10:22  BAOCompressionObservable  INFO     Found quantities ['qiso'].
Out[8]:
LogPosterior(logpost=0.10471144781489061, logpriors=[0.10536051565782628], loglikes=array([-0.00064907]), derived=[], finite=False)
In [9]:
# Let's run MCMC!
info_sampler = {'mcmc': {'Rminus1_stop': 0.02}}
from cobaya.sampler import get_sampler
mcmc = get_sampler(info_sampler, model=model)
mcmc.run()
[000007.45] [0/1] 07-02 10:22  mcmc                      INFO     Getting initial point... (this may take a few seconds)
[000007.54] [0/1] 07-02 10:22  model                     INFO     Measuring speeds... (this may take a few seconds)
[000007.79] [0/1] 07-02 10:22  model                     INFO     Setting measured speeds (per sec): {bao_likelihood: 399.0, classy: 12.5}
[000007.79] [0/1] 07-02 10:22  mcmc                      INFO     Initial point: Omega_m:0.3151184
[000007.79] [0/1] 07-02 10:22  mcmc                      INFO     Covariance matrix not present. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
[000007.79] [0/1] 07-02 10:22  mcmc                      INFO     Sampling!
[000007.88] [0/1] 07-02 10:22  mcmc                      INFO     Progress @ 2023-07-02 10:22:39 : 1 steps taken, and 0 accepted.
[000011.29] [0/1] 07-02 10:22  mcmc                      INFO     Learn + convergence test @ 40 samples accepted.
[000011.30] [0/1] 07-02 10:22  mcmc                      INFO      - Acceptance rate: 1.000
[000011.30] [0/1] 07-02 10:22  mcmc                      INFO      - Convergence of means: R-1 = 2.029668 after 32 accepted steps
[000011.30] [0/1] 07-02 10:22  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000014.94] [0/1] 07-02 10:22  mcmc                      INFO     Learn + convergence test @ 80 samples accepted.
[000014.95] [0/1] 07-02 10:22  mcmc                      INFO      - Acceptance rate: 0.941
[000014.95] [0/1] 07-02 10:22  mcmc                      INFO      - Convergence of means: R-1 = 2.293076 after 64 accepted steps
[000014.95] [0/1] 07-02 10:22  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000019.73] [0/1] 07-02 10:22  mcmc                      INFO     Learn + convergence test @ 120 samples accepted.
[000019.74] [0/1] 07-02 10:22  mcmc                      INFO      - Acceptance rate: 0.774
[000019.74] [0/1] 07-02 10:22  mcmc                      INFO      - Convergence of means: R-1 = 0.646461 after 96 accepted steps
[000019.74] [0/1] 07-02 10:22  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000025.94] [0/1] 07-02 10:22  mcmc                      INFO     Learn + convergence test @ 160 samples accepted.
[000025.95] [0/1] 07-02 10:22  mcmc                      INFO      - Acceptance rate: 0.631
[000025.95] [0/1] 07-02 10:22  mcmc                      INFO      - Convergence of means: R-1 = 0.194300 after 128 accepted steps
[000025.95] [0/1] 07-02 10:22  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000028.78] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 200 samples accepted.
[000028.79] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.593
[000028.79] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.651474 after 160 accepted steps
[000028.79] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000031.65] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 240 samples accepted.
[000031.66] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.558
[000031.66] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.089038 after 192 accepted steps
[000031.66] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000035.02] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 280 samples accepted.
[000035.02] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.528
[000035.02] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.011035 after 224 accepted steps
[000035.03] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000037.95] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 320 samples accepted.
[000037.95] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.526
[000037.95] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.090079 after 256 accepted steps
[000037.96] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000041.74] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 360 samples accepted.
[000041.74] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.500
[000041.74] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.015248 after 288 accepted steps
[000041.74] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000044.27] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 400 samples accepted.
[000044.28] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.507
[000044.28] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.070305 after 320 accepted steps
[000044.28] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000047.24] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 440 samples accepted.
[000047.24] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.506
[000047.24] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.043942 after 352 accepted steps
[000047.24] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000050.36] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 480 samples accepted.
[000050.37] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.496
[000050.37] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.004447 after 384 accepted steps
[000050.37] [0/1] 07-02 10:23  mcmc                      INFO      - Updated covariance matrix of proposal pdf.
[000054.13] [0/1] 07-02 10:23  mcmc                      INFO     Learn + convergence test @ 520 samples accepted.
[000054.13] [0/1] 07-02 10:23  mcmc                      INFO      - Acceptance rate: 0.478
[000054.14] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of means: R-1 = 0.016915 after 416 accepted steps
[000054.15] [0/1] 07-02 10:23  mcmc                      INFO      - Convergence of bounds: R-1 = 0.097983 after 520 accepted steps
[000054.15] [0/1] 07-02 10:23  mcmc                      INFO     The run has converged!
[000054.15] [0/1] 07-02 10:23  mcmc                      INFO     Sampling complete after 520 accepted steps.
In [10]:
from getdist.mcsamples import MCSamplesFromCobaya
samples_bao_cobaya = mcmc.samples(combined=True, skip_samples=0.5, to_getdist=True).copy(label='cobaya')
from getdist import plots
g = plots.get_subplot_plotter()
g.triangle_plot(samples_bao_cobaya, params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
[000054.16] [0/1] 07-02 10:23  root                      WARNING  outlier fraction 0.08076923076923077

Interlude: let's do the same within desilike¶

In [11]:
from desilike.samplers import MCMCSampler

from desilike.theories import Cosmoprimo
cosmo = Cosmoprimo(fiducial='DESI')
# Set Cosmoprimo calculator's parameters
cosmo.init.params = {'Omega_m': {'prior': {'limits': [0.1, 1.]},
                                 'ref': {'dist': 'norm', 'loc': 0.3, 'scale': 0.01},
                                 'latex': '\Omega_m'}}
sampler = MCMCSampler(BAOLikelihood(cosmo=cosmo), seed=42)
chains = sampler.run(check={'max_eigen_gr': 0.03, 'stable_over': 2}, check_every=40)
# do help(chains[0]) to get info on the available methods!
samples_bao_desilike = chains[0].remove_burnin(0.5).to_getdist(label='desilike')
[000054.78] [0/1] 07-02 10:23  BAOCompressionObservable  INFO     Found quantities ['qpar', 'qper'].
[000054.84] [0/1] 07-02 10:23  BAOCompressionObservable  INFO     Found quantities ['qiso'].
[000054.96] [0/1] 07-02 10:23  MCMCSampler               INFO     Varied parameters: ['Omega_m'].
[000055.50] [0/1] 07-02 10:23  BasePipeline              INFO     Found speeds:
[000055.50] [0/1] 07-02 10:23  BasePipeline              INFO     - <desilike.theories.primordial_cosmology.Cosmoprimo object at 0x7f1829effb20>: 1157.94 iterations / second
[000055.50] [0/1] 07-02 10:23  BasePipeline              INFO     - <desilike.theories.galaxy_clustering.power_template.BAOExtractor object at 0x7f1829e91370>: 22.03 iterations / second
[000055.51] [0/1] 07-02 10:23  BasePipeline              INFO     - <desilike.observables.galaxy_clustering.compression.BAOCompressionObservable object at 0x7f1829ea7ca0>: 4391.94 iterations / second
[000055.51] [0/1] 07-02 10:23  BasePipeline              INFO     - <desilike.theories.galaxy_clustering.power_template.BAOExtractor object at 0x7f1829e91700>: 12531.53 iterations / second
[000055.51] [0/1] 07-02 10:23  BasePipeline              INFO     - <desilike.observables.galaxy_clustering.compression.BAOCompressionObservable object at 0x7f1829ea75e0>: 9226.36 iterations / second
[000055.51] [0/1] 07-02 10:23  BasePipeline              INFO     - <desilike.likelihoods.base.ObservablesGaussianLikelihood object at 0x7f1829e8b2b0>: 4640.23 iterations / second
[000057.76] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000057.76] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 1.6; not < 0.03.
[000057.76] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 1.6.
[000057.78] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 2.04.
[000057.78] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is nan.
[000057.78] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000057.78] [0/1] 07-02 10:23  MCMCSampler               INFO     - (20 iterations / integrated autocorrelation time) is 32.5.
[000057.84] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000060.64] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000060.65] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 1.07; not < 0.03.
[000060.65] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 1.07.
[000060.66] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 3.79.
[000060.66] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is nan.
[000060.66] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000060.66] [0/1] 07-02 10:23  MCMCSampler               INFO     - (40 iterations / integrated autocorrelation time) is 13.7.
[000060.66] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.789.
[000060.73] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000064.27] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000064.27] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0663; not < 0.03.
[000064.27] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0663.
[000064.29] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.776.
[000064.29] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 3.28.
[000064.29] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000064.29] [0/1] 07-02 10:23  MCMCSampler               INFO     - (60 iterations / integrated autocorrelation time) (reliable) is 557.
[000064.29] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 26.1.
[000064.35] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000067.87] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000067.88] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.165; not < 0.03.
[000067.88] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.165.
[000067.90] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.439.
[000067.90] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 2.38.
[000067.90] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000067.90] [0/1] 07-02 10:23  MCMCSampler               INFO     - (80 iterations / integrated autocorrelation time) (reliable) is 115.
[000067.90] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.846.
[000067.96] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000071.53] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000071.53] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0549; not < 0.03.
[000071.53] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0549.
[000071.55] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.128.
[000071.55] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 1.35.
[000071.55] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000071.55] [0/1] 07-02 10:23  MCMCSampler               INFO     - (100 iterations / integrated autocorrelation time) is 45.4.
[000071.55] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.684.
[000071.61] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000075.51] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000075.52] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0152; < 0.03.
[000075.52] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0152.
[000075.54] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.104.
[000075.54] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 0.609.
[000075.54] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000075.54] [0/1] 07-02 10:23  MCMCSampler               INFO     - (120 iterations / integrated autocorrelation time) (reliable) is 154.
[000075.54] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 1.83.
[000075.61] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000079.50] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000079.50] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0706; not < 0.03.
[000079.51] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0706.
[000079.52] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.103.
[000079.53] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 0.606.
[000079.53] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000079.53] [0/1] 07-02 10:23  MCMCSampler               INFO     - (140 iterations / integrated autocorrelation time) (reliable) is 130.
[000079.53] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.276.
[000079.59] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000083.07] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000083.07] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0264; < 0.03.
[000083.08] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0264.
[000083.09] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.0624.
[000083.10] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 0.43.
[000083.10] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000083.10] [0/1] 07-02 10:23  MCMCSampler               INFO     - (160 iterations / integrated autocorrelation time) (reliable) is 160.
[000083.10] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.0771.
[000083.16] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000086.97] [0/1] 07-02 10:23  MCMCSampler               INFO     Diagnostics:
[000086.97] [0/1] 07-02 10:23  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0308; not < 0.03.
[000086.97] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0308.
[000086.99] [0/1] 07-02 10:23  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.177.
[000087.00] [0/1] 07-02 10:23  MCMCSampler               INFO     - max Geweke is 2.62.
[000087.00] [0/1] 07-02 10:23  MCMCSampler               INFO     - Geweke p-value is nan.
[000087.00] [0/1] 07-02 10:23  MCMCSampler               INFO     - (180 iterations / integrated autocorrelation time) (reliable) is 177.
[000087.00] [0/1] 07-02 10:23  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.0201.
[000087.05] [0/1] 07-02 10:23  MCMCSampler               INFO     Updating proposal covariance.
[000091.36] [0/1] 07-02 10:24  MCMCSampler               INFO     Diagnostics:
[000091.36] [0/1] 07-02 10:24  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.015; < 0.03.
[000091.37] [0/1] 07-02 10:24  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.015.
[000091.39] [0/1] 07-02 10:24  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.103.
[000091.39] [0/1] 07-02 10:24  MCMCSampler               INFO     - max Geweke is 0.747.
[000091.39] [0/1] 07-02 10:24  MCMCSampler               INFO     - Geweke p-value is nan.
[000091.39] [0/1] 07-02 10:24  MCMCSampler               INFO     - (200 iterations / integrated autocorrelation time) (reliable) is 207.
[000091.39] [0/1] 07-02 10:24  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.0558.
[000091.45] [0/1] 07-02 10:24  MCMCSampler               INFO     Updating proposal covariance.
[000095.19] [0/1] 07-02 10:24  MCMCSampler               INFO     Diagnostics:
[000095.20] [0/1] 07-02 10:24  MCMCSampler               INFO     - max eigen Gelman-Rubin - 1 is 0.0264; < 0.03.
[000095.20] [0/1] 07-02 10:24  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 is 0.0264.
[000095.22] [0/1] 07-02 10:24  MCMCSampler               INFO     - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.118.
[000095.23] [0/1] 07-02 10:24  MCMCSampler               INFO     - max Geweke is 0.548.
[000095.23] [0/1] 07-02 10:24  MCMCSampler               INFO     - Geweke p-value is nan.
[000095.23] [0/1] 07-02 10:24  MCMCSampler               INFO     - (220 iterations / integrated autocorrelation time) (reliable) is 159.
[000095.23] [0/1] 07-02 10:24  MCMCSampler               INFO     - max variation of integrated autocorrelation time is 0.3.
[000095.23] [0/1] 07-02 10:24  root                      WARNING  outlier fraction 0.11363636363636363
In [12]:
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike],
                 params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})

'Static' bindings¶

Other inference codes (CosmoSIS, MontePython) typically require the likelihood to be written down in a file, such that it is imported by the code. Let's illustrate this, still with Cobaya.

In [15]:
%%file _tests/bao_likelihood.py

dirname = '.'

def BAOLikelihood(cosmo='external'):
    import numpy as np
    from desilike.observables.galaxy_clustering import BAOCompressionObservable
    from desilike.likelihoods import ObservablesGaussianLikelihood
    # cosmo = 'external' to tell desilike that cosmo will be provided externally
    observable1 = BAOCompressionObservable(data=[1., 1.], quantities=['qpar', 'qper'], z=0.5, cosmo=cosmo)
    observable2 = BAOCompressionObservable(data=[1.], quantities=['qiso'], z=1., cosmo=cosmo)
    likelihood = ObservablesGaussianLikelihood([observable1, observable2],
                                               covariance=np.diag([0.002, 0.002, 0.005]))
    return likelihood

if __name__ == '__main__':
    from desilike.bindings import CobayaLikelihoodGenerator
    # We could provide a list of Likelihoods, which will all be written at once
    CobayaLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
Writing _tests/bao_likelihood.py

Let's generate the static bindings by calling the above Python script

In [16]:
%%bash
cd _tests/
python bao_likelihood.py
bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by bash)
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)

Let's take a look at the generated files:

  • the Python module containing the Cobaya likelihood: bao_likelihood.py
  • imported in the __init__.py
  • the .yaml config file containing the nuisance parameters (none in this case)
In [17]:
!ls -la _tests/cobaya
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 20
drwxr-xr-x 2 adematti idphp 4096 juil.  2 10:24 .
drwxr-xr-x 3 adematti idphp 4096 juil.  2 10:24 ..
-rw-r--r-- 1 adematti idphp  477 juil.  2 10:24 bao_likelihood.py
-rw-r--r-- 1 adematti idphp   31 juil.  2 10:24 BAOLikelihood.yaml
-rw-r--r-- 1 adematti idphp   30 juil.  2 10:24 __init__.py
In [19]:
# %load _tests/cobaya/my_likelihood.py
# NOTE: This code has been automatically generated by desilike.bindings.cobaya.factory.CobayaLikelihoodGenerator
from desilike.bindings.cobaya.factory import CobayaLikelihoodFactory

from desilike.bindings.base import load_from_file
BAOLikelihood = load_from_file('/home/adematti/Bureau/DESI/NERSC/cosmodesi/desilike-tutorials/_tests/bao_likelihood.py', 'BAOLikelihood')
BAOLikelihood = CobayaLikelihoodFactory(BAOLikelihood, 'BAOLikelihood',
                                        {'cosmo': 'external'}, __name__)

Now let's write the config file to run inference. This is pure Cobaya.

In [20]:
%%file _tests/config_bao.yaml

theory:
  classy:
    extra_args:
      N_ncdm: 1
      N_ur: 2.0328

likelihood:
  bao_likelihood.BAOLikelihood:
      python_path: _tests/cobaya

params:
  Omega_m:
    prior:
      min: 0.1
      max: 1.
    ref:
      dist: norm
      loc: 0.3
      scale: 0.01
    latex: \Omega_{m}
  omega_b: 0.02237
  H0: 67.36
  As: 2.083e-09
  n_s: 0.9649
  tau_reio: 0.0544

sampler:
  mcmc:
    Rminus1_stop: 0.02

debug: True

output: _tests/chains_bao_cobaya/chain
Writing _tests/config_bao.yaml

Let's sample!

In [21]:
!cobaya-run _tests/config_bao.yaml
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
 2023-07-02 10:24:11,168 [output] Creating output folder '_tests/chains_bao_cobaya'
 2023-07-02 10:24:11,168 [output] Output to be read-from/written-into folder '_tests/chains_bao_cobaya', with prefix 'chain'
 2023-07-02 10:24:14,042 [root] Initializing MLIR with module: _mlirRegisterEverything
 2023-07-02 10:24:14,042 [root] Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._mlirRegisterEverything' from '/home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/jaxlib/mlir/_mlir_libs/_mlirRegisterEverything.so'>
 2023-07-02 10:24:14,212 [absl] Finished tracing + transforming prim_fun for jit in 0.00026226043701171875 sec
 2023-07-02 10:24:14,212 [absl] Initializing backend 'interpreter'
 2023-07-02 10:24:14,213 [absl] Backend 'interpreter' initialized
 2023-07-02 10:24:14,213 [absl] Initializing backend 'cpu'
 2023-07-02 10:24:14,214 [absl] Backend 'cpu' initialized
 2023-07-02 10:24:14,214 [absl] Initializing backend 'tpu_driver'
 2023-07-02 10:24:14,215 [absl] Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker:
 2023-07-02 10:24:14,215 [absl] Initializing backend 'cuda'
 2023-07-02 10:24:14,215 [absl] Unable to initialize backend 'cuda': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
 2023-07-02 10:24:14,215 [absl] Initializing backend 'rocm'
 2023-07-02 10:24:14,215 [absl] Unable to initialize backend 'rocm': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
 2023-07-02 10:24:14,215 [absl] Initializing backend 'tpu'
 2023-07-02 10:24:14,216 [absl] Unable to initialize backend 'tpu': INVALID_ARGUMENT: TpuPlatform is not available.
 2023-07-02 10:24:14,216 [absl] *WARNING* No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
 2023-07-02 10:24:14,216 [absl] Compiling prim_fun (139946428465856 for args (ShapedArray(int64[]),).
 2023-07-02 10:24:14,227 [absl] Finished XLA compilation of convert_element_type in 0.008483171463012695 sec
 2023-07-02 10:24:14,517 [classy] Attempting global import (no `path` or Cobaya installation path given).
 2023-07-02 10:24:14,519 [classy] `classy` module loaded successfully from /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/classy-3.2.0-py3.9-linux-x86_64.egg
 2023-07-02 10:24:14,585 [BAOCompressionObservable] Found quantities ['qpar', 'qper'].
 2023-07-02 10:24:14,640 [BAOCompressionObservable] Found quantities ['qiso'].
 2023-07-02 10:24:14,807 [model] Parameters were assigned as follows:
 2023-07-02 10:24:14,807 [model] - bao_likelihood.BAOLikelihood:
 2023-07-02 10:24:14,807 [model]      Input:  []
 2023-07-02 10:24:14,807 [model]      Output: []
 2023-07-02 10:24:14,807 [model] - classy:
 2023-07-02 10:24:14,807 [model]      Input:  ['Omega_m', 'omega_b', 'H0', 'As', 'n_s', 'tau_reio']
 2023-07-02 10:24:14,807 [model]      Output: []
 2023-07-02 10:24:14,809 [model] Components will be computed in the order:
 2023-07-02 10:24:14,809 [model]  - [classy, bao_likelihood.BAOLikelihood]
 2023-07-02 10:24:14,809 [model] Requirements will be calculated by these components:
 2023-07-02 10:24:14,809 [model] - rdrag: classy
 2023-07-02 10:24:14,809 [model] - Hubble: classy
 2023-07-02 10:24:14,809 [model] - angular_diameter_distance: classy
 2023-07-02 10:24:14,814 [mcmc] Initializing
 2023-07-02 10:24:14,817 [mcmc] Getting initial point... (this may take a few seconds)
 2023-07-02 10:24:14,817 [prior] Evaluating prior at array([0.30227319])
 2023-07-02 10:24:14,817 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:14,817 [model] Posterior to be computed for parameters {'Omega_m': 0.302273186715765}
 2023-07-02 10:24:14,817 [prior] Evaluating prior at array([0.30227319])
 2023-07-02 10:24:14,818 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:14,818 [model] Got input parameters: {'Omega_m': 0.302273186715765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:14,818 [classy] Got parameters {'Omega_m': 0.302273186715765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:14,818 [classy] Computing new state
 2023-07-02 10:24:14,818 [classy] Setting parameters: {'Omega_m': 0.302273186715765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:14,869 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.5068711292102}
 2023-07-02 10:24:14,869 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:14,870 [absl] Finished tracing + transforming prim_fun for jit in 0.0002644062042236328 sec
 2023-07-02 10:24:14,871 [absl] Finished tracing + transforming prim_fun for jit in 0.00018143653869628906 sec
 2023-07-02 10:24:14,871 [absl] Finished tracing + transforming prim_fun for jit in 0.00018143653869628906 sec
 2023-07-02 10:24:14,872 [absl] Compiling prim_fun (139946281779584 for args (ShapedArray(float64[2]), ShapedArray(float64[1])).
 2023-07-02 10:24:14,883 [absl] Finished XLA compilation of concatenate in 0.008332014083862305 sec
 2023-07-02 10:24:14,884 [absl] Finished tracing + transforming <lambda> for jit in 0.0003628730773925781 sec
 2023-07-02 10:24:14,884 [absl] Compiling <lambda> (139945829539904 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
 2023-07-02 10:24:14,895 [absl] Finished XLA compilation of <lambda> in 0.008444547653198242 sec
 2023-07-02 10:24:14,898 [absl] Finished tracing + transforming dot for jit in 0.0008070468902587891 sec
 2023-07-02 10:24:14,898 [absl] Compiling dot (139945829539984 for args (ShapedArray(float64[3]), ShapedArray(float64[3,3])).
 2023-07-02 10:24:14,918 [absl] Finished XLA compilation of dot in 0.015986919403076172 sec
 2023-07-02 10:24:14,921 [absl] Finished tracing + transforming dot for jit in 0.0007879734039306641 sec
 2023-07-02 10:24:14,921 [absl] Compiling dot (139945829540384 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
 2023-07-02 10:24:14,941 [absl] Finished XLA compilation of dot in 0.012113094329833984 sec
 2023-07-02 10:24:14,942 [absl] Finished tracing + transforming fn for jit in 0.0004296302795410156 sec
 2023-07-02 10:24:14,943 [absl] Compiling fn (139945829540064 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[])).
 2023-07-02 10:24:14,952 [absl] Finished XLA compilation of fn in 0.006169557571411133 sec
 2023-07-02 10:24:14,953 [absl] Finished tracing + transforming fn for jit in 0.0004942417144775391 sec
 2023-07-02 10:24:14,953 [absl] Compiling fn (139945829540224 for args (ShapedArray(float64[]), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:24:14,962 [absl] Finished XLA compilation of fn in 0.0065000057220458984 sec
 2023-07-02 10:24:14,964 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00676172
 2023-07-02 10:24:14,964 [model] Computed derived parameters: {}
 2023-07-02 10:24:14,964 [model] Measuring speeds... (this may take a few seconds)
 2023-07-02 10:24:14,964 [prior] Evaluating prior at array([0.2995852])
 2023-07-02 10:24:14,964 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:14,964 [model] Got input parameters: {'Omega_m': 0.29958519951716434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:14,964 [classy] Got parameters {'Omega_m': 0.29958519951716434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:14,964 [classy] Computing new state
 2023-07-02 10:24:14,964 [classy] Setting parameters: {'Omega_m': 0.29958519951716434, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,015 [classy] First evaluation time: 0.0505338 s
 2023-07-02 10:24:15,015 [classy] Average evaluation time: 0.0505338 s
 2023-07-02 10:24:15,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.84123435525387}
 2023-07-02 10:24:15,015 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0107415
 2023-07-02 10:24:15,017 [bao_likelihood.baolikelihood] First evaluation time: 0.00203782 s
 2023-07-02 10:24:15,017 [bao_likelihood.baolikelihood] Average evaluation time: 0.00203782 s
 2023-07-02 10:24:15,017 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,017 [prior] Evaluating prior at array([0.32097431])
 2023-07-02 10:24:15,018 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,018 [model] Got input parameters: {'Omega_m': 0.32097431344246147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,018 [classy] Got parameters {'Omega_m': 0.32097431344246147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,018 [classy] Computing new state
 2023-07-02 10:24:15,018 [classy] Setting parameters: {'Omega_m': 0.32097431344246147, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,073 [classy] Average evaluation time: 0.0555832 s
 2023-07-02 10:24:15,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.25067556440436}
 2023-07-02 10:24:15,074 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,076 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00453072
 2023-07-02 10:24:15,076 [bao_likelihood.baolikelihood] Average evaluation time: 0.00288756 s
 2023-07-02 10:24:15,076 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,077 [prior] Evaluating prior at array([0.30121144])
 2023-07-02 10:24:15,077 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,077 [model] Got input parameters: {'Omega_m': 0.30121144035944686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,077 [classy] Got parameters {'Omega_m': 0.30121144035944686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,077 [classy] Computing new state
 2023-07-02 10:24:15,077 [classy] Setting parameters: {'Omega_m': 0.30121144035944686, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,134 [classy] Average evaluation time: 0.0561591 s
 2023-07-02 10:24:15,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6386245798302}
 2023-07-02 10:24:15,134 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,136 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00821818
 2023-07-02 10:24:15,136 [bao_likelihood.baolikelihood] Average evaluation time: 0.00237307 s
 2023-07-02 10:24:15,136 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,136 [model] Computed 3 points to measure speeds.
 2023-07-02 10:24:15,136 [model] Setting measured speeds (per sec): {bao_likelihood.BAOLikelihood: 421.0, classy: 17.8}
 2023-07-02 10:24:15,136 [mcmc] Initial point: Omega_m:0.3022732
 2023-07-02 10:24:15,136 [model] Cost, oversampling factor and parameters per block, in optimal order:
 2023-07-02 10:24:15,136 [model] * 0.0591324 : 1 : ['Omega_m']
 2023-07-02 10:24:15,136 [mcmc] Cycle length in steps: 1
 2023-07-02 10:24:15,137 [mcmc] Covariance matrix not present. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
 2023-07-02 10:24:15,138 [mcmc] Sampling with covmat:
          Omega_m
Omega_m  0.000025
 2023-07-02 10:24:15,148 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:15,153 [mcmc] Sampling!
 2023-07-02 10:24:15,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3007991086649757}
 2023-07-02 10:24:15,153 [prior] Evaluating prior at array([0.30079911])
 2023-07-02 10:24:15,153 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,153 [model] Got input parameters: {'Omega_m': 0.3007991086649757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,153 [classy] Got parameters {'Omega_m': 0.3007991086649757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,153 [classy] Computing new state
 2023-07-02 10:24:15,153 [classy] Setting parameters: {'Omega_m': 0.3007991086649757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.689900976284}
 2023-07-02 10:24:15,206 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00882428
 2023-07-02 10:24:15,208 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,208 [mcmc] Burn-in sample:
   Omega_m:0.3022732
 2023-07-02 10:24:15,208 [mcmc] Progress @ 2023-07-02 10:24:15 : 1 steps taken, and 0 accepted.
 2023-07-02 10:24:15,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32315842225220176}
 2023-07-02 10:24:15,208 [prior] Evaluating prior at array([0.32315842])
 2023-07-02 10:24:15,208 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,208 [model] Got input parameters: {'Omega_m': 0.32315842225220176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,208 [classy] Got parameters {'Omega_m': 0.32315842225220176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,208 [classy] Computing new state
 2023-07-02 10:24:15,208 [classy] Setting parameters: {'Omega_m': 0.32315842225220176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99485620641119}
 2023-07-02 10:24:15,264 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,267 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00700766
 2023-07-02 10:24:15,268 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,268 [mcmc] New sample, #1:
   Omega_m:0.3007991
 2023-07-02 10:24:15,268 [model] Posterior to be computed for parameters {'Omega_m': 0.33789596472574496}
 2023-07-02 10:24:15,268 [prior] Evaluating prior at array([0.33789596])
 2023-07-02 10:24:15,268 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,268 [model] Got input parameters: {'Omega_m': 0.33789596472574496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,268 [classy] Got parameters {'Omega_m': 0.33789596472574496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,268 [classy] Computing new state
 2023-07-02 10:24:15,268 [classy] Setting parameters: {'Omega_m': 0.33789596472574496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,331 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.3082409272329}
 2023-07-02 10:24:15,331 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,333 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0374296
 2023-07-02 10:24:15,333 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,333 [mcmc] New sample, #2:
   Omega_m:0.3231584
 2023-07-02 10:24:15,333 [model] Posterior to be computed for parameters {'Omega_m': 0.32413007886776585}
 2023-07-02 10:24:15,333 [prior] Evaluating prior at array([0.32413008])
 2023-07-02 10:24:15,333 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,333 [model] Got input parameters: {'Omega_m': 0.32413007886776585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,333 [classy] Got parameters {'Omega_m': 0.32413007886776585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,333 [classy] Computing new state
 2023-07-02 10:24:15,333 [classy] Setting parameters: {'Omega_m': 0.32413007886776585, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8815414956248}
 2023-07-02 10:24:15,384 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00828395
 2023-07-02 10:24:15,386 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,386 [mcmc] New sample, #3:
   Omega_m:0.337896
 2023-07-02 10:24:15,386 [model] Posterior to be computed for parameters {'Omega_m': 0.33083201785663213}
 2023-07-02 10:24:15,386 [prior] Evaluating prior at array([0.33083202])
 2023-07-02 10:24:15,386 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,386 [model] Got input parameters: {'Omega_m': 0.33083201785663213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,386 [classy] Got parameters {'Omega_m': 0.33083201785663213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,386 [classy] Computing new state
 2023-07-02 10:24:15,386 [classy] Setting parameters: {'Omega_m': 0.33083201785663213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,438 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1081750507962}
 2023-07-02 10:24:15,438 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,440 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0199404
 2023-07-02 10:24:15,440 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,440 [mcmc] New sample, #4:
   Omega_m:0.3241301
 2023-07-02 10:24:15,441 [model] Posterior to be computed for parameters {'Omega_m': 0.33607200100876394}
 2023-07-02 10:24:15,441 [prior] Evaluating prior at array([0.336072])
 2023-07-02 10:24:15,441 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,441 [model] Got input parameters: {'Omega_m': 0.33607200100876394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,441 [classy] Got parameters {'Omega_m': 0.33607200100876394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,441 [classy] Computing new state
 2023-07-02 10:24:15,441 [classy] Setting parameters: {'Omega_m': 0.33607200100876394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,496 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.51333283236454}
 2023-07-02 10:24:15,497 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,498 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0324167
 2023-07-02 10:24:15,498 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,499 [mcmc] New sample, #5:
   Omega_m:0.330832
 2023-07-02 10:24:15,499 [model] Posterior to be computed for parameters {'Omega_m': 0.33952887817032834}
 2023-07-02 10:24:15,499 [prior] Evaluating prior at array([0.33952888])
 2023-07-02 10:24:15,499 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,499 [model] Got input parameters: {'Omega_m': 0.33952887817032834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,499 [classy] Got parameters {'Omega_m': 0.33952887817032834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,499 [classy] Computing new state
 2023-07-02 10:24:15,499 [classy] Setting parameters: {'Omega_m': 0.33952887817032834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1254797896763}
 2023-07-02 10:24:15,567 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,569 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0422051
 2023-07-02 10:24:15,569 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,570 [mcmc] New sample, #6:
   Omega_m:0.336072
 2023-07-02 10:24:15,570 [model] Posterior to be computed for parameters {'Omega_m': 0.342473331012135}
 2023-07-02 10:24:15,570 [prior] Evaluating prior at array([0.34247333])
 2023-07-02 10:24:15,570 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,570 [model] Got input parameters: {'Omega_m': 0.342473331012135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,570 [classy] Got parameters {'Omega_m': 0.342473331012135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,570 [classy] Computing new state
 2023-07-02 10:24:15,570 [classy] Setting parameters: {'Omega_m': 0.342473331012135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.79792805596563}
 2023-07-02 10:24:15,619 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,620 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0514925
 2023-07-02 10:24:15,620 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,621 [mcmc] New sample, #7:
   Omega_m:0.3395289
 2023-07-02 10:24:15,621 [model] Posterior to be computed for parameters {'Omega_m': 0.3215200632916294}
 2023-07-02 10:24:15,621 [prior] Evaluating prior at array([0.32152006])
 2023-07-02 10:24:15,621 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,621 [model] Got input parameters: {'Omega_m': 0.3215200632916294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,621 [classy] Got parameters {'Omega_m': 0.3215200632916294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,621 [classy] Computing new state
 2023-07-02 10:24:15,621 [classy] Setting parameters: {'Omega_m': 0.3215200632916294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.18660752848703}
 2023-07-02 10:24:15,681 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0050985
 2023-07-02 10:24:15,683 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,683 [mcmc] New sample, #8:
   Omega_m:0.3424733
 2023-07-02 10:24:15,683 [model] Posterior to be computed for parameters {'Omega_m': 0.3117036623357385}
 2023-07-02 10:24:15,683 [prior] Evaluating prior at array([0.31170366])
 2023-07-02 10:24:15,683 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,683 [model] Got input parameters: {'Omega_m': 0.3117036623357385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,683 [classy] Got parameters {'Omega_m': 0.3117036623357385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,683 [classy] Computing new state
 2023-07-02 10:24:15,683 [classy] Setting parameters: {'Omega_m': 0.3117036623357385, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35412871793827}
 2023-07-02 10:24:15,743 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00023978
 2023-07-02 10:24:15,745 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,745 [mcmc] New sample, #9:
   Omega_m:0.3215201
 2023-07-02 10:24:15,745 [model] Posterior to be computed for parameters {'Omega_m': 0.3123373924246803}
 2023-07-02 10:24:15,745 [prior] Evaluating prior at array([0.31233739])
 2023-07-02 10:24:15,745 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,745 [model] Got input parameters: {'Omega_m': 0.3123373924246803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,745 [classy] Got parameters {'Omega_m': 0.3123373924246803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,745 [classy] Computing new state
 2023-07-02 10:24:15,745 [classy] Setting parameters: {'Omega_m': 0.3123373924246803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.27777077091875}
 2023-07-02 10:24:15,796 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000203686
 2023-07-02 10:24:15,798 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,798 [mcmc] New sample, #10:
   Omega_m:0.3117037
 2023-07-02 10:24:15,798 [model] Posterior to be computed for parameters {'Omega_m': 0.2932204999145311}
 2023-07-02 10:24:15,799 [prior] Evaluating prior at array([0.2932205])
 2023-07-02 10:24:15,799 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,799 [model] Got input parameters: {'Omega_m': 0.2932204999145311, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,799 [classy] Got parameters {'Omega_m': 0.2932204999145311, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,799 [classy] Computing new state
 2023-07-02 10:24:15,799 [classy] Setting parameters: {'Omega_m': 0.2932204999145311, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.6435741385667}
 2023-07-02 10:24:15,849 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0240966
 2023-07-02 10:24:15,851 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,851 [mcmc] New sample, #11:
   Omega_m:0.3123374
 2023-07-02 10:24:15,851 [model] Posterior to be computed for parameters {'Omega_m': 0.29947916769934524}
 2023-07-02 10:24:15,851 [prior] Evaluating prior at array([0.29947917])
 2023-07-02 10:24:15,851 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,851 [model] Got input parameters: {'Omega_m': 0.29947916769934524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,851 [classy] Got parameters {'Omega_m': 0.29947916769934524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,851 [classy] Computing new state
 2023-07-02 10:24:15,851 [classy] Setting parameters: {'Omega_m': 0.29947916769934524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.85447580462787}
 2023-07-02 10:24:15,901 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0109183
 2023-07-02 10:24:15,903 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,903 [mcmc] New sample, #12:
   Omega_m:0.2932205
 2023-07-02 10:24:15,903 [model] Posterior to be computed for parameters {'Omega_m': 0.2900981027279275}
 2023-07-02 10:24:15,903 [prior] Evaluating prior at array([0.2900981])
 2023-07-02 10:24:15,903 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,903 [model] Got input parameters: {'Omega_m': 0.2900981027279275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,903 [classy] Got parameters {'Omega_m': 0.2900981027279275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,903 [classy] Computing new state
 2023-07-02 10:24:15,903 [classy] Setting parameters: {'Omega_m': 0.2900981027279275, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:15,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.0427302927278}
 2023-07-02 10:24:15,953 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:15,955 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0327323
 2023-07-02 10:24:15,955 [model] Computed derived parameters: {}
 2023-07-02 10:24:15,955 [mcmc] New sample, #13:
   Omega_m:0.2994792
 2023-07-02 10:24:15,955 [model] Posterior to be computed for parameters {'Omega_m': 0.2691868700159219}
 2023-07-02 10:24:15,955 [prior] Evaluating prior at array([0.26918687])
 2023-07-02 10:24:15,955 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:15,955 [model] Got input parameters: {'Omega_m': 0.2691868700159219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,955 [classy] Got parameters {'Omega_m': 0.2691868700159219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:15,955 [classy] Computing new state
 2023-07-02 10:24:15,955 [classy] Setting parameters: {'Omega_m': 0.2691868700159219, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.8156274119291}
 2023-07-02 10:24:16,015 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.128845
 2023-07-02 10:24:16,017 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,017 [model] Posterior to be computed for parameters {'Omega_m': 0.280471289320419}
 2023-07-02 10:24:16,017 [prior] Evaluating prior at array([0.28047129])
 2023-07-02 10:24:16,017 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,017 [model] Got input parameters: {'Omega_m': 0.280471289320419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,017 [classy] Got parameters {'Omega_m': 0.280471289320419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,017 [classy] Computing new state
 2023-07-02 10:24:16,017 [classy] Setting parameters: {'Omega_m': 0.280471289320419, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,064 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.29724526202205}
 2023-07-02 10:24:16,064 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,066 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684299
 2023-07-02 10:24:16,066 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,066 [mcmc] New sample, #14:
   Omega_m:0.2900981
 2023-07-02 10:24:16,067 [model] Posterior to be computed for parameters {'Omega_m': 0.2912250387630257}
 2023-07-02 10:24:16,067 [prior] Evaluating prior at array([0.29122504])
 2023-07-02 10:24:16,067 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,067 [model] Got input parameters: {'Omega_m': 0.2912250387630257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,067 [classy] Got parameters {'Omega_m': 0.2912250387630257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,067 [classy] Computing new state
 2023-07-02 10:24:16,067 [classy] Setting parameters: {'Omega_m': 0.2912250387630257, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.89823836186707}
 2023-07-02 10:24:16,116 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0294539
 2023-07-02 10:24:16,118 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,118 [mcmc] New sample, #15:
   Omega_m:0.2804713
 2023-07-02 10:24:16,118 [model] Posterior to be computed for parameters {'Omega_m': 0.27609166145454084}
 2023-07-02 10:24:16,118 [prior] Evaluating prior at array([0.27609166])
 2023-07-02 10:24:16,118 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,118 [model] Got input parameters: {'Omega_m': 0.27609166145454084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,118 [classy] Got parameters {'Omega_m': 0.27609166145454084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,118 [classy] Computing new state
 2023-07-02 10:24:16,118 [classy] Setting parameters: {'Omega_m': 0.27609166145454084, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.88025221398976}
 2023-07-02 10:24:16,167 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,169 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0894095
 2023-07-02 10:24:16,169 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,169 [mcmc] New sample, #16:
   Omega_m:0.291225
 2023-07-02 10:24:16,170 [model] Posterior to be computed for parameters {'Omega_m': 0.29479639688293596}
 2023-07-02 10:24:16,170 [prior] Evaluating prior at array([0.2947964])
 2023-07-02 10:24:16,170 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,170 [model] Got input parameters: {'Omega_m': 0.29479639688293596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,170 [classy] Got parameters {'Omega_m': 0.29479639688293596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,170 [classy] Computing new state
 2023-07-02 10:24:16,170 [classy] Setting parameters: {'Omega_m': 0.29479639688293596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4435138141882}
 2023-07-02 10:24:16,218 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0202653
 2023-07-02 10:24:16,220 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,220 [mcmc] New sample, #17:
   Omega_m:0.2760917
 2023-07-02 10:24:16,220 [model] Posterior to be computed for parameters {'Omega_m': 0.29865588582998637}
 2023-07-02 10:24:16,220 [prior] Evaluating prior at array([0.29865589])
 2023-07-02 10:24:16,220 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,220 [model] Got input parameters: {'Omega_m': 0.29865588582998637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,220 [classy] Got parameters {'Omega_m': 0.29865588582998637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,220 [classy] Computing new state
 2023-07-02 10:24:16,220 [classy] Setting parameters: {'Omega_m': 0.29865588582998637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9574512028558}
 2023-07-02 10:24:16,271 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,274 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123437
 2023-07-02 10:24:16,274 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,275 [mcmc] New sample, #18:
   Omega_m:0.2947964
 2023-07-02 10:24:16,275 [model] Posterior to be computed for parameters {'Omega_m': 0.29723500560955995}
 2023-07-02 10:24:16,275 [prior] Evaluating prior at array([0.29723501])
 2023-07-02 10:24:16,276 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,276 [model] Got input parameters: {'Omega_m': 0.29723500560955995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,276 [classy] Got parameters {'Omega_m': 0.29723500560955995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,276 [classy] Computing new state
 2023-07-02 10:24:16,276 [classy] Setting parameters: {'Omega_m': 0.29723500560955995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.13575844311157}
 2023-07-02 10:24:16,324 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150211
 2023-07-02 10:24:16,327 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,327 [mcmc] New sample, #19:
   Omega_m:0.2986559
 2023-07-02 10:24:16,327 [model] Posterior to be computed for parameters {'Omega_m': 0.28305010515806117}
 2023-07-02 10:24:16,327 [prior] Evaluating prior at array([0.28305011])
 2023-07-02 10:24:16,327 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,327 [model] Got input parameters: {'Omega_m': 0.28305010515806117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,327 [classy] Got parameters {'Omega_m': 0.28305010515806117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,327 [classy] Computing new state
 2023-07-02 10:24:16,327 [classy] Setting parameters: {'Omega_m': 0.28305010515806117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.95758563130443}
 2023-07-02 10:24:16,378 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,381 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0574878
 2023-07-02 10:24:16,381 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,381 [mcmc] New sample, #20:
   Omega_m:0.297235
 2023-07-02 10:24:16,381 [model] Posterior to be computed for parameters {'Omega_m': 0.28073149980625695}
 2023-07-02 10:24:16,381 [prior] Evaluating prior at array([0.2807315])
 2023-07-02 10:24:16,381 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,381 [model] Got input parameters: {'Omega_m': 0.28073149980625695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,381 [classy] Got parameters {'Omega_m': 0.28073149980625695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,381 [classy] Computing new state
 2023-07-02 10:24:16,381 [classy] Setting parameters: {'Omega_m': 0.28073149980625695, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.26285158142838}
 2023-07-02 10:24:16,433 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.067279
 2023-07-02 10:24:16,436 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,436 [mcmc] New sample, #21:
   Omega_m:0.2830501
 2023-07-02 10:24:16,436 [model] Posterior to be computed for parameters {'Omega_m': 0.29223660116766337}
 2023-07-02 10:24:16,436 [prior] Evaluating prior at array([0.2922366])
 2023-07-02 10:24:16,437 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,437 [model] Got input parameters: {'Omega_m': 0.29223660116766337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,437 [classy] Got parameters {'Omega_m': 0.29223660116766337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,437 [classy] Computing new state
 2023-07-02 10:24:16,437 [classy] Setting parameters: {'Omega_m': 0.29223660116766337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7689546038691}
 2023-07-02 10:24:16,488 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,490 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0266671
 2023-07-02 10:24:16,490 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,490 [mcmc] New sample, #22:
   Omega_m:0.2807315
 2023-07-02 10:24:16,490 [model] Posterior to be computed for parameters {'Omega_m': 0.2969693279596925}
 2023-07-02 10:24:16,490 [prior] Evaluating prior at array([0.29696933])
 2023-07-02 10:24:16,490 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,490 [model] Got input parameters: {'Omega_m': 0.2969693279596925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,490 [classy] Got parameters {'Omega_m': 0.2969693279596925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,490 [classy] Computing new state
 2023-07-02 10:24:16,490 [classy] Setting parameters: {'Omega_m': 0.2969693279596925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,541 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1691800298089}
 2023-07-02 10:24:16,542 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0155525
 2023-07-02 10:24:16,546 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,546 [mcmc] New sample, #23:
   Omega_m:0.2922366
 2023-07-02 10:24:16,546 [model] Posterior to be computed for parameters {'Omega_m': 0.297233934750986}
 2023-07-02 10:24:16,546 [prior] Evaluating prior at array([0.29723393])
 2023-07-02 10:24:16,547 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,547 [model] Got input parameters: {'Omega_m': 0.297233934750986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,547 [classy] Got parameters {'Omega_m': 0.297233934750986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,547 [classy] Computing new state
 2023-07-02 10:24:16,547 [classy] Setting parameters: {'Omega_m': 0.297233934750986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1358969285858}
 2023-07-02 10:24:16,598 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150234
 2023-07-02 10:24:16,600 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,600 [mcmc] New sample, #24:
   Omega_m:0.2969693
 2023-07-02 10:24:16,600 [model] Posterior to be computed for parameters {'Omega_m': 0.3499030775936966}
 2023-07-02 10:24:16,600 [prior] Evaluating prior at array([0.34990308])
 2023-07-02 10:24:16,601 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,601 [model] Got input parameters: {'Omega_m': 0.3499030775936966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,601 [classy] Got parameters {'Omega_m': 0.3499030775936966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,601 [classy] Computing new state
 2023-07-02 10:24:16,601 [classy] Setting parameters: {'Omega_m': 0.3499030775936966, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,652 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.98276014896697}
 2023-07-02 10:24:16,652 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,654 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.078679
 2023-07-02 10:24:16,654 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,654 [mcmc] New sample, #25:
   Omega_m:0.2972339
 2023-07-02 10:24:16,654 [model] Posterior to be computed for parameters {'Omega_m': 0.34926691201517696}
 2023-07-02 10:24:16,654 [prior] Evaluating prior at array([0.34926691])
 2023-07-02 10:24:16,654 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,654 [model] Got input parameters: {'Omega_m': 0.34926691201517696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,654 [classy] Got parameters {'Omega_m': 0.34926691201517696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,654 [classy] Computing new state
 2023-07-02 10:24:16,654 [classy] Setting parameters: {'Omega_m': 0.34926691201517696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0519341089871}
 2023-07-02 10:24:16,708 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,710 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0761455
 2023-07-02 10:24:16,710 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,710 [mcmc] New sample, #26:
   Omega_m:0.3499031
 2023-07-02 10:24:16,710 [model] Posterior to be computed for parameters {'Omega_m': 0.36342619528868847}
 2023-07-02 10:24:16,710 [prior] Evaluating prior at array([0.3634262])
 2023-07-02 10:24:16,710 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,710 [model] Got input parameters: {'Omega_m': 0.36342619528868847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,710 [classy] Got parameters {'Omega_m': 0.36342619528868847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,710 [classy] Computing new state
 2023-07-02 10:24:16,711 [classy] Setting parameters: {'Omega_m': 0.36342619528868847, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.53901511391388}
 2023-07-02 10:24:16,767 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,768 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.14121
 2023-07-02 10:24:16,768 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,769 [mcmc] New sample, #27:
   Omega_m:0.3492669
 2023-07-02 10:24:16,769 [model] Posterior to be computed for parameters {'Omega_m': 0.35214122431692957}
 2023-07-02 10:24:16,769 [prior] Evaluating prior at array([0.35214122])
 2023-07-02 10:24:16,769 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,769 [model] Got input parameters: {'Omega_m': 0.35214122431692957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,769 [classy] Got parameters {'Omega_m': 0.35214122431692957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,769 [classy] Computing new state
 2023-07-02 10:24:16,769 [classy] Setting parameters: {'Omega_m': 0.35214122431692957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.74030408688444}
 2023-07-02 10:24:16,823 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,826 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0878916
 2023-07-02 10:24:16,826 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,826 [mcmc] New sample, #28:
   Omega_m:0.3634262
 2023-07-02 10:24:16,826 [model] Posterior to be computed for parameters {'Omega_m': 0.35016960846442663}
 2023-07-02 10:24:16,826 [prior] Evaluating prior at array([0.35016961])
 2023-07-02 10:24:16,827 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,827 [model] Got input parameters: {'Omega_m': 0.35016960846442663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,827 [classy] Got parameters {'Omega_m': 0.35016960846442663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,827 [classy] Computing new state
 2023-07-02 10:24:16,827 [classy] Setting parameters: {'Omega_m': 0.35016960846442663, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,904 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.95381309063686}
 2023-07-02 10:24:16,904 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0797516
 2023-07-02 10:24:16,906 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,907 [mcmc] New sample, #29:
   Omega_m:0.3521412
 2023-07-02 10:24:16,907 [model] Posterior to be computed for parameters {'Omega_m': 0.33120937553814433}
 2023-07-02 10:24:16,907 [prior] Evaluating prior at array([0.33120938])
 2023-07-02 10:24:16,907 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,907 [model] Got input parameters: {'Omega_m': 0.33120937553814433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,907 [classy] Got parameters {'Omega_m': 0.33120937553814433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,907 [classy] Computing new state
 2023-07-02 10:24:16,907 [classy] Setting parameters: {'Omega_m': 0.33120937553814433, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:16,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0650540352797}
 2023-07-02 10:24:16,967 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:16,969 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0207419
 2023-07-02 10:24:16,969 [model] Computed derived parameters: {}
 2023-07-02 10:24:16,969 [mcmc] New sample, #30:
   Omega_m:0.3501696
 2023-07-02 10:24:16,969 [model] Posterior to be computed for parameters {'Omega_m': 0.34391059230924237}
 2023-07-02 10:24:16,969 [prior] Evaluating prior at array([0.34391059])
 2023-07-02 10:24:16,969 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:16,969 [model] Got input parameters: {'Omega_m': 0.34391059230924237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,969 [classy] Got parameters {'Omega_m': 0.34391059230924237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:16,969 [classy] Computing new state
 2023-07-02 10:24:16,969 [classy] Setting parameters: {'Omega_m': 0.34391059230924237, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6389719980835}
 2023-07-02 10:24:17,034 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,035 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563373
 2023-07-02 10:24:17,035 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,036 [mcmc] New sample, #31:
   Omega_m:0.3312094
 2023-07-02 10:24:17,036 [model] Posterior to be computed for parameters {'Omega_m': 0.3333248644244746}
 2023-07-02 10:24:17,036 [prior] Evaluating prior at array([0.33332486])
 2023-07-02 10:24:17,036 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,036 [model] Got input parameters: {'Omega_m': 0.3333248644244746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,036 [classy] Got parameters {'Omega_m': 0.3333248644244746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,036 [classy] Computing new state
 2023-07-02 10:24:17,036 [classy] Setting parameters: {'Omega_m': 0.3333248644244746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,086 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.82413574460827}
 2023-07-02 10:24:17,086 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0255157
 2023-07-02 10:24:17,090 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,090 [mcmc] New sample, #32:
   Omega_m:0.3439106
 2023-07-02 10:24:17,090 [model] Posterior to be computed for parameters {'Omega_m': 0.3536732961125939}
 2023-07-02 10:24:17,090 [prior] Evaluating prior at array([0.3536733])
 2023-07-02 10:24:17,091 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,091 [model] Got input parameters: {'Omega_m': 0.3536732961125939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,091 [classy] Got parameters {'Omega_m': 0.3536732961125939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,091 [classy] Computing new state
 2023-07-02 10:24:17,091 [classy] Setting parameters: {'Omega_m': 0.3536732961125939, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57514870695294}
 2023-07-02 10:24:17,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.094464
 2023-07-02 10:24:17,149 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,149 [mcmc] New sample, #33:
   Omega_m:0.3333249
 2023-07-02 10:24:17,149 [model] Posterior to be computed for parameters {'Omega_m': 0.37045242206221485}
 2023-07-02 10:24:17,149 [prior] Evaluating prior at array([0.37045242])
 2023-07-02 10:24:17,150 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,150 [model] Got input parameters: {'Omega_m': 0.37045242206221485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,150 [classy] Got parameters {'Omega_m': 0.37045242206221485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,150 [classy] Computing new state
 2023-07-02 10:24:17,150 [classy] Setting parameters: {'Omega_m': 0.37045242206221485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.80842460608994}
 2023-07-02 10:24:17,202 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,205 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.179922
 2023-07-02 10:24:17,205 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,205 [mcmc] New sample, #34:
   Omega_m:0.3536733
 2023-07-02 10:24:17,205 [model] Posterior to be computed for parameters {'Omega_m': 0.36808450307191337}
 2023-07-02 10:24:17,205 [prior] Evaluating prior at array([0.3680845])
 2023-07-02 10:24:17,205 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,205 [model] Got input parameters: {'Omega_m': 0.36808450307191337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,205 [classy] Got parameters {'Omega_m': 0.36808450307191337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,205 [classy] Computing new state
 2023-07-02 10:24:17,205 [classy] Setting parameters: {'Omega_m': 0.36808450307191337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.05319593829313}
 2023-07-02 10:24:17,270 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,272 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.166419
 2023-07-02 10:24:17,272 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,272 [mcmc] New sample, #35:
   Omega_m:0.3704524
 2023-07-02 10:24:17,272 [model] Posterior to be computed for parameters {'Omega_m': 0.34620313501519584}
 2023-07-02 10:24:17,272 [prior] Evaluating prior at array([0.34620314])
 2023-07-02 10:24:17,272 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,272 [model] Got input parameters: {'Omega_m': 0.34620313501519584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,272 [classy] Got parameters {'Omega_m': 0.34620313501519584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,272 [classy] Computing new state
 2023-07-02 10:24:17,272 [classy] Setting parameters: {'Omega_m': 0.34620313501519584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.38669449399833}
 2023-07-02 10:24:17,328 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0644796
 2023-07-02 10:24:17,330 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,330 [mcmc] New sample, #36:
   Omega_m:0.3680845
 2023-07-02 10:24:17,330 [model] Posterior to be computed for parameters {'Omega_m': 0.34810138032190235}
 2023-07-02 10:24:17,330 [prior] Evaluating prior at array([0.34810138])
 2023-07-02 10:24:17,330 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,331 [model] Got input parameters: {'Omega_m': 0.34810138032190235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,331 [classy] Got parameters {'Omega_m': 0.34810138032190235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,331 [classy] Computing new state
 2023-07-02 10:24:17,331 [classy] Setting parameters: {'Omega_m': 0.34810138032190235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.178967779028}
 2023-07-02 10:24:17,384 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0716027
 2023-07-02 10:24:17,386 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,386 [mcmc] New sample, #37:
   Omega_m:0.3462031
 2023-07-02 10:24:17,387 [model] Posterior to be computed for parameters {'Omega_m': 0.3445511484616483}
 2023-07-02 10:24:17,387 [prior] Evaluating prior at array([0.34455115])
 2023-07-02 10:24:17,387 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,387 [model] Got input parameters: {'Omega_m': 0.3445511484616483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,387 [classy] Got parameters {'Omega_m': 0.3445511484616483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,387 [classy] Computing new state
 2023-07-02 10:24:17,387 [classy] Setting parameters: {'Omega_m': 0.3445511484616483, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.5683228147591}
 2023-07-02 10:24:17,442 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0585616
 2023-07-02 10:24:17,445 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,445 [mcmc] New sample, #38:
   Omega_m:0.3481014
 2023-07-02 10:24:17,446 [model] Posterior to be computed for parameters {'Omega_m': 0.3468201565018789}
 2023-07-02 10:24:17,446 [prior] Evaluating prior at array([0.34682016])
 2023-07-02 10:24:17,446 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,446 [model] Got input parameters: {'Omega_m': 0.3468201565018789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,446 [classy] Got parameters {'Omega_m': 0.3468201565018789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,446 [classy] Computing new state
 2023-07-02 10:24:17,446 [classy] Setting parameters: {'Omega_m': 0.3468201565018789, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.31905974738186}
 2023-07-02 10:24:17,503 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,505 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0667573
 2023-07-02 10:24:17,505 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,505 [mcmc] New sample, #39:
   Omega_m:0.3445511
 2023-07-02 10:24:17,505 [model] Posterior to be computed for parameters {'Omega_m': 0.35364803069707795}
 2023-07-02 10:24:17,505 [prior] Evaluating prior at array([0.35364803])
 2023-07-02 10:24:17,505 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,506 [model] Got input parameters: {'Omega_m': 0.35364803069707795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,506 [classy] Got parameters {'Omega_m': 0.35364803069707795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,506 [classy] Computing new state
 2023-07-02 10:24:17,506 [classy] Setting parameters: {'Omega_m': 0.35364803069707795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57786789162083}
 2023-07-02 10:24:17,570 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,571 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0943538
 2023-07-02 10:24:17,572 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,572 [mcmc] New sample, #40:
   Omega_m:0.3468202
 2023-07-02 10:24:17,572 [mcmc] Learn + convergence test @ 40 samples accepted.
 2023-07-02 10:24:17,572 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:17,577 [mcmc]  - Acceptance rate: 0.970
 2023-07-02 10:24:17,578 [mcmc]  - Condition number = 1
 2023-07-02 10:24:17,578 [mcmc]  - Eigenvalues = array([4.12433607])
 2023-07-02 10:24:17,578 [mcmc]  - Convergence of means: R-1 = 4.124336 after 32 accepted steps
 2023-07-02 10:24:17,578 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:17,578 [mcmc] array([[0.00023226]])
 2023-07-02 10:24:17,588 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:17,589 [model] Posterior to be computed for parameters {'Omega_m': 0.3434946484190942}
 2023-07-02 10:24:17,589 [prior] Evaluating prior at array([0.34349465])
 2023-07-02 10:24:17,589 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,589 [model] Got input parameters: {'Omega_m': 0.3434946484190942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,589 [classy] Got parameters {'Omega_m': 0.3434946484190942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,589 [classy] Computing new state
 2023-07-02 10:24:17,589 [classy] Setting parameters: {'Omega_m': 0.3434946484190942, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6849122336123}
 2023-07-02 10:24:17,650 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0549144
 2023-07-02 10:24:17,652 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,653 [mcmc] New sample, #41:
   Omega_m:0.353648
 2023-07-02 10:24:17,653 [model] Posterior to be computed for parameters {'Omega_m': 0.31164082741182497}
 2023-07-02 10:24:17,653 [prior] Evaluating prior at array([0.31164083])
 2023-07-02 10:24:17,653 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,653 [model] Got input parameters: {'Omega_m': 0.31164082741182497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,653 [classy] Got parameters {'Omega_m': 0.31164082741182497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,653 [classy] Computing new state
 2023-07-02 10:24:17,653 [classy] Setting parameters: {'Omega_m': 0.31164082741182497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.36170671916042}
 2023-07-02 10:24:17,706 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,708 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000246056
 2023-07-02 10:24:17,708 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,708 [mcmc] New sample, #42:
   Omega_m:0.3434946
 2023-07-02 10:24:17,708 [model] Posterior to be computed for parameters {'Omega_m': 0.35911874589211235}
 2023-07-02 10:24:17,708 [prior] Evaluating prior at array([0.35911875])
 2023-07-02 10:24:17,709 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,709 [model] Got input parameters: {'Omega_m': 0.35911874589211235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,709 [classy] Got parameters {'Omega_m': 0.35911874589211235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,709 [classy] Computing new state
 2023-07-02 10:24:17,709 [classy] Setting parameters: {'Omega_m': 0.35911874589211235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,765 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99340735531325}
 2023-07-02 10:24:17,765 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,767 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119537
 2023-07-02 10:24:17,767 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,767 [mcmc] New sample, #43:
   Omega_m:0.3116408
 2023-07-02 10:24:17,767 [model] Posterior to be computed for parameters {'Omega_m': 0.38438805590647795}
 2023-07-02 10:24:17,767 [prior] Evaluating prior at array([0.38438806])
 2023-07-02 10:24:17,767 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,767 [model] Got input parameters: {'Omega_m': 0.38438805590647795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,767 [classy] Got parameters {'Omega_m': 0.38438805590647795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,767 [classy] Computing new state
 2023-07-02 10:24:17,767 [classy] Setting parameters: {'Omega_m': 0.38438805590647795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.39689420537823}
 2023-07-02 10:24:17,819 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.26832
 2023-07-02 10:24:17,821 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,821 [mcmc] New sample, #44:
   Omega_m:0.3591187
 2023-07-02 10:24:17,821 [model] Posterior to be computed for parameters {'Omega_m': 0.29690913953196835}
 2023-07-02 10:24:17,821 [prior] Evaluating prior at array([0.29690914])
 2023-07-02 10:24:17,821 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,821 [model] Got input parameters: {'Omega_m': 0.29690913953196835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,821 [classy] Got parameters {'Omega_m': 0.29690913953196835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,821 [classy] Computing new state
 2023-07-02 10:24:17,821 [classy] Setting parameters: {'Omega_m': 0.29690913953196835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1767559837437}
 2023-07-02 10:24:17,881 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,883 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156742
 2023-07-02 10:24:17,883 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,883 [mcmc] New sample, #45:
   Omega_m:0.3843881
 2023-07-02 10:24:17,884 [model] Posterior to be computed for parameters {'Omega_m': 0.2742060636134438}
 2023-07-02 10:24:17,884 [prior] Evaluating prior at array([0.27420606])
 2023-07-02 10:24:17,884 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,884 [model] Got input parameters: {'Omega_m': 0.2742060636134438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,884 [classy] Got parameters {'Omega_m': 0.2742060636134438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,884 [classy] Computing new state
 2023-07-02 10:24:17,884 [classy] Setting parameters: {'Omega_m': 0.2742060636134438, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:17,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13368429248118}
 2023-07-02 10:24:17,954 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:17,955 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0993925
 2023-07-02 10:24:17,955 [model] Computed derived parameters: {}
 2023-07-02 10:24:17,956 [mcmc] New sample, #46:
   Omega_m:0.2969091
 2023-07-02 10:24:17,956 [model] Posterior to be computed for parameters {'Omega_m': 0.2900212166496125}
 2023-07-02 10:24:17,956 [prior] Evaluating prior at array([0.29002122])
 2023-07-02 10:24:17,956 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:17,956 [model] Got input parameters: {'Omega_m': 0.2900212166496125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,956 [classy] Got parameters {'Omega_m': 0.2900212166496125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:17,956 [classy] Computing new state
 2023-07-02 10:24:17,956 [classy] Setting parameters: {'Omega_m': 0.2900212166496125, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,014 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05260420907697}
 2023-07-02 10:24:18,015 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0329626
 2023-07-02 10:24:18,017 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,017 [mcmc] New sample, #47:
   Omega_m:0.2742061
 2023-07-02 10:24:18,017 [model] Posterior to be computed for parameters {'Omega_m': 0.34614081995542817}
 2023-07-02 10:24:18,017 [prior] Evaluating prior at array([0.34614082])
 2023-07-02 10:24:18,017 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,017 [model] Got input parameters: {'Omega_m': 0.34614081995542817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,017 [classy] Got parameters {'Omega_m': 0.34614081995542817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,017 [classy] Computing new state
 2023-07-02 10:24:18,017 [classy] Setting parameters: {'Omega_m': 0.34614081995542817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.3935323776795}
 2023-07-02 10:24:18,077 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,080 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0642516
 2023-07-02 10:24:18,080 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,080 [mcmc] New sample, #48:
   Omega_m:0.2900212
 2023-07-02 10:24:18,080 [model] Posterior to be computed for parameters {'Omega_m': 0.4159224670621742}
 2023-07-02 10:24:18,080 [prior] Evaluating prior at array([0.41592247])
 2023-07-02 10:24:18,080 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,080 [model] Got input parameters: {'Omega_m': 0.4159224670621742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,080 [classy] Got parameters {'Omega_m': 0.4159224670621742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,080 [classy] Computing new state
 2023-07-02 10:24:18,080 [classy] Setting parameters: {'Omega_m': 0.4159224670621742, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,136 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.37354777840756}
 2023-07-02 10:24:18,136 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.518985
 2023-07-02 10:24:18,139 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,139 [mcmc] New sample, #49:
   Omega_m:0.3461408
 2023-07-02 10:24:18,139 [model] Posterior to be computed for parameters {'Omega_m': 0.4020603874371157}
 2023-07-02 10:24:18,139 [prior] Evaluating prior at array([0.40206039])
 2023-07-02 10:24:18,139 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,139 [model] Got input parameters: {'Omega_m': 0.4020603874371157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,139 [classy] Got parameters {'Omega_m': 0.4020603874371157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,139 [classy] Computing new state
 2023-07-02 10:24:18,139 [classy] Setting parameters: {'Omega_m': 0.4020603874371157, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.67469055425212}
 2023-07-02 10:24:18,186 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.400756
 2023-07-02 10:24:18,188 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,188 [mcmc] New sample, #50:
   Omega_m:0.4159225
 2023-07-02 10:24:18,188 [model] Posterior to be computed for parameters {'Omega_m': 0.34875742041024865}
 2023-07-02 10:24:18,188 [prior] Evaluating prior at array([0.34875742])
 2023-07-02 10:24:18,189 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,189 [model] Got input parameters: {'Omega_m': 0.34875742041024865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,189 [classy] Got parameters {'Omega_m': 0.34875742041024865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,189 [classy] Computing new state
 2023-07-02 10:24:18,189 [classy] Setting parameters: {'Omega_m': 0.34875742041024865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.10741653786135}
 2023-07-02 10:24:18,235 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.074144
 2023-07-02 10:24:18,237 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,237 [mcmc] New sample, #51:
   Omega_m:0.4020604
 2023-07-02 10:24:18,237 [model] Posterior to be computed for parameters {'Omega_m': 0.3790102593223994}
 2023-07-02 10:24:18,237 [prior] Evaluating prior at array([0.37901026])
 2023-07-02 10:24:18,238 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,238 [model] Got input parameters: {'Omega_m': 0.3790102593223994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,238 [classy] Got parameters {'Omega_m': 0.3790102593223994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,238 [classy] Computing new state
 2023-07-02 10:24:18,238 [classy] Setting parameters: {'Omega_m': 0.3790102593223994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.93582436747081}
 2023-07-02 10:24:18,284 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,286 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.232443
 2023-07-02 10:24:18,286 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,286 [mcmc] New sample, #52:
   Omega_m:0.3487574
 2023-07-02 10:24:18,286 [model] Posterior to be computed for parameters {'Omega_m': 0.34278955423758845}
 2023-07-02 10:24:18,286 [prior] Evaluating prior at array([0.34278955])
 2023-07-02 10:24:18,286 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,286 [model] Got input parameters: {'Omega_m': 0.34278955423758845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,286 [classy] Got parameters {'Omega_m': 0.34278955423758845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,286 [classy] Computing new state
 2023-07-02 10:24:18,286 [classy] Setting parameters: {'Omega_m': 0.34278955423758845, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.76290375337732}
 2023-07-02 10:24:18,332 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.052541
 2023-07-02 10:24:18,334 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,334 [mcmc] New sample, #53:
   Omega_m:0.3790103
 2023-07-02 10:24:18,334 [model] Posterior to be computed for parameters {'Omega_m': 0.36758932131026517}
 2023-07-02 10:24:18,334 [prior] Evaluating prior at array([0.36758932])
 2023-07-02 10:24:18,334 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,334 [model] Got input parameters: {'Omega_m': 0.36758932131026517, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,334 [classy] Got parameters {'Omega_m': 0.36758932131026517, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,334 [classy] Computing new state
 2023-07-02 10:24:18,334 [classy] Setting parameters: {'Omega_m': 0.36758932131026517, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.10456555513295}
 2023-07-02 10:24:18,380 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,382 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.163654
 2023-07-02 10:24:18,382 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,382 [mcmc] New sample, #54:
   Omega_m:0.3427896
 2023-07-02 10:24:18,382 [model] Posterior to be computed for parameters {'Omega_m': 0.3755426516112474}
 2023-07-02 10:24:18,382 [prior] Evaluating prior at array([0.37554265])
 2023-07-02 10:24:18,382 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,382 [model] Got input parameters: {'Omega_m': 0.3755426516112474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,382 [classy] Got parameters {'Omega_m': 0.3755426516112474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,382 [classy] Computing new state
 2023-07-02 10:24:18,382 [classy] Setting parameters: {'Omega_m': 0.3755426516112474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.28713173771578}
 2023-07-02 10:24:18,429 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.210474
 2023-07-02 10:24:18,431 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,431 [mcmc] New sample, #55:
   Omega_m:0.3675893
 2023-07-02 10:24:18,431 [model] Posterior to be computed for parameters {'Omega_m': 0.42315655758688553}
 2023-07-02 10:24:18,431 [prior] Evaluating prior at array([0.42315656])
 2023-07-02 10:24:18,431 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,431 [model] Got input parameters: {'Omega_m': 0.42315655758688553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,431 [classy] Got parameters {'Omega_m': 0.42315655758688553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,431 [classy] Computing new state
 2023-07-02 10:24:18,431 [classy] Setting parameters: {'Omega_m': 0.42315655758688553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.71096115013347}
 2023-07-02 10:24:18,480 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.585277
 2023-07-02 10:24:18,481 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,482 [mcmc] New sample, #56:
   Omega_m:0.3755427
 2023-07-02 10:24:18,482 [model] Posterior to be computed for parameters {'Omega_m': 0.4744200609223728}
 2023-07-02 10:24:18,482 [prior] Evaluating prior at array([0.47442006])
 2023-07-02 10:24:18,482 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,482 [model] Got input parameters: {'Omega_m': 0.4744200609223728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,482 [classy] Got parameters {'Omega_m': 0.4744200609223728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,482 [classy] Computing new state
 2023-07-02 10:24:18,482 [classy] Setting parameters: {'Omega_m': 0.4744200609223728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.30962418964663}
 2023-07-02 10:24:18,529 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,531 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.13203
 2023-07-02 10:24:18,531 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,531 [model] Posterior to be computed for parameters {'Omega_m': 0.4524392402008138}
 2023-07-02 10:24:18,531 [prior] Evaluating prior at array([0.45243924])
 2023-07-02 10:24:18,531 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,531 [model] Got input parameters: {'Omega_m': 0.4524392402008138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,531 [classy] Got parameters {'Omega_m': 0.4524392402008138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,531 [classy] Computing new state
 2023-07-02 10:24:18,531 [classy] Setting parameters: {'Omega_m': 0.4524392402008138, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.13674000765212}
 2023-07-02 10:24:18,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.882354
 2023-07-02 10:24:18,581 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,581 [mcmc] New sample, #57:
   Omega_m:0.4231566
 2023-07-02 10:24:18,581 [model] Posterior to be computed for parameters {'Omega_m': 0.4683741499572768}
 2023-07-02 10:24:18,581 [prior] Evaluating prior at array([0.46837415])
 2023-07-02 10:24:18,581 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,581 [model] Got input parameters: {'Omega_m': 0.4683741499572768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,581 [classy] Got parameters {'Omega_m': 0.4683741499572768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,581 [classy] Computing new state
 2023-07-02 10:24:18,581 [classy] Setting parameters: {'Omega_m': 0.4683741499572768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,629 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8037069741478}
 2023-07-02 10:24:18,629 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,631 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.06129
 2023-07-02 10:24:18,631 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,631 [mcmc] New sample, #58:
   Omega_m:0.4524392
 2023-07-02 10:24:18,631 [model] Posterior to be computed for parameters {'Omega_m': 0.44475293665972726}
 2023-07-02 10:24:18,631 [prior] Evaluating prior at array([0.44475294])
 2023-07-02 10:24:18,631 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,631 [model] Got input parameters: {'Omega_m': 0.44475293665972726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,631 [classy] Got parameters {'Omega_m': 0.44475293665972726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,631 [classy] Computing new state
 2023-07-02 10:24:18,631 [classy] Setting parameters: {'Omega_m': 0.44475293665972726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.79633866775825}
 2023-07-02 10:24:18,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.80019
 2023-07-02 10:24:18,681 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,681 [mcmc] New sample, #59:
   Omega_m:0.4683741
 2023-07-02 10:24:18,681 [model] Posterior to be computed for parameters {'Omega_m': 0.5118120402734262}
 2023-07-02 10:24:18,681 [prior] Evaluating prior at array([0.51181204])
 2023-07-02 10:24:18,682 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,682 [model] Got input parameters: {'Omega_m': 0.5118120402734262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,682 [classy] Got parameters {'Omega_m': 0.5118120402734262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,682 [classy] Computing new state
 2023-07-02 10:24:18,682 [classy] Setting parameters: {'Omega_m': 0.5118120402734262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,729 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.3871102237813}
 2023-07-02 10:24:18,729 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,731 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.60008
 2023-07-02 10:24:18,731 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,731 [model] Posterior to be computed for parameters {'Omega_m': 0.4238646743502005}
 2023-07-02 10:24:18,731 [prior] Evaluating prior at array([0.42386467])
 2023-07-02 10:24:18,731 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,731 [model] Got input parameters: {'Omega_m': 0.4238646743502005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,731 [classy] Got parameters {'Omega_m': 0.4238646743502005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,732 [classy] Computing new state
 2023-07-02 10:24:18,732 [classy] Setting parameters: {'Omega_m': 0.4238646743502005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.64668691149058}
 2023-07-02 10:24:18,779 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.591928
 2023-07-02 10:24:18,781 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,781 [mcmc] New sample, #60:
   Omega_m:0.4447529
 2023-07-02 10:24:18,781 [model] Posterior to be computed for parameters {'Omega_m': 0.3436429875295004}
 2023-07-02 10:24:18,781 [prior] Evaluating prior at array([0.34364299])
 2023-07-02 10:24:18,781 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,781 [model] Got input parameters: {'Omega_m': 0.3436429875295004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,781 [classy] Got parameters {'Omega_m': 0.3436429875295004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,781 [classy] Computing new state
 2023-07-02 10:24:18,782 [classy] Setting parameters: {'Omega_m': 0.3436429875295004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6685221758994}
 2023-07-02 10:24:18,829 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0554199
 2023-07-02 10:24:18,830 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,831 [mcmc] New sample, #61:
   Omega_m:0.4238647
 2023-07-02 10:24:18,831 [model] Posterior to be computed for parameters {'Omega_m': 0.3133760423111451}
 2023-07-02 10:24:18,831 [prior] Evaluating prior at array([0.31337604])
 2023-07-02 10:24:18,831 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,831 [model] Got input parameters: {'Omega_m': 0.3133760423111451, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,831 [classy] Got parameters {'Omega_m': 0.3133760423111451, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,831 [classy] Computing new state
 2023-07-02 10:24:18,831 [classy] Setting parameters: {'Omega_m': 0.3133760423111451, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.15291895172206}
 2023-07-02 10:24:18,879 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000251081
 2023-07-02 10:24:18,881 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,881 [mcmc] New sample, #62:
   Omega_m:0.343643
 2023-07-02 10:24:18,881 [model] Posterior to be computed for parameters {'Omega_m': 0.29645416731960006}
 2023-07-02 10:24:18,881 [prior] Evaluating prior at array([0.29645417])
 2023-07-02 10:24:18,881 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,881 [model] Got input parameters: {'Omega_m': 0.29645416731960006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,881 [classy] Got parameters {'Omega_m': 0.29645416731960006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,881 [classy] Computing new state
 2023-07-02 10:24:18,881 [classy] Setting parameters: {'Omega_m': 0.29645416731960006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.23406218474446}
 2023-07-02 10:24:18,928 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0166106
 2023-07-02 10:24:18,930 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,930 [mcmc] New sample, #63:
   Omega_m:0.313376
 2023-07-02 10:24:18,930 [model] Posterior to be computed for parameters {'Omega_m': 0.29042647734846566}
 2023-07-02 10:24:18,930 [prior] Evaluating prior at array([0.29042648])
 2023-07-02 10:24:18,930 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,930 [model] Got input parameters: {'Omega_m': 0.29042647734846566, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,930 [classy] Got parameters {'Omega_m': 0.29042647734846566, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,930 [classy] Computing new state
 2023-07-02 10:24:18,930 [classy] Setting parameters: {'Omega_m': 0.29042647734846566, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:18,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.00057898317326}
 2023-07-02 10:24:18,978 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:18,979 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0317581
 2023-07-02 10:24:18,979 [model] Computed derived parameters: {}
 2023-07-02 10:24:18,980 [mcmc] New sample, #64:
   Omega_m:0.2964542
 2023-07-02 10:24:18,980 [model] Posterior to be computed for parameters {'Omega_m': 0.3222866627095768}
 2023-07-02 10:24:18,980 [prior] Evaluating prior at array([0.32228666])
 2023-07-02 10:24:18,980 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:18,980 [model] Got input parameters: {'Omega_m': 0.3222866627095768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,980 [classy] Got parameters {'Omega_m': 0.3222866627095768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:18,980 [classy] Computing new state
 2023-07-02 10:24:18,980 [classy] Setting parameters: {'Omega_m': 0.3222866627095768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09677624267084}
 2023-07-02 10:24:19,034 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,036 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00595374
 2023-07-02 10:24:19,036 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,036 [mcmc] New sample, #65:
   Omega_m:0.2904265
 2023-07-02 10:24:19,036 [model] Posterior to be computed for parameters {'Omega_m': 0.22225349294669922}
 2023-07-02 10:24:19,036 [prior] Evaluating prior at array([0.22225349])
 2023-07-02 10:24:19,036 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,036 [model] Got input parameters: {'Omega_m': 0.22225349294669922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,036 [classy] Got parameters {'Omega_m': 0.22225349294669922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,036 [classy] Computing new state
 2023-07-02 10:24:19,036 [classy] Setting parameters: {'Omega_m': 0.22225349294669922, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,084 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.76268707085174}
 2023-07-02 10:24:19,084 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,086 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.639244
 2023-07-02 10:24:19,086 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,086 [model] Posterior to be computed for parameters {'Omega_m': 0.309050007723876}
 2023-07-02 10:24:19,086 [prior] Evaluating prior at array([0.30905001])
 2023-07-02 10:24:19,086 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,086 [model] Got input parameters: {'Omega_m': 0.309050007723876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,086 [classy] Got parameters {'Omega_m': 0.309050007723876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,086 [classy] Computing new state
 2023-07-02 10:24:19,086 [classy] Setting parameters: {'Omega_m': 0.309050007723876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.67536190596553}
 2023-07-02 10:24:19,133 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,135 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00093177
 2023-07-02 10:24:19,135 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,135 [mcmc] New sample, #66:
   Omega_m:0.3222867
 2023-07-02 10:24:19,135 [model] Posterior to be computed for parameters {'Omega_m': 0.30009599369395673}
 2023-07-02 10:24:19,135 [prior] Evaluating prior at array([0.30009599])
 2023-07-02 10:24:19,135 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,135 [model] Got input parameters: {'Omega_m': 0.30009599369395673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,135 [classy] Got parameters {'Omega_m': 0.30009599369395673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,135 [classy] Computing new state
 2023-07-02 10:24:19,135 [classy] Setting parameters: {'Omega_m': 0.30009599369395673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,183 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.77748660867425}
 2023-07-02 10:24:19,183 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,184 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0099105
 2023-07-02 10:24:19,185 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,185 [mcmc] New sample, #67:
   Omega_m:0.30905
 2023-07-02 10:24:19,185 [model] Posterior to be computed for parameters {'Omega_m': 0.3964570899636888}
 2023-07-02 10:24:19,185 [prior] Evaluating prior at array([0.39645709])
 2023-07-02 10:24:19,185 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,185 [model] Got input parameters: {'Omega_m': 0.3964570899636888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,185 [classy] Got parameters {'Omega_m': 0.3964570899636888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,185 [classy] Computing new state
 2023-07-02 10:24:19,185 [classy] Setting parameters: {'Omega_m': 0.3964570899636888, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,232 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.21283551583468}
 2023-07-02 10:24:19,232 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,234 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.356447
 2023-07-02 10:24:19,234 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,234 [mcmc] New sample, #68:
   Omega_m:0.300096
 2023-07-02 10:24:19,234 [model] Posterior to be computed for parameters {'Omega_m': 0.3665539146960622}
 2023-07-02 10:24:19,234 [prior] Evaluating prior at array([0.36655391])
 2023-07-02 10:24:19,235 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,235 [model] Got input parameters: {'Omega_m': 0.3665539146960622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,235 [classy] Got parameters {'Omega_m': 0.3665539146960622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,235 [classy] Computing new state
 2023-07-02 10:24:19,235 [classy] Setting parameters: {'Omega_m': 0.3665539146960622, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.21219013189292}
 2023-07-02 10:24:19,283 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,284 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.157937
 2023-07-02 10:24:19,284 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,285 [mcmc] New sample, #69:
   Omega_m:0.3964571
 2023-07-02 10:24:19,285 [model] Posterior to be computed for parameters {'Omega_m': 0.367761724113744}
 2023-07-02 10:24:19,285 [prior] Evaluating prior at array([0.36776172])
 2023-07-02 10:24:19,285 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,285 [model] Got input parameters: {'Omega_m': 0.367761724113744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,285 [classy] Got parameters {'Omega_m': 0.367761724113744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,285 [classy] Computing new state
 2023-07-02 10:24:19,285 [classy] Setting parameters: {'Omega_m': 0.367761724113744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.08667295805708}
 2023-07-02 10:24:19,332 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.164615
 2023-07-02 10:24:19,334 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,334 [mcmc] New sample, #70:
   Omega_m:0.3665539
 2023-07-02 10:24:19,334 [model] Posterior to be computed for parameters {'Omega_m': 0.3311413174185863}
 2023-07-02 10:24:19,334 [prior] Evaluating prior at array([0.33114132])
 2023-07-02 10:24:19,334 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,334 [model] Got input parameters: {'Omega_m': 0.3311413174185863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,334 [classy] Got parameters {'Omega_m': 0.3311413174185863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,334 [classy] Computing new state
 2023-07-02 10:24:19,334 [classy] Setting parameters: {'Omega_m': 0.3311413174185863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,382 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.07282729431478}
 2023-07-02 10:24:19,382 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,384 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0205962
 2023-07-02 10:24:19,384 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,384 [mcmc] New sample, #71:
   Omega_m:0.3677617
 2023-07-02 10:24:19,384 [model] Posterior to be computed for parameters {'Omega_m': 0.3653226599934083}
 2023-07-02 10:24:19,384 [prior] Evaluating prior at array([0.36532266])
 2023-07-02 10:24:19,384 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,384 [model] Got input parameters: {'Omega_m': 0.3653226599934083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,384 [classy] Got parameters {'Omega_m': 0.3653226599934083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,384 [classy] Computing new state
 2023-07-02 10:24:19,384 [classy] Setting parameters: {'Omega_m': 0.3653226599934083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.34053925364174}
 2023-07-02 10:24:19,432 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,433 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.151254
 2023-07-02 10:24:19,433 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,434 [mcmc] New sample, #72:
   Omega_m:0.3311413
 2023-07-02 10:24:19,434 [model] Posterior to be computed for parameters {'Omega_m': 0.36248148250931017}
 2023-07-02 10:24:19,434 [prior] Evaluating prior at array([0.36248148])
 2023-07-02 10:24:19,434 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,434 [model] Got input parameters: {'Omega_m': 0.36248148250931017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,434 [classy] Got parameters {'Omega_m': 0.36248148250931017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,434 [classy] Computing new state
 2023-07-02 10:24:19,434 [classy] Setting parameters: {'Omega_m': 0.36248148250931017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.63824196425236}
 2023-07-02 10:24:19,481 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.136321
 2023-07-02 10:24:19,483 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,483 [mcmc] New sample, #73:
   Omega_m:0.3653227
 2023-07-02 10:24:19,483 [model] Posterior to be computed for parameters {'Omega_m': 0.3608741839193422}
 2023-07-02 10:24:19,483 [prior] Evaluating prior at array([0.36087418])
 2023-07-02 10:24:19,483 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,483 [model] Got input parameters: {'Omega_m': 0.3608741839193422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,483 [classy] Got parameters {'Omega_m': 0.3608741839193422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,483 [classy] Computing new state
 2023-07-02 10:24:19,483 [classy] Setting parameters: {'Omega_m': 0.3608741839193422, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,530 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.80761446141827}
 2023-07-02 10:24:19,530 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,531 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.128177
 2023-07-02 10:24:19,531 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,532 [mcmc] New sample, #74:
   Omega_m:0.3624815
 2023-07-02 10:24:19,532 [model] Posterior to be computed for parameters {'Omega_m': 0.37099817135952673}
 2023-07-02 10:24:19,532 [prior] Evaluating prior at array([0.37099817])
 2023-07-02 10:24:19,532 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,532 [model] Got input parameters: {'Omega_m': 0.37099817135952673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,532 [classy] Got parameters {'Omega_m': 0.37099817135952673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,532 [classy] Computing new state
 2023-07-02 10:24:19,532 [classy] Setting parameters: {'Omega_m': 0.37099817135952673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.7522166942065}
 2023-07-02 10:24:19,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.183098
 2023-07-02 10:24:19,580 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,581 [mcmc] New sample, #75:
   Omega_m:0.3608742
 2023-07-02 10:24:19,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3471817922820753}
 2023-07-02 10:24:19,581 [prior] Evaluating prior at array([0.34718179])
 2023-07-02 10:24:19,581 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,581 [model] Got input parameters: {'Omega_m': 0.3471817922820753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,581 [classy] Got parameters {'Omega_m': 0.3471817922820753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,581 [classy] Computing new state
 2023-07-02 10:24:19,581 [classy] Setting parameters: {'Omega_m': 0.3471817922820753, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.27946936789536}
 2023-07-02 10:24:19,629 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0681091
 2023-07-02 10:24:19,630 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,630 [mcmc] New sample, #76:
   Omega_m:0.3709982
 2023-07-02 10:24:19,630 [model] Posterior to be computed for parameters {'Omega_m': 0.3564838863913796}
 2023-07-02 10:24:19,630 [prior] Evaluating prior at array([0.35648389])
 2023-07-02 10:24:19,631 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,631 [model] Got input parameters: {'Omega_m': 0.3564838863913796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,631 [classy] Got parameters {'Omega_m': 0.3564838863913796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,631 [classy] Computing new state
 2023-07-02 10:24:19,631 [classy] Setting parameters: {'Omega_m': 0.3564838863913796, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.27387042810247}
 2023-07-02 10:24:19,678 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,680 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.107075
 2023-07-02 10:24:19,680 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,680 [mcmc] New sample, #77:
   Omega_m:0.3471818
 2023-07-02 10:24:19,680 [model] Posterior to be computed for parameters {'Omega_m': 0.33435946501735225}
 2023-07-02 10:24:19,680 [prior] Evaluating prior at array([0.33435947])
 2023-07-02 10:24:19,680 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,680 [model] Got input parameters: {'Omega_m': 0.33435946501735225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,680 [classy] Got parameters {'Omega_m': 0.33435946501735225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,680 [classy] Computing new state
 2023-07-02 10:24:19,680 [classy] Setting parameters: {'Omega_m': 0.33435946501735225, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.70681382533994}
 2023-07-02 10:24:19,726 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0280223
 2023-07-02 10:24:19,728 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,728 [mcmc] New sample, #78:
   Omega_m:0.3564839
 2023-07-02 10:24:19,729 [model] Posterior to be computed for parameters {'Omega_m': 0.2582444406099313}
 2023-07-02 10:24:19,729 [prior] Evaluating prior at array([0.25824444])
 2023-07-02 10:24:19,729 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,729 [model] Got input parameters: {'Omega_m': 0.2582444406099313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,729 [classy] Got parameters {'Omega_m': 0.2582444406099313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,729 [classy] Computing new state
 2023-07-02 10:24:19,729 [classy] Setting parameters: {'Omega_m': 0.2582444406099313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.34032164324853}
 2023-07-02 10:24:19,774 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,777 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.208246
 2023-07-02 10:24:19,777 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,777 [mcmc] New sample, #79:
   Omega_m:0.3343595
 2023-07-02 10:24:19,777 [model] Posterior to be computed for parameters {'Omega_m': 0.26137194392774193}
 2023-07-02 10:24:19,777 [prior] Evaluating prior at array([0.26137194])
 2023-07-02 10:24:19,778 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,778 [model] Got input parameters: {'Omega_m': 0.26137194392774193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,778 [classy] Got parameters {'Omega_m': 0.26137194392774193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,778 [classy] Computing new state
 2023-07-02 10:24:19,778 [classy] Setting parameters: {'Omega_m': 0.26137194392774193, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.89909479233503}
 2023-07-02 10:24:19,824 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.183352
 2023-07-02 10:24:19,827 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,827 [mcmc] New sample, #80:
   Omega_m:0.2582444
 2023-07-02 10:24:19,827 [mcmc] Learn + convergence test @ 80 samples accepted.
 2023-07-02 10:24:19,827 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:19,832 [mcmc]  - Acceptance rate: 0.955
 2023-07-02 10:24:19,832 [mcmc]  - Condition number = 1
 2023-07-02 10:24:19,832 [mcmc]  - Eigenvalues = array([0.94182869])
 2023-07-02 10:24:19,832 [mcmc]  - Convergence of means: R-1 = 0.941829 after 64 accepted steps
 2023-07-02 10:24:19,832 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:19,833 [mcmc] array([[0.00120268]])
 2023-07-02 10:24:19,842 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:19,843 [model] Posterior to be computed for parameters {'Omega_m': 0.32542810755875745}
 2023-07-02 10:24:19,843 [prior] Evaluating prior at array([0.32542811])
 2023-07-02 10:24:19,843 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,843 [model] Got input parameters: {'Omega_m': 0.32542810755875745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,843 [classy] Got parameters {'Omega_m': 0.32542810755875745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,843 [classy] Computing new state
 2023-07-02 10:24:19,843 [classy] Setting parameters: {'Omega_m': 0.32542810755875745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7306416384166}
 2023-07-02 10:24:19,890 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0101545
 2023-07-02 10:24:19,892 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,892 [mcmc] New sample, #81:
   Omega_m:0.2613719
 2023-07-02 10:24:19,892 [model] Posterior to be computed for parameters {'Omega_m': 0.3457700613203705}
 2023-07-02 10:24:19,892 [prior] Evaluating prior at array([0.34577006])
 2023-07-02 10:24:19,892 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,892 [model] Got input parameters: {'Omega_m': 0.3457700613203705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,892 [classy] Got parameters {'Omega_m': 0.3457700613203705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,892 [classy] Computing new state
 2023-07-02 10:24:19,892 [classy] Setting parameters: {'Omega_m': 0.3457700613203705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.43423342247658}
 2023-07-02 10:24:19,939 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0629027
 2023-07-02 10:24:19,941 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,941 [mcmc] New sample, #82:
   Omega_m:0.3254281
 2023-07-02 10:24:19,941 [model] Posterior to be computed for parameters {'Omega_m': 0.33183721574281244}
 2023-07-02 10:24:19,941 [prior] Evaluating prior at array([0.33183722])
 2023-07-02 10:24:19,941 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,941 [model] Got input parameters: {'Omega_m': 0.33183721574281244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,942 [classy] Got parameters {'Omega_m': 0.33183721574281244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,942 [classy] Computing new state
 2023-07-02 10:24:19,942 [classy] Setting parameters: {'Omega_m': 0.33183721574281244, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:19,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99340982655661}
 2023-07-02 10:24:19,988 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:19,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221091
 2023-07-02 10:24:19,990 [model] Computed derived parameters: {}
 2023-07-02 10:24:19,990 [mcmc] New sample, #83:
   Omega_m:0.3457701
 2023-07-02 10:24:19,990 [model] Posterior to be computed for parameters {'Omega_m': 0.3324193586031656}
 2023-07-02 10:24:19,990 [prior] Evaluating prior at array([0.33241936])
 2023-07-02 10:24:19,990 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:19,990 [model] Got input parameters: {'Omega_m': 0.3324193586031656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,990 [classy] Got parameters {'Omega_m': 0.3324193586031656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:19,990 [classy] Computing new state
 2023-07-02 10:24:19,990 [classy] Setting parameters: {'Omega_m': 0.3324193586031656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.92708801426514}
 2023-07-02 10:24:20,038 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0234143
 2023-07-02 10:24:20,040 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,040 [mcmc] New sample, #84:
   Omega_m:0.3318372
 2023-07-02 10:24:20,040 [model] Posterior to be computed for parameters {'Omega_m': 0.31960736699763315}
 2023-07-02 10:24:20,040 [prior] Evaluating prior at array([0.31960737])
 2023-07-02 10:24:20,040 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,040 [model] Got input parameters: {'Omega_m': 0.31960736699763315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,041 [classy] Got parameters {'Omega_m': 0.31960736699763315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,041 [classy] Computing new state
 2023-07-02 10:24:20,041 [classy] Setting parameters: {'Omega_m': 0.31960736699763315, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.41157702715816}
 2023-07-02 10:24:20,088 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00325939
 2023-07-02 10:24:20,090 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,090 [mcmc] New sample, #85:
   Omega_m:0.3324194
 2023-07-02 10:24:20,090 [model] Posterior to be computed for parameters {'Omega_m': 0.29390568502253234}
 2023-07-02 10:24:20,090 [prior] Evaluating prior at array([0.29390569])
 2023-07-02 10:24:20,090 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,090 [model] Got input parameters: {'Omega_m': 0.29390568502253234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,090 [classy] Got parameters {'Omega_m': 0.29390568502253234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,090 [classy] Computing new state
 2023-07-02 10:24:20,091 [classy] Setting parameters: {'Omega_m': 0.29390568502253234, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55647482745402}
 2023-07-02 10:24:20,137 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0223877
 2023-07-02 10:24:20,139 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,139 [mcmc] New sample, #86:
   Omega_m:0.3196074
 2023-07-02 10:24:20,139 [model] Posterior to be computed for parameters {'Omega_m': 0.19149637836383487}
 2023-07-02 10:24:20,140 [prior] Evaluating prior at array([0.19149638])
 2023-07-02 10:24:20,140 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,140 [model] Got input parameters: {'Omega_m': 0.19149637836383487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,140 [classy] Got parameters {'Omega_m': 0.19149637836383487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,140 [classy] Computing new state
 2023-07-02 10:24:20,140 [classy] Setting parameters: {'Omega_m': 0.19149637836383487, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.97863300954097}
 2023-07-02 10:24:20,186 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,189 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.26568
 2023-07-02 10:24:20,189 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,189 [model] Posterior to be computed for parameters {'Omega_m': 0.37944327789657617}
 2023-07-02 10:24:20,189 [prior] Evaluating prior at array([0.37944328])
 2023-07-02 10:24:20,189 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,189 [model] Got input parameters: {'Omega_m': 0.37944327789657617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,189 [classy] Got parameters {'Omega_m': 0.37944327789657617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,189 [classy] Computing new state
 2023-07-02 10:24:20,189 [classy] Setting parameters: {'Omega_m': 0.37944327789657617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.8921658789699}
 2023-07-02 10:24:20,236 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.235251
 2023-07-02 10:24:20,238 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,238 [mcmc] New sample, #87:
   Omega_m:0.2939057
 2023-07-02 10:24:20,239 [model] Posterior to be computed for parameters {'Omega_m': 0.5860772124878907}
 2023-07-02 10:24:20,239 [prior] Evaluating prior at array([0.58607721])
 2023-07-02 10:24:20,239 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,239 [model] Got input parameters: {'Omega_m': 0.5860772124878907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,239 [classy] Got parameters {'Omega_m': 0.5860772124878907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,239 [classy] Computing new state
 2023-07-02 10:24:20,239 [classy] Setting parameters: {'Omega_m': 0.5860772124878907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.17651197891021}
 2023-07-02 10:24:20,285 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.65186
 2023-07-02 10:24:20,287 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,287 [model] Posterior to be computed for parameters {'Omega_m': 0.34098361597985255}
 2023-07-02 10:24:20,287 [prior] Evaluating prior at array([0.34098362])
 2023-07-02 10:24:20,287 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,287 [model] Got input parameters: {'Omega_m': 0.34098361597985255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,287 [classy] Got parameters {'Omega_m': 0.34098361597985255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,287 [classy] Computing new state
 2023-07-02 10:24:20,288 [classy] Setting parameters: {'Omega_m': 0.34098361597985255, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.96332848611638}
 2023-07-02 10:24:20,335 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,336 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0466857
 2023-07-02 10:24:20,336 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,336 [mcmc] New sample, #88:
   Omega_m:0.3794433
 2023-07-02 10:24:20,337 [model] Posterior to be computed for parameters {'Omega_m': 0.3536749304546155}
 2023-07-02 10:24:20,337 [prior] Evaluating prior at array([0.35367493])
 2023-07-02 10:24:20,337 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,337 [model] Got input parameters: {'Omega_m': 0.3536749304546155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,337 [classy] Got parameters {'Omega_m': 0.3536749304546155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,337 [classy] Computing new state
 2023-07-02 10:24:20,337 [classy] Setting parameters: {'Omega_m': 0.3536749304546155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.5749708267815}
 2023-07-02 10:24:20,383 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,385 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0944713
 2023-07-02 10:24:20,385 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,385 [mcmc] New sample, #89:
   Omega_m:0.3409836
 2023-07-02 10:24:20,385 [model] Posterior to be computed for parameters {'Omega_m': 0.3551905003976208}
 2023-07-02 10:24:20,385 [prior] Evaluating prior at array([0.3551905])
 2023-07-02 10:24:20,385 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,385 [model] Got input parameters: {'Omega_m': 0.3551905003976208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,385 [classy] Got parameters {'Omega_m': 0.3551905003976208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,385 [classy] Computing new state
 2023-07-02 10:24:20,385 [classy] Setting parameters: {'Omega_m': 0.3551905003976208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.41224135889237}
 2023-07-02 10:24:20,432 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.101183
 2023-07-02 10:24:20,434 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,434 [mcmc] New sample, #90:
   Omega_m:0.3536749
 2023-07-02 10:24:20,434 [model] Posterior to be computed for parameters {'Omega_m': 0.38523073417392883}
 2023-07-02 10:24:20,434 [prior] Evaluating prior at array([0.38523073])
 2023-07-02 10:24:20,434 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,434 [model] Got input parameters: {'Omega_m': 0.38523073417392883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,434 [classy] Got parameters {'Omega_m': 0.38523073417392883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,434 [classy] Computing new state
 2023-07-02 10:24:20,434 [classy] Setting parameters: {'Omega_m': 0.38523073417392883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.31308953242507}
 2023-07-02 10:24:20,481 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.274136
 2023-07-02 10:24:20,483 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,483 [mcmc] New sample, #91:
   Omega_m:0.3551905
 2023-07-02 10:24:20,483 [model] Posterior to be computed for parameters {'Omega_m': 0.37130300838940666}
 2023-07-02 10:24:20,483 [prior] Evaluating prior at array([0.37130301])
 2023-07-02 10:24:20,483 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,483 [model] Got input parameters: {'Omega_m': 0.37130300838940666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,483 [classy] Got parameters {'Omega_m': 0.37130300838940666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,483 [classy] Computing new state
 2023-07-02 10:24:20,483 [classy] Setting parameters: {'Omega_m': 0.37130300838940666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,530 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.72085199319577}
 2023-07-02 10:24:20,530 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,532 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.184883
 2023-07-02 10:24:20,532 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,532 [mcmc] New sample, #92:
   Omega_m:0.3852307
 2023-07-02 10:24:20,532 [model] Posterior to be computed for parameters {'Omega_m': 0.1631398791071817}
 2023-07-02 10:24:20,532 [prior] Evaluating prior at array([0.16313988])
 2023-07-02 10:24:20,532 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,532 [model] Got input parameters: {'Omega_m': 0.1631398791071817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,532 [classy] Got parameters {'Omega_m': 0.1631398791071817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,532 [classy] Computing new state
 2023-07-02 10:24:20,532 [classy] Setting parameters: {'Omega_m': 0.1631398791071817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,578 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.37469504569316}
 2023-07-02 10:24:20,578 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.12325
 2023-07-02 10:24:20,580 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3267299874396019}
 2023-07-02 10:24:20,581 [prior] Evaluating prior at array([0.32672999])
 2023-07-02 10:24:20,581 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,581 [model] Got input parameters: {'Omega_m': 0.3267299874396019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,581 [classy] Got parameters {'Omega_m': 0.3267299874396019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,581 [classy] Computing new state
 2023-07-02 10:24:20,581 [classy] Setting parameters: {'Omega_m': 0.3267299874396019, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,627 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57983036946771}
 2023-07-02 10:24:20,627 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,629 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0122194
 2023-07-02 10:24:20,629 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,629 [mcmc] New sample, #93:
   Omega_m:0.371303
 2023-07-02 10:24:20,629 [model] Posterior to be computed for parameters {'Omega_m': 0.4607339937525602}
 2023-07-02 10:24:20,630 [prior] Evaluating prior at array([0.46073399])
 2023-07-02 10:24:20,630 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,630 [model] Got input parameters: {'Omega_m': 0.4607339937525602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,630 [classy] Got parameters {'Omega_m': 0.4607339937525602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,630 [classy] Computing new state
 2023-07-02 10:24:20,630 [classy] Setting parameters: {'Omega_m': 0.4607339937525602, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.43715218301216}
 2023-07-02 10:24:20,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,682 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.974105
 2023-07-02 10:24:20,682 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,682 [model] Posterior to be computed for parameters {'Omega_m': 0.377051598659586}
 2023-07-02 10:24:20,682 [prior] Evaluating prior at array([0.3770516])
 2023-07-02 10:24:20,682 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,682 [model] Got input parameters: {'Omega_m': 0.377051598659586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,682 [classy] Got parameters {'Omega_m': 0.377051598659586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,682 [classy] Computing new state
 2023-07-02 10:24:20,682 [classy] Setting parameters: {'Omega_m': 0.377051598659586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,730 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.13388886584093}
 2023-07-02 10:24:20,731 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,732 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.219919
 2023-07-02 10:24:20,732 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,733 [mcmc] New sample, #94:
   Omega_m:0.32673
 2023-07-02 10:24:20,733 [model] Posterior to be computed for parameters {'Omega_m': 0.35422236570857696}
 2023-07-02 10:24:20,733 [prior] Evaluating prior at array([0.35422237])
 2023-07-02 10:24:20,733 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,733 [model] Got input parameters: {'Omega_m': 0.35422236570857696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,733 [classy] Got parameters {'Omega_m': 0.35422236570857696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,733 [classy] Computing new state
 2023-07-02 10:24:20,733 [classy] Setting parameters: {'Omega_m': 0.35422236570857696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.51611974504237}
 2023-07-02 10:24:20,778 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0968715
 2023-07-02 10:24:20,781 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,781 [mcmc] New sample, #95:
   Omega_m:0.3770516
 2023-07-02 10:24:20,781 [model] Posterior to be computed for parameters {'Omega_m': 0.6461783449436684}
 2023-07-02 10:24:20,781 [prior] Evaluating prior at array([0.64617834])
 2023-07-02 10:24:20,781 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,781 [model] Got input parameters: {'Omega_m': 0.6461783449436684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,781 [classy] Got parameters {'Omega_m': 0.6461783449436684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,781 [classy] Computing new state
 2023-07-02 10:24:20,781 [classy] Setting parameters: {'Omega_m': 0.6461783449436684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,826 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.43955990522315}
 2023-07-02 10:24:20,826 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,828 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.58528
 2023-07-02 10:24:20,828 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,828 [mcmc] New sample, #96:
   Omega_m:0.3542224
 2023-07-02 10:24:20,828 [model] Posterior to be computed for parameters {'Omega_m': 0.7278821175440413}
 2023-07-02 10:24:20,828 [prior] Evaluating prior at array([0.72788212])
 2023-07-02 10:24:20,828 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,829 [model] Got input parameters: {'Omega_m': 0.7278821175440413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,829 [classy] Got parameters {'Omega_m': 0.7278821175440413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,829 [classy] Computing new state
 2023-07-02 10:24:20,829 [classy] Setting parameters: {'Omega_m': 0.7278821175440413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,873 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.91387472642691}
 2023-07-02 10:24:20,873 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,875 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.92667
 2023-07-02 10:24:20,875 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,875 [mcmc] New sample, #97:
   Omega_m:0.6461783
 2023-07-02 10:24:20,875 [model] Posterior to be computed for parameters {'Omega_m': 0.7227308727852103}
 2023-07-02 10:24:20,875 [prior] Evaluating prior at array([0.72273087])
 2023-07-02 10:24:20,875 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,875 [model] Got input parameters: {'Omega_m': 0.7227308727852103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,876 [classy] Got parameters {'Omega_m': 0.7227308727852103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,876 [classy] Computing new state
 2023-07-02 10:24:20,876 [classy] Setting parameters: {'Omega_m': 0.7227308727852103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,921 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.182645547493}
 2023-07-02 10:24:20,921 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,923 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.84033
 2023-07-02 10:24:20,923 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,923 [mcmc] New sample, #98:
   Omega_m:0.7278821
 2023-07-02 10:24:20,923 [model] Posterior to be computed for parameters {'Omega_m': 0.7644760241456}
 2023-07-02 10:24:20,923 [prior] Evaluating prior at array([0.76447602])
 2023-07-02 10:24:20,923 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,923 [model] Got input parameters: {'Omega_m': 0.7644760241456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,923 [classy] Got parameters {'Omega_m': 0.7644760241456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,923 [classy] Computing new state
 2023-07-02 10:24:20,923 [classy] Setting parameters: {'Omega_m': 0.7644760241456, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:20,969 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.06243018594267}
 2023-07-02 10:24:20,969 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:20,970 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.54479
 2023-07-02 10:24:20,971 [model] Computed derived parameters: {}
 2023-07-02 10:24:20,971 [model] Posterior to be computed for parameters {'Omega_m': 0.8284890662465013}
 2023-07-02 10:24:20,971 [prior] Evaluating prior at array([0.82848907])
 2023-07-02 10:24:20,971 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:20,971 [model] Got input parameters: {'Omega_m': 0.8284890662465013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,971 [classy] Got parameters {'Omega_m': 0.8284890662465013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:20,971 [classy] Computing new state
 2023-07-02 10:24:20,971 [classy] Setting parameters: {'Omega_m': 0.8284890662465013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.04678782018938}
 2023-07-02 10:24:21,017 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,019 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.64127
 2023-07-02 10:24:21,019 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,019 [model] Posterior to be computed for parameters {'Omega_m': 0.783053075147835}
 2023-07-02 10:24:21,019 [prior] Evaluating prior at array([0.78305308])
 2023-07-02 10:24:21,019 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,019 [model] Got input parameters: {'Omega_m': 0.783053075147835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,019 [classy] Got parameters {'Omega_m': 0.783053075147835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,019 [classy] Computing new state
 2023-07-02 10:24:21,020 [classy] Setting parameters: {'Omega_m': 0.783053075147835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.15936018924137}
 2023-07-02 10:24:21,065 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,067 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.86135
 2023-07-02 10:24:21,067 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,067 [mcmc] New sample, #99:
   Omega_m:0.7227309
 2023-07-02 10:24:21,067 [model] Posterior to be computed for parameters {'Omega_m': 1.1694945245795805}
 2023-07-02 10:24:21,067 [prior] Evaluating prior at array([1.16949452])
 2023-07-02 10:24:21,067 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:21,067 [model] Posterior to be computed for parameters {'Omega_m': 0.7729589770581474}
 2023-07-02 10:24:21,068 [prior] Evaluating prior at array([0.77295898])
 2023-07-02 10:24:21,068 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,068 [model] Got input parameters: {'Omega_m': 0.7729589770581474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,068 [classy] Got parameters {'Omega_m': 0.7729589770581474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,068 [classy] Computing new state
 2023-07-02 10:24:21,068 [classy] Setting parameters: {'Omega_m': 0.7729589770581474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.64708186328386}
 2023-07-02 10:24:21,114 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,115 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.68915
 2023-07-02 10:24:21,115 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,115 [mcmc] New sample, #100:
   Omega_m:0.7830531
 2023-07-02 10:24:21,115 [model] Posterior to be computed for parameters {'Omega_m': 0.5502608978661879}
 2023-07-02 10:24:21,115 [prior] Evaluating prior at array([0.5502609])
 2023-07-02 10:24:21,116 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,116 [model] Got input parameters: {'Omega_m': 0.5502608978661879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,116 [classy] Got parameters {'Omega_m': 0.5502608978661879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,116 [classy] Computing new state
 2023-07-02 10:24:21,116 [classy] Setting parameters: {'Omega_m': 0.5502608978661879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.59910230588486}
 2023-07-02 10:24:21,163 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.1275
 2023-07-02 10:24:21,165 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,165 [mcmc] New sample, #101:
   Omega_m:0.772959
 2023-07-02 10:24:21,165 [model] Posterior to be computed for parameters {'Omega_m': 0.550306699150419}
 2023-07-02 10:24:21,165 [prior] Evaluating prior at array([0.5503067])
 2023-07-02 10:24:21,166 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,166 [model] Got input parameters: {'Omega_m': 0.550306699150419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,166 [classy] Got parameters {'Omega_m': 0.550306699150419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,166 [classy] Computing new state
 2023-07-02 10:24:21,166 [classy] Setting parameters: {'Omega_m': 0.550306699150419, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,212 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.59590136295017}
 2023-07-02 10:24:21,212 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,214 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.12815
 2023-07-02 10:24:21,214 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,214 [mcmc] New sample, #102:
   Omega_m:0.5502609
 2023-07-02 10:24:21,214 [model] Posterior to be computed for parameters {'Omega_m': 0.4009189150853601}
 2023-07-02 10:24:21,214 [prior] Evaluating prior at array([0.40091892])
 2023-07-02 10:24:21,214 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,214 [model] Got input parameters: {'Omega_m': 0.4009189150853601, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,214 [classy] Got parameters {'Omega_m': 0.4009189150853601, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,214 [classy] Computing new state
 2023-07-02 10:24:21,214 [classy] Setting parameters: {'Omega_m': 0.4009189150853601, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,261 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.78373744380585}
 2023-07-02 10:24:21,261 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,262 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.391561
 2023-07-02 10:24:21,262 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,262 [mcmc] New sample, #103:
   Omega_m:0.5503067
 2023-07-02 10:24:21,263 [model] Posterior to be computed for parameters {'Omega_m': 0.4814450421490043}
 2023-07-02 10:24:21,263 [prior] Evaluating prior at array([0.48144504])
 2023-07-02 10:24:21,263 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,263 [model] Got input parameters: {'Omega_m': 0.4814450421490043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,263 [classy] Got parameters {'Omega_m': 0.4814450421490043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,263 [classy] Computing new state
 2023-07-02 10:24:21,263 [classy] Setting parameters: {'Omega_m': 0.4814450421490043, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.74337788323268}
 2023-07-02 10:24:21,310 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,312 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.21606
 2023-07-02 10:24:21,312 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,312 [model] Posterior to be computed for parameters {'Omega_m': 0.3238356064504956}
 2023-07-02 10:24:21,312 [prior] Evaluating prior at array([0.32383561])
 2023-07-02 10:24:21,312 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,312 [model] Got input parameters: {'Omega_m': 0.3238356064504956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,312 [classy] Got parameters {'Omega_m': 0.3238356064504956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,312 [classy] Computing new state
 2023-07-02 10:24:21,312 [classy] Setting parameters: {'Omega_m': 0.3238356064504956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.91585043328428}
 2023-07-02 10:24:21,360 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00788591
 2023-07-02 10:24:21,362 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,362 [mcmc] New sample, #104:
   Omega_m:0.4009189
 2023-07-02 10:24:21,362 [model] Posterior to be computed for parameters {'Omega_m': 0.2827052887679717}
 2023-07-02 10:24:21,362 [prior] Evaluating prior at array([0.28270529])
 2023-07-02 10:24:21,362 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,362 [model] Got input parameters: {'Omega_m': 0.2827052887679717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,362 [classy] Got parameters {'Omega_m': 0.2827052887679717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,362 [classy] Computing new state
 2023-07-02 10:24:21,362 [classy] Setting parameters: {'Omega_m': 0.2827052887679717, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,410 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.002847417495}
 2023-07-02 10:24:21,410 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,412 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0588913
 2023-07-02 10:24:21,412 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,412 [mcmc] New sample, #105:
   Omega_m:0.3238356
 2023-07-02 10:24:21,412 [model] Posterior to be computed for parameters {'Omega_m': 0.43645950344663065}
 2023-07-02 10:24:21,412 [prior] Evaluating prior at array([0.4364595])
 2023-07-02 10:24:21,412 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,412 [model] Got input parameters: {'Omega_m': 0.43645950344663065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,412 [classy] Got parameters {'Omega_m': 0.43645950344663065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,412 [classy] Computing new state
 2023-07-02 10:24:21,412 [classy] Setting parameters: {'Omega_m': 0.43645950344663065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.5206726093113}
 2023-07-02 10:24:21,460 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.714777
 2023-07-02 10:24:21,462 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,462 [model] Posterior to be computed for parameters {'Omega_m': 0.26269599480400374}
 2023-07-02 10:24:21,462 [prior] Evaluating prior at array([0.26269599])
 2023-07-02 10:24:21,462 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,462 [model] Got input parameters: {'Omega_m': 0.26269599480400374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,462 [classy] Got parameters {'Omega_m': 0.26269599480400374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,462 [classy] Computing new state
 2023-07-02 10:24:21,462 [classy] Setting parameters: {'Omega_m': 0.26269599480400374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.71363448145135}
 2023-07-02 10:24:21,510 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.173353
 2023-07-02 10:24:21,512 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,512 [mcmc] New sample, #106:
   Omega_m:0.2827053
 2023-07-02 10:24:21,512 [model] Posterior to be computed for parameters {'Omega_m': 0.23330859700781822}
 2023-07-02 10:24:21,512 [prior] Evaluating prior at array([0.2333086])
 2023-07-02 10:24:21,512 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,512 [model] Got input parameters: {'Omega_m': 0.23330859700781822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,512 [classy] Got parameters {'Omega_m': 0.23330859700781822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,512 [classy] Computing new state
 2023-07-02 10:24:21,512 [classy] Setting parameters: {'Omega_m': 0.23330859700781822, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.0257544704451}
 2023-07-02 10:24:21,560 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,562 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.476286
 2023-07-02 10:24:21,562 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,562 [mcmc] New sample, #107:
   Omega_m:0.262696
 2023-07-02 10:24:21,562 [model] Posterior to be computed for parameters {'Omega_m': 0.223108250031336}
 2023-07-02 10:24:21,562 [prior] Evaluating prior at array([0.22310825])
 2023-07-02 10:24:21,562 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,562 [model] Got input parameters: {'Omega_m': 0.223108250031336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,562 [classy] Got parameters {'Omega_m': 0.223108250031336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,562 [classy] Computing new state
 2023-07-02 10:24:21,562 [classy] Setting parameters: {'Omega_m': 0.223108250031336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.62597526601968}
 2023-07-02 10:24:21,610 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,611 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.62558
 2023-07-02 10:24:21,611 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,611 [mcmc] New sample, #108:
   Omega_m:0.2333086
 2023-07-02 10:24:21,612 [model] Posterior to be computed for parameters {'Omega_m': 0.18301431251518846}
 2023-07-02 10:24:21,612 [prior] Evaluating prior at array([0.18301431])
 2023-07-02 10:24:21,612 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,612 [model] Got input parameters: {'Omega_m': 0.18301431251518846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,612 [classy] Got parameters {'Omega_m': 0.18301431251518846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,612 [classy] Computing new state
 2023-07-02 10:24:21,612 [classy] Setting parameters: {'Omega_m': 0.18301431251518846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.52807996718136}
 2023-07-02 10:24:21,660 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.4905
 2023-07-02 10:24:21,662 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,662 [model] Posterior to be computed for parameters {'Omega_m': 0.26142035989498996}
 2023-07-02 10:24:21,662 [prior] Evaluating prior at array([0.26142036])
 2023-07-02 10:24:21,662 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,662 [model] Got input parameters: {'Omega_m': 0.26142035989498996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,663 [classy] Got parameters {'Omega_m': 0.26142035989498996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,663 [classy] Computing new state
 2023-07-02 10:24:21,663 [classy] Setting parameters: {'Omega_m': 0.26142035989498996, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,710 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.8923003116362}
 2023-07-02 10:24:21,710 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,712 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.182981
 2023-07-02 10:24:21,712 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,712 [mcmc] New sample, #109:
   Omega_m:0.2231083
 2023-07-02 10:24:21,712 [model] Posterior to be computed for parameters {'Omega_m': 0.2842301996994825}
 2023-07-02 10:24:21,712 [prior] Evaluating prior at array([0.2842302])
 2023-07-02 10:24:21,712 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,712 [model] Got input parameters: {'Omega_m': 0.2842301996994825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,712 [classy] Got parameters {'Omega_m': 0.2842301996994825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,712 [classy] Computing new state
 2023-07-02 10:24:21,712 [classy] Setting parameters: {'Omega_m': 0.2842301996994825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,760 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.80303648186978}
 2023-07-02 10:24:21,760 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,762 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.052822
 2023-07-02 10:24:21,762 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,762 [mcmc] New sample, #110:
   Omega_m:0.2614204
 2023-07-02 10:24:21,762 [model] Posterior to be computed for parameters {'Omega_m': 0.3036936918666723}
 2023-07-02 10:24:21,762 [prior] Evaluating prior at array([0.30369369])
 2023-07-02 10:24:21,762 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,762 [model] Got input parameters: {'Omega_m': 0.3036936918666723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,762 [classy] Got parameters {'Omega_m': 0.3036936918666723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,762 [classy] Computing new state
 2023-07-02 10:24:21,762 [classy] Setting parameters: {'Omega_m': 0.3036936918666723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3312278802238}
 2023-07-02 10:24:21,810 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,812 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00504624
 2023-07-02 10:24:21,812 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,812 [mcmc] New sample, #111:
   Omega_m:0.2842302
 2023-07-02 10:24:21,812 [model] Posterior to be computed for parameters {'Omega_m': 0.30484146752666286}
 2023-07-02 10:24:21,812 [prior] Evaluating prior at array([0.30484147])
 2023-07-02 10:24:21,812 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,812 [model] Got input parameters: {'Omega_m': 0.30484146752666286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,812 [classy] Got parameters {'Omega_m': 0.30484146752666286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,812 [classy] Computing new state
 2023-07-02 10:24:21,812 [classy] Setting parameters: {'Omega_m': 0.30484146752666286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1898364580859}
 2023-07-02 10:24:21,860 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,862 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00385336
 2023-07-02 10:24:21,862 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,862 [mcmc] New sample, #112:
   Omega_m:0.3036937
 2023-07-02 10:24:21,862 [model] Posterior to be computed for parameters {'Omega_m': 0.2891974391020737}
 2023-07-02 10:24:21,862 [prior] Evaluating prior at array([0.28919744])
 2023-07-02 10:24:21,862 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,862 [model] Got input parameters: {'Omega_m': 0.2891974391020737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,862 [classy] Got parameters {'Omega_m': 0.2891974391020737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,862 [classy] Computing new state
 2023-07-02 10:24:21,863 [classy] Setting parameters: {'Omega_m': 0.2891974391020737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.15855523916892}
 2023-07-02 10:24:21,910 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,912 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0354848
 2023-07-02 10:24:21,912 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,912 [mcmc] New sample, #113:
   Omega_m:0.3048415
 2023-07-02 10:24:21,912 [model] Posterior to be computed for parameters {'Omega_m': 0.30566336299947927}
 2023-07-02 10:24:21,912 [prior] Evaluating prior at array([0.30566336])
 2023-07-02 10:24:21,912 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,912 [model] Got input parameters: {'Omega_m': 0.30566336299947927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,912 [classy] Got parameters {'Omega_m': 0.30566336299947927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,912 [classy] Computing new state
 2023-07-02 10:24:21,912 [classy] Setting parameters: {'Omega_m': 0.30566336299947927, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:21,960 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.08887717484674}
 2023-07-02 10:24:21,960 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:21,962 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00310436
 2023-07-02 10:24:21,962 [model] Computed derived parameters: {}
 2023-07-02 10:24:21,962 [mcmc] New sample, #114:
   Omega_m:0.2891974
 2023-07-02 10:24:21,962 [model] Posterior to be computed for parameters {'Omega_m': 0.0890050969170921}
 2023-07-02 10:24:21,962 [prior] Evaluating prior at array([0.0890051])
 2023-07-02 10:24:21,962 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:21,962 [model] Posterior to be computed for parameters {'Omega_m': 0.35162412565256884}
 2023-07-02 10:24:21,962 [prior] Evaluating prior at array([0.35162413])
 2023-07-02 10:24:21,962 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:21,962 [model] Got input parameters: {'Omega_m': 0.35162412565256884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,962 [classy] Got parameters {'Omega_m': 0.35162412565256884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:21,962 [classy] Computing new state
 2023-07-02 10:24:21,962 [classy] Setting parameters: {'Omega_m': 0.35162412565256884, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,010 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.79619655141454}
 2023-07-02 10:24:22,010 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0857218
 2023-07-02 10:24:22,013 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,014 [mcmc] New sample, #115:
   Omega_m:0.3056634
 2023-07-02 10:24:22,014 [model] Posterior to be computed for parameters {'Omega_m': 0.4427614040795856}
 2023-07-02 10:24:22,014 [prior] Evaluating prior at array([0.4427614])
 2023-07-02 10:24:22,014 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,014 [model] Got input parameters: {'Omega_m': 0.4427614040795856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,014 [classy] Got parameters {'Omega_m': 0.4427614040795856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,014 [classy] Computing new state
 2023-07-02 10:24:22,014 [classy] Setting parameters: {'Omega_m': 0.4427614040795856, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,063 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.96905594953483}
 2023-07-02 10:24:22,063 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,065 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.779368
 2023-07-02 10:24:22,065 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,065 [mcmc] New sample, #116:
   Omega_m:0.3516241
 2023-07-02 10:24:22,065 [model] Posterior to be computed for parameters {'Omega_m': 0.3935343636714861}
 2023-07-02 10:24:22,066 [prior] Evaluating prior at array([0.39353436])
 2023-07-02 10:24:22,066 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,066 [model] Got input parameters: {'Omega_m': 0.3935343636714861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,066 [classy] Got parameters {'Omega_m': 0.3935343636714861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,066 [classy] Computing new state
 2023-07-02 10:24:22,066 [classy] Setting parameters: {'Omega_m': 0.3935343636714861, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.49639854759803}
 2023-07-02 10:24:22,113 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,115 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.334174
 2023-07-02 10:24:22,115 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,115 [mcmc] New sample, #117:
   Omega_m:0.4427614
 2023-07-02 10:24:22,115 [model] Posterior to be computed for parameters {'Omega_m': 0.3823420602657087}
 2023-07-02 10:24:22,115 [prior] Evaluating prior at array([0.38234206])
 2023-07-02 10:24:22,115 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,115 [model] Got input parameters: {'Omega_m': 0.3823420602657087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,115 [classy] Got parameters {'Omega_m': 0.3823420602657087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,115 [classy] Computing new state
 2023-07-02 10:24:22,115 [classy] Setting parameters: {'Omega_m': 0.3823420602657087, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.6010943040304}
 2023-07-02 10:24:22,164 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,166 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.254415
 2023-07-02 10:24:22,166 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,166 [mcmc] New sample, #118:
   Omega_m:0.3935344
 2023-07-02 10:24:22,166 [model] Posterior to be computed for parameters {'Omega_m': 0.46741677759013117}
 2023-07-02 10:24:22,166 [prior] Evaluating prior at array([0.46741678])
 2023-07-02 10:24:22,166 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,166 [model] Got input parameters: {'Omega_m': 0.46741677759013117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,166 [classy] Got parameters {'Omega_m': 0.46741677759013117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,166 [classy] Computing new state
 2023-07-02 10:24:22,166 [classy] Setting parameters: {'Omega_m': 0.46741677759013117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8825220726529}
 2023-07-02 10:24:22,215 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,217 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05023
 2023-07-02 10:24:22,217 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,217 [model] Posterior to be computed for parameters {'Omega_m': 0.3622509917754513}
 2023-07-02 10:24:22,217 [prior] Evaluating prior at array([0.36225099])
 2023-07-02 10:24:22,217 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,217 [model] Got input parameters: {'Omega_m': 0.3622509917754513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,217 [classy] Got parameters {'Omega_m': 0.3622509917754513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,217 [classy] Computing new state
 2023-07-02 10:24:22,217 [classy] Setting parameters: {'Omega_m': 0.3622509917754513, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.66248566384328}
 2023-07-02 10:24:22,266 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.135139
 2023-07-02 10:24:22,268 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,268 [mcmc] New sample, #119:
   Omega_m:0.3823421
 2023-07-02 10:24:22,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3407912420860704}
 2023-07-02 10:24:22,268 [prior] Evaluating prior at array([0.34079124])
 2023-07-02 10:24:22,268 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,268 [model] Got input parameters: {'Omega_m': 0.3407912420860704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,268 [classy] Got parameters {'Omega_m': 0.3407912420860704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,268 [classy] Computing new state
 2023-07-02 10:24:22,268 [classy] Setting parameters: {'Omega_m': 0.3407912420860704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,315 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.98473571356905}
 2023-07-02 10:24:22,316 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.046081
 2023-07-02 10:24:22,318 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,318 [mcmc] New sample, #120:
   Omega_m:0.362251
 2023-07-02 10:24:22,318 [mcmc] Learn + convergence test @ 120 samples accepted.
 2023-07-02 10:24:22,318 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:22,325 [mcmc]  - Acceptance rate: 0.865
 2023-07-02 10:24:22,326 [mcmc]  - Condition number = 1
 2023-07-02 10:24:22,326 [mcmc]  - Eigenvalues = array([0.19826185])
 2023-07-02 10:24:22,326 [mcmc]  - Convergence of means: R-1 = 0.198262 after 96 accepted steps
 2023-07-02 10:24:22,326 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:22,326 [mcmc] array([[0.01064517]])
 2023-07-02 10:24:22,337 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:22,337 [model] Posterior to be computed for parameters {'Omega_m': 0.14206225343130843}
 2023-07-02 10:24:22,337 [prior] Evaluating prior at array([0.14206225])
 2023-07-02 10:24:22,337 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,338 [model] Got input parameters: {'Omega_m': 0.14206225343130843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,338 [classy] Got parameters {'Omega_m': 0.14206225343130843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,338 [classy] Computing new state
 2023-07-02 10:24:22,338 [classy] Setting parameters: {'Omega_m': 0.14206225343130843, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.82952700610903}
 2023-07-02 10:24:22,385 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.9856
 2023-07-02 10:24:22,387 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,387 [mcmc] New sample, #121:
   Omega_m:0.3407912
 2023-07-02 10:24:22,387 [model] Posterior to be computed for parameters {'Omega_m': -0.33651803915215794}
 2023-07-02 10:24:22,387 [prior] Evaluating prior at array([-0.33651804])
 2023-07-02 10:24:22,387 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:22,387 [model] Posterior to be computed for parameters {'Omega_m': 0.06128268951356944}
 2023-07-02 10:24:22,387 [prior] Evaluating prior at array([0.06128269])
 2023-07-02 10:24:22,387 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:22,387 [model] Posterior to be computed for parameters {'Omega_m': 0.4818798357930848}
 2023-07-02 10:24:22,387 [prior] Evaluating prior at array([0.48187984])
 2023-07-02 10:24:22,387 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,388 [model] Got input parameters: {'Omega_m': 0.4818798357930848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,388 [classy] Got parameters {'Omega_m': 0.4818798357930848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,388 [classy] Computing new state
 2023-07-02 10:24:22,388 [classy] Setting parameters: {'Omega_m': 0.4818798357930848, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.70860136326027}
 2023-07-02 10:24:22,435 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,437 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.22132
 2023-07-02 10:24:22,437 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,437 [mcmc] New sample, #122:
   Omega_m:0.1420623
 2023-07-02 10:24:22,437 [model] Posterior to be computed for parameters {'Omega_m': 0.12258725916394797}
 2023-07-02 10:24:22,437 [prior] Evaluating prior at array([0.12258726])
 2023-07-02 10:24:22,437 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,437 [model] Got input parameters: {'Omega_m': 0.12258725916394797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,437 [classy] Got parameters {'Omega_m': 0.12258725916394797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,437 [classy] Computing new state
 2023-07-02 10:24:22,437 [classy] Setting parameters: {'Omega_m': 0.12258725916394797, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,483 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.34986909166238}
 2023-07-02 10:24:22,483 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,485 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.99807
 2023-07-02 10:24:22,485 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,485 [model] Posterior to be computed for parameters {'Omega_m': 0.4677104717372182}
 2023-07-02 10:24:22,485 [prior] Evaluating prior at array([0.46771047])
 2023-07-02 10:24:22,486 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,486 [model] Got input parameters: {'Omega_m': 0.4677104717372182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,486 [classy] Got parameters {'Omega_m': 0.4677104717372182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,486 [classy] Computing new state
 2023-07-02 10:24:22,486 [classy] Setting parameters: {'Omega_m': 0.4677104717372182, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.85832797726198}
 2023-07-02 10:24:22,532 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,534 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05362
 2023-07-02 10:24:22,534 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,534 [mcmc] New sample, #123:
   Omega_m:0.4818798
 2023-07-02 10:24:22,534 [model] Posterior to be computed for parameters {'Omega_m': 0.7341476064363232}
 2023-07-02 10:24:22,534 [prior] Evaluating prior at array([0.73414761])
 2023-07-02 10:24:22,534 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,534 [model] Got input parameters: {'Omega_m': 0.7341476064363232, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,534 [classy] Got parameters {'Omega_m': 0.7341476064363232, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,534 [classy] Computing new state
 2023-07-02 10:24:22,534 [classy] Setting parameters: {'Omega_m': 0.7341476064363232, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.58977454941673}
 2023-07-02 10:24:22,580 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.0319
 2023-07-02 10:24:22,582 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,582 [model] Posterior to be computed for parameters {'Omega_m': 0.2995549035460449}
 2023-07-02 10:24:22,582 [prior] Evaluating prior at array([0.2995549])
 2023-07-02 10:24:22,582 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,582 [model] Got input parameters: {'Omega_m': 0.2995549035460449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,582 [classy] Got parameters {'Omega_m': 0.2995549035460449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,582 [classy] Computing new state
 2023-07-02 10:24:22,582 [classy] Setting parameters: {'Omega_m': 0.2995549035460449, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8450191001144}
 2023-07-02 10:24:22,630 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,631 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0107919
 2023-07-02 10:24:22,631 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,631 [mcmc] New sample, #124:
   Omega_m:0.4677105
 2023-07-02 10:24:22,632 [model] Posterior to be computed for parameters {'Omega_m': 0.17212523664658047}
 2023-07-02 10:24:22,632 [prior] Evaluating prior at array([0.17212524])
 2023-07-02 10:24:22,632 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,632 [model] Got input parameters: {'Omega_m': 0.17212523664658047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,632 [classy] Got parameters {'Omega_m': 0.17212523664658047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,632 [classy] Computing new state
 2023-07-02 10:24:22,632 [classy] Setting parameters: {'Omega_m': 0.17212523664658047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.59629567843504}
 2023-07-02 10:24:22,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.81762
 2023-07-02 10:24:22,681 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,681 [model] Posterior to be computed for parameters {'Omega_m': 0.6178583464290346}
 2023-07-02 10:24:22,681 [prior] Evaluating prior at array([0.61785835])
 2023-07-02 10:24:22,682 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,682 [model] Got input parameters: {'Omega_m': 0.6178583464290346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,682 [classy] Got parameters {'Omega_m': 0.6178583464290346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,682 [classy] Computing new state
 2023-07-02 10:24:22,682 [classy] Setting parameters: {'Omega_m': 0.6178583464290346, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,729 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.15268770890266}
 2023-07-02 10:24:22,729 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,731 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.13828
 2023-07-02 10:24:22,731 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,731 [model] Posterior to be computed for parameters {'Omega_m': 0.5425659347968598}
 2023-07-02 10:24:22,731 [prior] Evaluating prior at array([0.54256593])
 2023-07-02 10:24:22,731 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,731 [model] Got input parameters: {'Omega_m': 0.5425659347968598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,731 [classy] Got parameters {'Omega_m': 0.5425659347968598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,731 [classy] Computing new state
 2023-07-02 10:24:22,731 [classy] Setting parameters: {'Omega_m': 0.5425659347968598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.14081340246815}
 2023-07-02 10:24:22,778 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.01872
 2023-07-02 10:24:22,780 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,780 [model] Posterior to be computed for parameters {'Omega_m': 0.5006328308081452}
 2023-07-02 10:24:22,780 [prior] Evaluating prior at array([0.50063283])
 2023-07-02 10:24:22,781 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,781 [model] Got input parameters: {'Omega_m': 0.5006328308081452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,781 [classy] Got parameters {'Omega_m': 0.5006328308081452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,781 [classy] Computing new state
 2023-07-02 10:24:22,781 [classy] Setting parameters: {'Omega_m': 0.5006328308081452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.23779239091814}
 2023-07-02 10:24:22,828 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,829 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.455
 2023-07-02 10:24:22,829 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,830 [model] Posterior to be computed for parameters {'Omega_m': 0.03334462802441124}
 2023-07-02 10:24:22,830 [prior] Evaluating prior at array([0.03334463])
 2023-07-02 10:24:22,830 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:22,830 [model] Posterior to be computed for parameters {'Omega_m': -0.1589279775940718}
 2023-07-02 10:24:22,830 [prior] Evaluating prior at array([-0.15892798])
 2023-07-02 10:24:22,830 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:22,830 [model] Posterior to be computed for parameters {'Omega_m': 0.4259348139929615}
 2023-07-02 10:24:22,830 [prior] Evaluating prior at array([0.42593481])
 2023-07-02 10:24:22,830 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,830 [model] Got input parameters: {'Omega_m': 0.4259348139929615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,830 [classy] Got parameters {'Omega_m': 0.4259348139929615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,830 [classy] Computing new state
 2023-07-02 10:24:22,830 [classy] Setting parameters: {'Omega_m': 0.4259348139929615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.45940771058147}
 2023-07-02 10:24:22,877 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,878 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.611526
 2023-07-02 10:24:22,879 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,879 [mcmc] New sample, #125:
   Omega_m:0.2995549
 2023-07-02 10:24:22,879 [model] Posterior to be computed for parameters {'Omega_m': 0.4624401870941436}
 2023-07-02 10:24:22,879 [prior] Evaluating prior at array([0.46244019])
 2023-07-02 10:24:22,879 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,879 [model] Got input parameters: {'Omega_m': 0.4624401870941436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,879 [classy] Got parameters {'Omega_m': 0.4624401870941436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,879 [classy] Computing new state
 2023-07-02 10:24:22,879 [classy] Setting parameters: {'Omega_m': 0.4624401870941436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.2947996815878}
 2023-07-02 10:24:22,926 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,928 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.993355
 2023-07-02 10:24:22,928 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,928 [model] Posterior to be computed for parameters {'Omega_m': 0.24167661050146633}
 2023-07-02 10:24:22,928 [prior] Evaluating prior at array([0.24167661])
 2023-07-02 10:24:22,928 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,928 [model] Got input parameters: {'Omega_m': 0.24167661050146633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,928 [classy] Got parameters {'Omega_m': 0.24167661050146633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,928 [classy] Computing new state
 2023-07-02 10:24:22,928 [classy] Setting parameters: {'Omega_m': 0.24167661050146633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:22,976 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.75453153435635}
 2023-07-02 10:24:22,976 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:22,978 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.371798
 2023-07-02 10:24:22,978 [model] Computed derived parameters: {}
 2023-07-02 10:24:22,978 [mcmc] New sample, #126:
   Omega_m:0.4259348
 2023-07-02 10:24:22,978 [model] Posterior to be computed for parameters {'Omega_m': -0.07734807144616312}
 2023-07-02 10:24:22,978 [prior] Evaluating prior at array([-0.07734807])
 2023-07-02 10:24:22,978 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:22,978 [model] Posterior to be computed for parameters {'Omega_m': -0.08855664694599208}
 2023-07-02 10:24:22,978 [prior] Evaluating prior at array([-0.08855665])
 2023-07-02 10:24:22,978 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:22,978 [model] Posterior to be computed for parameters {'Omega_m': 0.35576828245936876}
 2023-07-02 10:24:22,978 [prior] Evaluating prior at array([0.35576828])
 2023-07-02 10:24:22,979 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:22,979 [model] Got input parameters: {'Omega_m': 0.35576828245936876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,979 [classy] Got parameters {'Omega_m': 0.35576828245936876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:22,979 [classy] Computing new state
 2023-07-02 10:24:22,979 [classy] Setting parameters: {'Omega_m': 0.35576828245936876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.35037135446305}
 2023-07-02 10:24:23,027 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,029 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103797
 2023-07-02 10:24:23,029 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,029 [mcmc] New sample, #127:
   Omega_m:0.2416766
 2023-07-02 10:24:23,029 [model] Posterior to be computed for parameters {'Omega_m': 0.3905998800715945}
 2023-07-02 10:24:23,029 [prior] Evaluating prior at array([0.39059988])
 2023-07-02 10:24:23,029 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,029 [model] Got input parameters: {'Omega_m': 0.3905998800715945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,029 [classy] Got parameters {'Omega_m': 0.3905998800715945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,029 [classy] Computing new state
 2023-07-02 10:24:23,029 [classy] Setting parameters: {'Omega_m': 0.3905998800715945, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.7831249620747}
 2023-07-02 10:24:23,076 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.312402
 2023-07-02 10:24:23,078 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,078 [model] Posterior to be computed for parameters {'Omega_m': 0.4609250190800241}
 2023-07-02 10:24:23,078 [prior] Evaluating prior at array([0.46092502])
 2023-07-02 10:24:23,078 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,078 [model] Got input parameters: {'Omega_m': 0.4609250190800241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,078 [classy] Got parameters {'Omega_m': 0.4609250190800241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,079 [classy] Computing new state
 2023-07-02 10:24:23,079 [classy] Setting parameters: {'Omega_m': 0.4609250190800241, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.42118883247076}
 2023-07-02 10:24:23,129 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,130 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.976253
 2023-07-02 10:24:23,130 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,131 [model] Posterior to be computed for parameters {'Omega_m': 0.5286028310987089}
 2023-07-02 10:24:23,131 [prior] Evaluating prior at array([0.52860283])
 2023-07-02 10:24:23,131 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,131 [model] Got input parameters: {'Omega_m': 0.5286028310987089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,131 [classy] Got parameters {'Omega_m': 0.5286028310987089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,131 [classy] Computing new state
 2023-07-02 10:24:23,131 [classy] Setting parameters: {'Omega_m': 0.5286028310987089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,179 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.14416363848744}
 2023-07-02 10:24:23,179 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,181 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.82531
 2023-07-02 10:24:23,181 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,181 [model] Posterior to be computed for parameters {'Omega_m': 0.32389924181819896}
 2023-07-02 10:24:23,181 [prior] Evaluating prior at array([0.32389924])
 2023-07-02 10:24:23,181 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,181 [model] Got input parameters: {'Omega_m': 0.32389924181819896, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,181 [classy] Got parameters {'Omega_m': 0.32389924181819896, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,181 [classy] Computing new state
 2023-07-02 10:24:23,181 [classy] Setting parameters: {'Omega_m': 0.32389924181819896, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90843369677927}
 2023-07-02 10:24:23,229 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,231 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00797111
 2023-07-02 10:24:23,231 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,231 [mcmc] New sample, #128:
   Omega_m:0.3557683
 2023-07-02 10:24:23,231 [model] Posterior to be computed for parameters {'Omega_m': 0.3382696126392587}
 2023-07-02 10:24:23,231 [prior] Evaluating prior at array([0.33826961])
 2023-07-02 10:24:23,231 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,231 [model] Got input parameters: {'Omega_m': 0.3382696126392587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,231 [classy] Got parameters {'Omega_m': 0.3382696126392587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,232 [classy] Computing new state
 2023-07-02 10:24:23,232 [classy] Setting parameters: {'Omega_m': 0.3382696126392587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.26635108854407}
 2023-07-02 10:24:23,279 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,280 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0384985
 2023-07-02 10:24:23,281 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,281 [mcmc] New sample, #129:
   Omega_m:0.3238992
 2023-07-02 10:24:23,281 [model] Posterior to be computed for parameters {'Omega_m': 0.05995848092867245}
 2023-07-02 10:24:23,281 [prior] Evaluating prior at array([0.05995848])
 2023-07-02 10:24:23,281 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:23,281 [model] Posterior to be computed for parameters {'Omega_m': 0.10088278595666456}
 2023-07-02 10:24:23,281 [prior] Evaluating prior at array([0.10088279])
 2023-07-02 10:24:23,281 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,281 [model] Got input parameters: {'Omega_m': 0.10088278595666456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,281 [classy] Got parameters {'Omega_m': 0.10088278595666456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,281 [classy] Computing new state
 2023-07-02 10:24:23,281 [classy] Setting parameters: {'Omega_m': 0.10088278595666456, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 184.93669596313848}
 2023-07-02 10:24:23,328 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.43355
 2023-07-02 10:24:23,330 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,331 [model] Posterior to be computed for parameters {'Omega_m': 0.2084565679017576}
 2023-07-02 10:24:23,331 [prior] Evaluating prior at array([0.20845657])
 2023-07-02 10:24:23,331 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,331 [model] Got input parameters: {'Omega_m': 0.2084565679017576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,331 [classy] Got parameters {'Omega_m': 0.2084565679017576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,331 [classy] Computing new state
 2023-07-02 10:24:23,331 [classy] Setting parameters: {'Omega_m': 0.2084565679017576, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.02879024975945}
 2023-07-02 10:24:23,378 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,380 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.886402
 2023-07-02 10:24:23,380 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,380 [model] Posterior to be computed for parameters {'Omega_m': 0.2221715877530942}
 2023-07-02 10:24:23,380 [prior] Evaluating prior at array([0.22217159])
 2023-07-02 10:24:23,380 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,380 [model] Got input parameters: {'Omega_m': 0.2221715877530942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,380 [classy] Got parameters {'Omega_m': 0.2221715877530942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,380 [classy] Computing new state
 2023-07-02 10:24:23,380 [classy] Setting parameters: {'Omega_m': 0.2221715877530942, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.77581032256077}
 2023-07-02 10:24:23,428 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.640563
 2023-07-02 10:24:23,430 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,430 [model] Posterior to be computed for parameters {'Omega_m': 0.3884377383665991}
 2023-07-02 10:24:23,430 [prior] Evaluating prior at array([0.38843774])
 2023-07-02 10:24:23,431 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,431 [model] Got input parameters: {'Omega_m': 0.3884377383665991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,431 [classy] Got parameters {'Omega_m': 0.3884377383665991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,431 [classy] Computing new state
 2023-07-02 10:24:23,431 [classy] Setting parameters: {'Omega_m': 0.3884377383665991, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.9957112674892}
 2023-07-02 10:24:23,479 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.296744
 2023-07-02 10:24:23,481 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,481 [mcmc] New sample, #130:
   Omega_m:0.3382696
 2023-07-02 10:24:23,481 [model] Posterior to be computed for parameters {'Omega_m': 0.36028096075323623}
 2023-07-02 10:24:23,481 [prior] Evaluating prior at array([0.36028096])
 2023-07-02 10:24:23,481 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,481 [model] Got input parameters: {'Omega_m': 0.36028096075323623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,481 [classy] Got parameters {'Omega_m': 0.36028096075323623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,481 [classy] Computing new state
 2023-07-02 10:24:23,481 [classy] Setting parameters: {'Omega_m': 0.36028096075323623, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.87030108539744}
 2023-07-02 10:24:23,528 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125228
 2023-07-02 10:24:23,530 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,530 [mcmc] New sample, #131:
   Omega_m:0.3884377
 2023-07-02 10:24:23,530 [model] Posterior to be computed for parameters {'Omega_m': 0.42634451615557567}
 2023-07-02 10:24:23,530 [prior] Evaluating prior at array([0.42634452])
 2023-07-02 10:24:23,530 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,530 [model] Got input parameters: {'Omega_m': 0.42634451615557567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,530 [classy] Got parameters {'Omega_m': 0.42634451615557567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,531 [classy] Computing new state
 2023-07-02 10:24:23,531 [classy] Setting parameters: {'Omega_m': 0.42634451615557567, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,576 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.42244799335614}
 2023-07-02 10:24:23,576 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,578 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.615433
 2023-07-02 10:24:23,578 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,578 [model] Posterior to be computed for parameters {'Omega_m': 0.041735156496988224}
 2023-07-02 10:24:23,578 [prior] Evaluating prior at array([0.04173516])
 2023-07-02 10:24:23,578 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:23,578 [model] Posterior to be computed for parameters {'Omega_m': 0.16533821645096491}
 2023-07-02 10:24:23,578 [prior] Evaluating prior at array([0.16533822])
 2023-07-02 10:24:23,579 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,579 [model] Got input parameters: {'Omega_m': 0.16533821645096491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,579 [classy] Got parameters {'Omega_m': 0.16533821645096491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,579 [classy] Computing new state
 2023-07-02 10:24:23,579 [classy] Setting parameters: {'Omega_m': 0.16533821645096491, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,624 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.9333502196603}
 2023-07-02 10:24:23,624 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.04532
 2023-07-02 10:24:23,627 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,627 [mcmc] New sample, #132:
   Omega_m:0.360281
 2023-07-02 10:24:23,627 [model] Posterior to be computed for parameters {'Omega_m': 0.06926126170119862}
 2023-07-02 10:24:23,627 [prior] Evaluating prior at array([0.06926126])
 2023-07-02 10:24:23,627 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:23,627 [model] Posterior to be computed for parameters {'Omega_m': 0.5741626817207262}
 2023-07-02 10:24:23,627 [prior] Evaluating prior at array([0.57416268])
 2023-07-02 10:24:23,628 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,628 [model] Got input parameters: {'Omega_m': 0.5741626817207262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,628 [classy] Got parameters {'Omega_m': 0.5741626817207262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,628 [classy] Computing new state
 2023-07-02 10:24:23,628 [classy] Setting parameters: {'Omega_m': 0.5741626817207262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,675 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.9649771753205}
 2023-07-02 10:24:23,675 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,677 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.47434
 2023-07-02 10:24:23,677 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,677 [model] Posterior to be computed for parameters {'Omega_m': 0.16579412026351453}
 2023-07-02 10:24:23,678 [prior] Evaluating prior at array([0.16579412])
 2023-07-02 10:24:23,678 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,678 [model] Got input parameters: {'Omega_m': 0.16579412026351453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,678 [classy] Got parameters {'Omega_m': 0.16579412026351453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,678 [classy] Computing new state
 2023-07-02 10:24:23,678 [classy] Setting parameters: {'Omega_m': 0.16579412026351453, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,723 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.84233671992158}
 2023-07-02 10:24:23,723 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,725 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.02942
 2023-07-02 10:24:23,725 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,725 [mcmc] New sample, #133:
   Omega_m:0.1653382
 2023-07-02 10:24:23,725 [model] Posterior to be computed for parameters {'Omega_m': 0.46337149122354393}
 2023-07-02 10:24:23,725 [prior] Evaluating prior at array([0.46337149])
 2023-07-02 10:24:23,725 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,725 [model] Got input parameters: {'Omega_m': 0.46337149122354393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,725 [classy] Got parameters {'Omega_m': 0.46337149122354393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,725 [classy] Computing new state
 2023-07-02 10:24:23,725 [classy] Setting parameters: {'Omega_m': 0.46337149122354393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.21731539998035}
 2023-07-02 10:24:23,772 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.00392
 2023-07-02 10:24:23,774 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,774 [mcmc] New sample, #134:
   Omega_m:0.1657941
 2023-07-02 10:24:23,774 [model] Posterior to be computed for parameters {'Omega_m': 0.7655513096513915}
 2023-07-02 10:24:23,774 [prior] Evaluating prior at array([0.76555131])
 2023-07-02 10:24:23,774 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,774 [model] Got input parameters: {'Omega_m': 0.7655513096513915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,774 [classy] Got parameters {'Omega_m': 0.7655513096513915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,774 [classy] Computing new state
 2023-07-02 10:24:23,774 [classy] Setting parameters: {'Omega_m': 0.7655513096513915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.00950138015209}
 2023-07-02 10:24:23,820 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.56307
 2023-07-02 10:24:23,822 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,822 [model] Posterior to be computed for parameters {'Omega_m': 0.270789139040159}
 2023-07-02 10:24:23,822 [prior] Evaluating prior at array([0.27078914])
 2023-07-02 10:24:23,822 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,822 [model] Got input parameters: {'Omega_m': 0.270789139040159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,822 [classy] Got parameters {'Omega_m': 0.270789139040159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,822 [classy] Computing new state
 2023-07-02 10:24:23,822 [classy] Setting parameters: {'Omega_m': 0.270789139040159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.5967610910096}
 2023-07-02 10:24:23,868 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,870 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.118981
 2023-07-02 10:24:23,870 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,870 [mcmc] New sample, #135:
   Omega_m:0.4633715
 2023-07-02 10:24:23,870 [model] Posterior to be computed for parameters {'Omega_m': 0.6082507166716997}
 2023-07-02 10:24:23,870 [prior] Evaluating prior at array([0.60825072])
 2023-07-02 10:24:23,870 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,870 [model] Got input parameters: {'Omega_m': 0.6082507166716997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,871 [classy] Got parameters {'Omega_m': 0.6082507166716997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,871 [classy] Computing new state
 2023-07-02 10:24:23,871 [classy] Setting parameters: {'Omega_m': 0.6082507166716997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.75276112503566}
 2023-07-02 10:24:23,917 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,919 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.9894
 2023-07-02 10:24:23,919 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,919 [model] Posterior to be computed for parameters {'Omega_m': 0.5059672011936754}
 2023-07-02 10:24:23,919 [prior] Evaluating prior at array([0.5059672])
 2023-07-02 10:24:23,920 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,920 [model] Got input parameters: {'Omega_m': 0.5059672011936754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,920 [classy] Got parameters {'Omega_m': 0.5059672011936754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,920 [classy] Computing new state
 2023-07-02 10:24:23,920 [classy] Setting parameters: {'Omega_m': 0.5059672011936754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:23,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.82951290949086}
 2023-07-02 10:24:23,966 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:23,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.52371
 2023-07-02 10:24:23,968 [model] Computed derived parameters: {}
 2023-07-02 10:24:23,968 [model] Posterior to be computed for parameters {'Omega_m': 0.4807708409920225}
 2023-07-02 10:24:23,968 [prior] Evaluating prior at array([0.48077084])
 2023-07-02 10:24:23,968 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:23,968 [model] Got input parameters: {'Omega_m': 0.4807708409920225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,969 [classy] Got parameters {'Omega_m': 0.4807708409920225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:23,969 [classy] Computing new state
 2023-07-02 10:24:23,969 [classy] Setting parameters: {'Omega_m': 0.4807708409920225, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.7973630919621}
 2023-07-02 10:24:24,015 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.20791
 2023-07-02 10:24:24,017 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,017 [mcmc] New sample, #136:
   Omega_m:0.2707891
 2023-07-02 10:24:24,017 [model] Posterior to be computed for parameters {'Omega_m': 0.47910613365540666}
 2023-07-02 10:24:24,017 [prior] Evaluating prior at array([0.47910613])
 2023-07-02 10:24:24,017 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,017 [model] Got input parameters: {'Omega_m': 0.47910613365540666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,017 [classy] Got parameters {'Omega_m': 0.47910613365540666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,017 [classy] Computing new state
 2023-07-02 10:24:24,017 [classy] Setting parameters: {'Omega_m': 0.47910613365540666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.93098341594222}
 2023-07-02 10:24:24,065 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,067 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.18787
 2023-07-02 10:24:24,067 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,067 [mcmc] New sample, #137:
   Omega_m:0.4807708
 2023-07-02 10:24:24,067 [model] Posterior to be computed for parameters {'Omega_m': 0.6326607954686883}
 2023-07-02 10:24:24,067 [prior] Evaluating prior at array([0.6326608])
 2023-07-02 10:24:24,067 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,067 [model] Got input parameters: {'Omega_m': 0.6326607954686883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,067 [classy] Got parameters {'Omega_m': 0.6326607954686883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,067 [classy] Computing new state
 2023-07-02 10:24:24,067 [classy] Setting parameters: {'Omega_m': 0.6326607954686883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.24713523779305}
 2023-07-02 10:24:24,112 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,114 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.37049
 2023-07-02 10:24:24,114 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,114 [model] Posterior to be computed for parameters {'Omega_m': 0.305662828461555}
 2023-07-02 10:24:24,114 [prior] Evaluating prior at array([0.30566283])
 2023-07-02 10:24:24,115 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,115 [model] Got input parameters: {'Omega_m': 0.305662828461555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,115 [classy] Got parameters {'Omega_m': 0.305662828461555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,115 [classy] Computing new state
 2023-07-02 10:24:24,115 [classy] Setting parameters: {'Omega_m': 0.305662828461555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,162 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.08894363688228}
 2023-07-02 10:24:24,162 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,163 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00310483
 2023-07-02 10:24:24,164 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,164 [mcmc] New sample, #138:
   Omega_m:0.4791061
 2023-07-02 10:24:24,164 [model] Posterior to be computed for parameters {'Omega_m': 1.0771052795016534}
 2023-07-02 10:24:24,164 [prior] Evaluating prior at array([1.07710528])
 2023-07-02 10:24:24,164 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:24,164 [model] Posterior to be computed for parameters {'Omega_m': 0.2976259333085199}
 2023-07-02 10:24:24,164 [prior] Evaluating prior at array([0.29762593])
 2023-07-02 10:24:24,164 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,164 [model] Got input parameters: {'Omega_m': 0.2976259333085199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,164 [classy] Got parameters {'Omega_m': 0.2976259333085199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,164 [classy] Computing new state
 2023-07-02 10:24:24,164 [classy] Setting parameters: {'Omega_m': 0.2976259333085199, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,211 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.08662803830572}
 2023-07-02 10:24:24,211 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,213 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.014257
 2023-07-02 10:24:24,213 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,213 [mcmc] New sample, #139:
   Omega_m:0.3056628
 2023-07-02 10:24:24,213 [model] Posterior to be computed for parameters {'Omega_m': 0.35859448483837464}
 2023-07-02 10:24:24,213 [prior] Evaluating prior at array([0.35859448])
 2023-07-02 10:24:24,213 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,214 [model] Got input parameters: {'Omega_m': 0.35859448483837464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,214 [classy] Got parameters {'Omega_m': 0.35859448483837464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,214 [classy] Computing new state
 2023-07-02 10:24:24,214 [classy] Setting parameters: {'Omega_m': 0.35859448483837464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.04905839839446}
 2023-07-02 10:24:24,262 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,263 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.117009
 2023-07-02 10:24:24,263 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,264 [mcmc] New sample, #140:
   Omega_m:0.2976259
 2023-07-02 10:24:24,264 [model] Posterior to be computed for parameters {'Omega_m': 0.005247977872464726}
 2023-07-02 10:24:24,264 [prior] Evaluating prior at array([0.00524798])
 2023-07-02 10:24:24,264 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:24,264 [model] Posterior to be computed for parameters {'Omega_m': 0.32056643279504426}
 2023-07-02 10:24:24,264 [prior] Evaluating prior at array([0.32056643])
 2023-07-02 10:24:24,264 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,264 [model] Got input parameters: {'Omega_m': 0.32056643279504426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,264 [classy] Got parameters {'Omega_m': 0.32056643279504426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,264 [classy] Computing new state
 2023-07-02 10:24:24,264 [classy] Setting parameters: {'Omega_m': 0.32056643279504426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.29862574019367}
 2023-07-02 10:24:24,312 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00412868
 2023-07-02 10:24:24,314 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,314 [mcmc] New sample, #141:
   Omega_m:0.3585945
 2023-07-02 10:24:24,314 [model] Posterior to be computed for parameters {'Omega_m': 0.6197586399129854}
 2023-07-02 10:24:24,314 [prior] Evaluating prior at array([0.61975864])
 2023-07-02 10:24:24,314 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,314 [model] Got input parameters: {'Omega_m': 0.6197586399129854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,314 [classy] Got parameters {'Omega_m': 0.6197586399129854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,314 [classy] Computing new state
 2023-07-02 10:24:24,314 [classy] Setting parameters: {'Omega_m': 0.6197586399129854, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.03515687597314}
 2023-07-02 10:24:24,362 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,363 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.16791
 2023-07-02 10:24:24,363 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,364 [model] Posterior to be computed for parameters {'Omega_m': 0.03223708890050481}
 2023-07-02 10:24:24,364 [prior] Evaluating prior at array([0.03223709])
 2023-07-02 10:24:24,364 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:24,364 [model] Posterior to be computed for parameters {'Omega_m': 0.5573407947048554}
 2023-07-02 10:24:24,364 [prior] Evaluating prior at array([0.55734079])
 2023-07-02 10:24:24,364 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,364 [model] Got input parameters: {'Omega_m': 0.5573407947048554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,364 [classy] Got parameters {'Omega_m': 0.5573407947048554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,364 [classy] Computing new state
 2023-07-02 10:24:24,364 [classy] Setting parameters: {'Omega_m': 0.5573407947048554, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,412 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.10755005544335}
 2023-07-02 10:24:24,412 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.22886
 2023-07-02 10:24:24,413 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,414 [model] Posterior to be computed for parameters {'Omega_m': 0.2946949033424985}
 2023-07-02 10:24:24,414 [prior] Evaluating prior at array([0.2946949])
 2023-07-02 10:24:24,414 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,414 [model] Got input parameters: {'Omega_m': 0.2946949033424985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,414 [classy] Got parameters {'Omega_m': 0.2946949033424985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,414 [classy] Computing new state
 2023-07-02 10:24:24,414 [classy] Setting parameters: {'Omega_m': 0.2946949033424985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,462 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45637304553736}
 2023-07-02 10:24:24,462 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0205016
 2023-07-02 10:24:24,464 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,464 [mcmc] New sample, #142:
   Omega_m:0.3205664
 2023-07-02 10:24:24,464 [model] Posterior to be computed for parameters {'Omega_m': 0.5216382668281213}
 2023-07-02 10:24:24,464 [prior] Evaluating prior at array([0.52163827])
 2023-07-02 10:24:24,464 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,464 [model] Got input parameters: {'Omega_m': 0.5216382668281213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,464 [classy] Got parameters {'Omega_m': 0.5216382668281213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,464 [classy] Computing new state
 2023-07-02 10:24:24,464 [classy] Setting parameters: {'Omega_m': 0.5216382668281213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.65480282168627}
 2023-07-02 10:24:24,510 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.73086
 2023-07-02 10:24:24,512 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,512 [mcmc] New sample, #143:
   Omega_m:0.2946949
 2023-07-02 10:24:24,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3041145005943974}
 2023-07-02 10:24:24,512 [prior] Evaluating prior at array([0.3041145])
 2023-07-02 10:24:24,512 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,513 [model] Got input parameters: {'Omega_m': 0.3041145005943974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,513 [classy] Got parameters {'Omega_m': 0.3041145005943974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,513 [classy] Computing new state
 2023-07-02 10:24:24,513 [classy] Setting parameters: {'Omega_m': 0.3041145005943974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2793371657879}
 2023-07-02 10:24:24,559 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,561 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00458897
 2023-07-02 10:24:24,561 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,561 [mcmc] New sample, #144:
   Omega_m:0.5216383
 2023-07-02 10:24:24,561 [model] Posterior to be computed for parameters {'Omega_m': 0.5066056641309248}
 2023-07-02 10:24:24,561 [prior] Evaluating prior at array([0.50660566])
 2023-07-02 10:24:24,561 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,561 [model] Got input parameters: {'Omega_m': 0.5066056641309248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,561 [classy] Got parameters {'Omega_m': 0.5066056641309248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,561 [classy] Computing new state
 2023-07-02 10:24:24,561 [classy] Setting parameters: {'Omega_m': 0.5066056641309248, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.7809373182323}
 2023-07-02 10:24:24,608 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.532
 2023-07-02 10:24:24,610 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,610 [model] Posterior to be computed for parameters {'Omega_m': 0.5944673860934429}
 2023-07-02 10:24:24,610 [prior] Evaluating prior at array([0.59446739])
 2023-07-02 10:24:24,610 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,610 [model] Got input parameters: {'Omega_m': 0.5944673860934429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,610 [classy] Got parameters {'Omega_m': 0.5944673860934429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,610 [classy] Computing new state
 2023-07-02 10:24:24,610 [classy] Setting parameters: {'Omega_m': 0.5944673860934429, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.63127732817031}
 2023-07-02 10:24:24,658 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,660 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.77852
 2023-07-02 10:24:24,660 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,660 [model] Posterior to be computed for parameters {'Omega_m': -0.01490252417513166}
 2023-07-02 10:24:24,660 [prior] Evaluating prior at array([-0.01490252])
 2023-07-02 10:24:24,660 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:24,660 [model] Posterior to be computed for parameters {'Omega_m': 0.39423406197239275}
 2023-07-02 10:24:24,660 [prior] Evaluating prior at array([0.39423406])
 2023-07-02 10:24:24,660 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,660 [model] Got input parameters: {'Omega_m': 0.39423406197239275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,660 [classy] Got parameters {'Omega_m': 0.39423406197239275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,660 [classy] Computing new state
 2023-07-02 10:24:24,660 [classy] Setting parameters: {'Omega_m': 0.39423406197239275, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.42833281259124}
 2023-07-02 10:24:24,708 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,709 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.339453
 2023-07-02 10:24:24,709 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,709 [mcmc] New sample, #145:
   Omega_m:0.3041145
 2023-07-02 10:24:24,709 [model] Posterior to be computed for parameters {'Omega_m': 0.9067531437355372}
 2023-07-02 10:24:24,710 [prior] Evaluating prior at array([0.90675314])
 2023-07-02 10:24:24,710 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,710 [model] Got input parameters: {'Omega_m': 0.9067531437355372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,710 [classy] Got parameters {'Omega_m': 0.9067531437355372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,710 [classy] Computing new state
 2023-07-02 10:24:24,710 [classy] Setting parameters: {'Omega_m': 0.9067531437355372, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.69436053260269}
 2023-07-02 10:24:24,756 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.99539
 2023-07-02 10:24:24,758 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,758 [model] Posterior to be computed for parameters {'Omega_m': 0.19156367502989086}
 2023-07-02 10:24:24,758 [prior] Evaluating prior at array([0.19156368])
 2023-07-02 10:24:24,758 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,758 [model] Got input parameters: {'Omega_m': 0.19156367502989086, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,758 [classy] Got parameters {'Omega_m': 0.19156367502989086, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,758 [classy] Computing new state
 2023-07-02 10:24:24,758 [classy] Setting parameters: {'Omega_m': 0.19156367502989086, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.96654510076615}
 2023-07-02 10:24:24,804 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.26399
 2023-07-02 10:24:24,806 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,807 [mcmc] New sample, #146:
   Omega_m:0.3942341
 2023-07-02 10:24:24,807 [model] Posterior to be computed for parameters {'Omega_m': 0.12725039500568475}
 2023-07-02 10:24:24,807 [prior] Evaluating prior at array([0.1272504])
 2023-07-02 10:24:24,807 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,807 [model] Got input parameters: {'Omega_m': 0.12725039500568475, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,807 [classy] Got parameters {'Omega_m': 0.12725039500568475, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,807 [classy] Computing new state
 2023-07-02 10:24:24,807 [classy] Setting parameters: {'Omega_m': 0.12725039500568475, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 178.22844003094588}
 2023-07-02 10:24:24,853 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,856 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.73424
 2023-07-02 10:24:24,856 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,856 [model] Posterior to be computed for parameters {'Omega_m': 0.18351084657607714}
 2023-07-02 10:24:24,856 [prior] Evaluating prior at array([0.18351085])
 2023-07-02 10:24:24,856 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,856 [model] Got input parameters: {'Omega_m': 0.18351084657607714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,856 [classy] Got parameters {'Omega_m': 0.18351084657607714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,856 [classy] Computing new state
 2023-07-02 10:24:24,856 [classy] Setting parameters: {'Omega_m': 0.18351084657607714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,903 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.43592799283766}
 2023-07-02 10:24:24,903 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.47664
 2023-07-02 10:24:24,906 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,906 [mcmc] New sample, #147:
   Omega_m:0.1915637
 2023-07-02 10:24:24,906 [model] Posterior to be computed for parameters {'Omega_m': 0.06313668392974646}
 2023-07-02 10:24:24,906 [prior] Evaluating prior at array([0.06313668])
 2023-07-02 10:24:24,906 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:24,907 [model] Posterior to be computed for parameters {'Omega_m': 0.3200165709482702}
 2023-07-02 10:24:24,907 [prior] Evaluating prior at array([0.32001657])
 2023-07-02 10:24:24,907 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,907 [model] Got input parameters: {'Omega_m': 0.3200165709482702, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,907 [classy] Got parameters {'Omega_m': 0.3200165709482702, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,907 [classy] Computing new state
 2023-07-02 10:24:24,907 [classy] Setting parameters: {'Omega_m': 0.3200165709482702, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:24,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36334634414226}
 2023-07-02 10:24:24,953 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:24,956 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00361727
 2023-07-02 10:24:24,956 [model] Computed derived parameters: {}
 2023-07-02 10:24:24,956 [mcmc] New sample, #148:
   Omega_m:0.1835108
 2023-07-02 10:24:24,956 [model] Posterior to be computed for parameters {'Omega_m': 0.30374436317079995}
 2023-07-02 10:24:24,956 [prior] Evaluating prior at array([0.30374436])
 2023-07-02 10:24:24,956 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:24,956 [model] Got input parameters: {'Omega_m': 0.30374436317079995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,956 [classy] Got parameters {'Omega_m': 0.30374436317079995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:24,956 [classy] Computing new state
 2023-07-02 10:24:24,956 [classy] Setting parameters: {'Omega_m': 0.30374436317079995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.32497992374226}
 2023-07-02 10:24:25,007 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,008 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00499001
 2023-07-02 10:24:25,008 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,008 [mcmc] New sample, #149:
   Omega_m:0.3200166
 2023-07-02 10:24:25,008 [model] Posterior to be computed for parameters {'Omega_m': -0.1262566739697653}
 2023-07-02 10:24:25,008 [prior] Evaluating prior at array([-0.12625667])
 2023-07-02 10:24:25,009 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:25,009 [model] Posterior to be computed for parameters {'Omega_m': 0.6584618252520076}
 2023-07-02 10:24:25,009 [prior] Evaluating prior at array([0.65846183])
 2023-07-02 10:24:25,009 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,009 [model] Got input parameters: {'Omega_m': 0.6584618252520076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,009 [classy] Got parameters {'Omega_m': 0.6584618252520076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,009 [classy] Computing new state
 2023-07-02 10:24:25,009 [classy] Setting parameters: {'Omega_m': 0.6584618252520076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.7211717728523}
 2023-07-02 10:24:25,057 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.78249
 2023-07-02 10:24:25,059 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,059 [model] Posterior to be computed for parameters {'Omega_m': 0.1501468984841768}
 2023-07-02 10:24:25,059 [prior] Evaluating prior at array([0.1501469])
 2023-07-02 10:24:25,059 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,059 [model] Got input parameters: {'Omega_m': 0.1501468984841768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,059 [classy] Got parameters {'Omega_m': 0.1501468984841768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,059 [classy] Computing new state
 2023-07-02 10:24:25,059 [classy] Setting parameters: {'Omega_m': 0.1501468984841768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.07108984499627}
 2023-07-02 10:24:25,107 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62888
 2023-07-02 10:24:25,108 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,108 [model] Posterior to be computed for parameters {'Omega_m': 0.12230486797178103}
 2023-07-02 10:24:25,109 [prior] Evaluating prior at array([0.12230487])
 2023-07-02 10:24:25,109 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,109 [model] Got input parameters: {'Omega_m': 0.12230486797178103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,109 [classy] Got parameters {'Omega_m': 0.12230486797178103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,109 [classy] Computing new state
 2023-07-02 10:24:25,109 [classy] Setting parameters: {'Omega_m': 0.12230486797178103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.4186178433223}
 2023-07-02 10:24:25,156 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.01451
 2023-07-02 10:24:25,158 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,158 [model] Posterior to be computed for parameters {'Omega_m': 0.5536096831927042}
 2023-07-02 10:24:25,158 [prior] Evaluating prior at array([0.55360968])
 2023-07-02 10:24:25,158 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,158 [model] Got input parameters: {'Omega_m': 0.5536096831927042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,159 [classy] Got parameters {'Omega_m': 0.5536096831927042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,159 [classy] Computing new state
 2023-07-02 10:24:25,159 [classy] Setting parameters: {'Omega_m': 0.5536096831927042, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.36579661687814}
 2023-07-02 10:24:25,206 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,208 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.17529
 2023-07-02 10:24:25,208 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,208 [model] Posterior to be computed for parameters {'Omega_m': 0.30221631904211776}
 2023-07-02 10:24:25,208 [prior] Evaluating prior at array([0.30221632])
 2023-07-02 10:24:25,208 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,208 [model] Got input parameters: {'Omega_m': 0.30221631904211776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,208 [classy] Got parameters {'Omega_m': 0.30221631904211776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,208 [classy] Computing new state
 2023-07-02 10:24:25,208 [classy] Setting parameters: {'Omega_m': 0.30221631904211776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,255 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.51391658649328}
 2023-07-02 10:24:25,255 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,257 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00683591
 2023-07-02 10:24:25,257 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,257 [mcmc] New sample, #150:
   Omega_m:0.3037444
 2023-07-02 10:24:25,258 [model] Posterior to be computed for parameters {'Omega_m': -0.13618722146547912}
 2023-07-02 10:24:25,258 [prior] Evaluating prior at array([-0.13618722])
 2023-07-02 10:24:25,258 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:25,258 [model] Posterior to be computed for parameters {'Omega_m': 0.3082574811849115}
 2023-07-02 10:24:25,258 [prior] Evaluating prior at array([0.30825748])
 2023-07-02 10:24:25,258 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,258 [model] Got input parameters: {'Omega_m': 0.3082574811849115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,258 [classy] Got parameters {'Omega_m': 0.3082574811849115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,258 [classy] Computing new state
 2023-07-02 10:24:25,258 [classy] Setting parameters: {'Omega_m': 0.3082574811849115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77177263957392}
 2023-07-02 10:24:25,304 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,307 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00130949
 2023-07-02 10:24:25,307 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,307 [mcmc] New sample, #151:
   Omega_m:0.3022163
 2023-07-02 10:24:25,307 [model] Posterior to be computed for parameters {'Omega_m': 0.3724394958323314}
 2023-07-02 10:24:25,307 [prior] Evaluating prior at array([0.3724395])
 2023-07-02 10:24:25,307 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,307 [model] Got input parameters: {'Omega_m': 0.3724394958323314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,307 [classy] Got parameters {'Omega_m': 0.3724394958323314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,308 [classy] Computing new state
 2023-07-02 10:24:25,308 [classy] Setting parameters: {'Omega_m': 0.3724394958323314, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.6041382108848}
 2023-07-02 10:24:25,354 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.191603
 2023-07-02 10:24:25,357 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,357 [mcmc] New sample, #152:
   Omega_m:0.3082575
 2023-07-02 10:24:25,357 [model] Posterior to be computed for parameters {'Omega_m': 0.3083756291470865}
 2023-07-02 10:24:25,357 [prior] Evaluating prior at array([0.30837563])
 2023-07-02 10:24:25,357 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,357 [model] Got input parameters: {'Omega_m': 0.3083756291470865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,357 [classy] Got parameters {'Omega_m': 0.3083756291470865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,357 [classy] Computing new state
 2023-07-02 10:24:25,357 [classy] Setting parameters: {'Omega_m': 0.3083756291470865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75738625562877}
 2023-07-02 10:24:25,403 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00124815
 2023-07-02 10:24:25,405 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,405 [mcmc] New sample, #153:
   Omega_m:0.3724395
 2023-07-02 10:24:25,406 [model] Posterior to be computed for parameters {'Omega_m': 0.35319819954668974}
 2023-07-02 10:24:25,406 [prior] Evaluating prior at array([0.3531982])
 2023-07-02 10:24:25,406 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,406 [model] Got input parameters: {'Omega_m': 0.35319819954668974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,406 [classy] Got parameters {'Omega_m': 0.35319819954668974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,406 [classy] Computing new state
 2023-07-02 10:24:25,406 [classy] Setting parameters: {'Omega_m': 0.35319819954668974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.62629260300002}
 2023-07-02 10:24:25,452 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.092403
 2023-07-02 10:24:25,455 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,455 [mcmc] New sample, #154:
   Omega_m:0.3083756
 2023-07-02 10:24:25,455 [model] Posterior to be computed for parameters {'Omega_m': 0.5005742682134801}
 2023-07-02 10:24:25,455 [prior] Evaluating prior at array([0.50057427])
 2023-07-02 10:24:25,455 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,455 [model] Got input parameters: {'Omega_m': 0.5005742682134801, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,455 [classy] Got parameters {'Omega_m': 0.5005742682134801, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,455 [classy] Computing new state
 2023-07-02 10:24:25,455 [classy] Setting parameters: {'Omega_m': 0.5005742682134801, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,502 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.24229745316117}
 2023-07-02 10:24:25,502 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,504 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45425
 2023-07-02 10:24:25,504 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,504 [mcmc] New sample, #155:
   Omega_m:0.3531982
 2023-07-02 10:24:25,505 [model] Posterior to be computed for parameters {'Omega_m': 0.5289638033121735}
 2023-07-02 10:24:25,505 [prior] Evaluating prior at array([0.5289638])
 2023-07-02 10:24:25,505 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,505 [model] Got input parameters: {'Omega_m': 0.5289638033121735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,505 [classy] Got parameters {'Omega_m': 0.5289638033121735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,505 [classy] Computing new state
 2023-07-02 10:24:25,505 [classy] Setting parameters: {'Omega_m': 0.5289638033121735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.11788462815247}
 2023-07-02 10:24:25,552 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,555 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.83025
 2023-07-02 10:24:25,555 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,555 [mcmc] New sample, #156:
   Omega_m:0.5005743
 2023-07-02 10:24:25,555 [model] Posterior to be computed for parameters {'Omega_m': 0.533166710063196}
 2023-07-02 10:24:25,555 [prior] Evaluating prior at array([0.53316671])
 2023-07-02 10:24:25,555 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,555 [model] Got input parameters: {'Omega_m': 0.533166710063196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,555 [classy] Got parameters {'Omega_m': 0.533166710063196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,555 [classy] Computing new state
 2023-07-02 10:24:25,555 [classy] Setting parameters: {'Omega_m': 0.533166710063196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.81327403852498}
 2023-07-02 10:24:25,602 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,605 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.88794
 2023-07-02 10:24:25,605 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,605 [mcmc] New sample, #157:
   Omega_m:0.5289638
 2023-07-02 10:24:25,605 [model] Posterior to be computed for parameters {'Omega_m': 0.6817820141490225}
 2023-07-02 10:24:25,605 [prior] Evaluating prior at array([0.68178201])
 2023-07-02 10:24:25,606 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,606 [model] Got input parameters: {'Omega_m': 0.6817820141490225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,606 [classy] Got parameters {'Omega_m': 0.6817820141490225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,606 [classy] Computing new state
 2023-07-02 10:24:25,606 [classy] Setting parameters: {'Omega_m': 0.6817820141490225, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.39585065339337}
 2023-07-02 10:24:25,651 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.16174
 2023-07-02 10:24:25,653 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,654 [model] Posterior to be computed for parameters {'Omega_m': 0.679562879559181}
 2023-07-02 10:24:25,654 [prior] Evaluating prior at array([0.67956288])
 2023-07-02 10:24:25,654 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,654 [model] Got input parameters: {'Omega_m': 0.679562879559181, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,654 [classy] Got parameters {'Omega_m': 0.679562879559181, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,654 [classy] Computing new state
 2023-07-02 10:24:25,654 [classy] Setting parameters: {'Omega_m': 0.679562879559181, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.51986375578694}
 2023-07-02 10:24:25,701 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,703 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.1254
 2023-07-02 10:24:25,703 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,703 [model] Posterior to be computed for parameters {'Omega_m': 0.5167059602785964}
 2023-07-02 10:24:25,703 [prior] Evaluating prior at array([0.51670596])
 2023-07-02 10:24:25,703 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,703 [model] Got input parameters: {'Omega_m': 0.5167059602785964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,703 [classy] Got parameters {'Omega_m': 0.5167059602785964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,703 [classy] Computing new state
 2023-07-02 10:24:25,703 [classy] Setting parameters: {'Omega_m': 0.5167059602785964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,749 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.02062945909347}
 2023-07-02 10:24:25,749 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,751 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.66484
 2023-07-02 10:24:25,751 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,752 [mcmc] New sample, #158:
   Omega_m:0.5331667
 2023-07-02 10:24:25,752 [model] Posterior to be computed for parameters {'Omega_m': 0.49208229611278004}
 2023-07-02 10:24:25,752 [prior] Evaluating prior at array([0.4920823])
 2023-07-02 10:24:25,752 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,752 [model] Got input parameters: {'Omega_m': 0.49208229611278004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,752 [classy] Got parameters {'Omega_m': 0.49208229611278004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,752 [classy] Computing new state
 2023-07-02 10:24:25,752 [classy] Setting parameters: {'Omega_m': 0.49208229611278004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,798 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.90142308539504}
 2023-07-02 10:24:25,798 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,800 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.34689
 2023-07-02 10:24:25,800 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,800 [mcmc] New sample, #159:
   Omega_m:0.516706
 2023-07-02 10:24:25,800 [model] Posterior to be computed for parameters {'Omega_m': 0.6430921747357369}
 2023-07-02 10:24:25,800 [prior] Evaluating prior at array([0.64309217])
 2023-07-02 10:24:25,801 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,801 [model] Got input parameters: {'Omega_m': 0.6430921747357369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,801 [classy] Got parameters {'Omega_m': 0.6430921747357369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,801 [classy] Computing new state
 2023-07-02 10:24:25,801 [classy] Setting parameters: {'Omega_m': 0.6430921747357369, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.62234724441264}
 2023-07-02 10:24:25,846 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.53602
 2023-07-02 10:24:25,848 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,848 [model] Posterior to be computed for parameters {'Omega_m': 0.5320469735180322}
 2023-07-02 10:24:25,848 [prior] Evaluating prior at array([0.53204697])
 2023-07-02 10:24:25,848 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,848 [model] Got input parameters: {'Omega_m': 0.5320469735180322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,848 [classy] Got parameters {'Omega_m': 0.5320469735180322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,848 [classy] Computing new state
 2023-07-02 10:24:25,848 [classy] Setting parameters: {'Omega_m': 0.5320469735180322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,895 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.89418917242322}
 2023-07-02 10:24:25,895 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,897 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.87252
 2023-07-02 10:24:25,897 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,897 [mcmc] New sample, #160:
   Omega_m:0.4920823
 2023-07-02 10:24:25,897 [mcmc] Learn + convergence test @ 160 samples accepted.
 2023-07-02 10:24:25,897 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:25,902 [mcmc]  - Acceptance rate: 0.670
 2023-07-02 10:24:25,902 [mcmc]  - Condition number = 1
 2023-07-02 10:24:25,902 [mcmc]  - Eigenvalues = array([0.05632543])
 2023-07-02 10:24:25,902 [mcmc]  - Convergence of means: R-1 = 0.056325 after 128 accepted steps
 2023-07-02 10:24:25,902 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:25,902 [mcmc] array([[0.01093334]])
 2023-07-02 10:24:25,913 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:25,913 [model] Posterior to be computed for parameters {'Omega_m': 0.4774438593566598}
 2023-07-02 10:24:25,913 [prior] Evaluating prior at array([0.47744386])
 2023-07-02 10:24:25,913 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,913 [model] Got input parameters: {'Omega_m': 0.4774438593566598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,913 [classy] Got parameters {'Omega_m': 0.4774438593566598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,913 [classy] Computing new state
 2023-07-02 10:24:25,913 [classy] Setting parameters: {'Omega_m': 0.4774438593566598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:25,960 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.0648721847981}
 2023-07-02 10:24:25,960 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:25,962 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.16796
 2023-07-02 10:24:25,962 [model] Computed derived parameters: {}
 2023-07-02 10:24:25,962 [mcmc] New sample, #161:
   Omega_m:0.532047
 2023-07-02 10:24:25,962 [model] Posterior to be computed for parameters {'Omega_m': 0.5738120430032648}
 2023-07-02 10:24:25,962 [prior] Evaluating prior at array([0.57381204])
 2023-07-02 10:24:25,962 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:25,962 [model] Got input parameters: {'Omega_m': 0.5738120430032648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,962 [classy] Got parameters {'Omega_m': 0.5738120430032648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:25,962 [classy] Computing new state
 2023-07-02 10:24:25,962 [classy] Setting parameters: {'Omega_m': 0.5738120430032648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,009 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.98843837033732}
 2023-07-02 10:24:26,009 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,011 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.46916
 2023-07-02 10:24:26,011 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,011 [model] Posterior to be computed for parameters {'Omega_m': 0.47314949572939563}
 2023-07-02 10:24:26,011 [prior] Evaluating prior at array([0.4731495])
 2023-07-02 10:24:26,011 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,011 [model] Got input parameters: {'Omega_m': 0.47314949572939563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,011 [classy] Got parameters {'Omega_m': 0.47314949572939563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,011 [classy] Computing new state
 2023-07-02 10:24:26,011 [classy] Setting parameters: {'Omega_m': 0.47314949572939563, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.41293811896026}
 2023-07-02 10:24:26,059 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,061 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.11704
 2023-07-02 10:24:26,061 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,061 [mcmc] New sample, #162:
   Omega_m:0.4774439
 2023-07-02 10:24:26,061 [model] Posterior to be computed for parameters {'Omega_m': 0.7605905762513676}
 2023-07-02 10:24:26,061 [prior] Evaluating prior at array([0.76059058])
 2023-07-02 10:24:26,061 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,061 [model] Got input parameters: {'Omega_m': 0.7605905762513676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,061 [classy] Got parameters {'Omega_m': 0.7605905762513676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,061 [classy] Computing new state
 2023-07-02 10:24:26,061 [classy] Setting parameters: {'Omega_m': 0.7605905762513676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.25436525207276}
 2023-07-02 10:24:26,105 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.47878
 2023-07-02 10:24:26,108 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,108 [model] Posterior to be computed for parameters {'Omega_m': 0.7460764282280585}
 2023-07-02 10:24:26,108 [prior] Evaluating prior at array([0.74607643])
 2023-07-02 10:24:26,109 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,109 [model] Got input parameters: {'Omega_m': 0.7460764282280585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,109 [classy] Got parameters {'Omega_m': 0.7460764282280585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,109 [classy] Computing new state
 2023-07-02 10:24:26,109 [classy] Setting parameters: {'Omega_m': 0.7460764282280585, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.98093873759065}
 2023-07-02 10:24:26,153 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.23299
 2023-07-02 10:24:26,155 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,155 [model] Posterior to be computed for parameters {'Omega_m': 0.5845237762772991}
 2023-07-02 10:24:26,155 [prior] Evaluating prior at array([0.58452378])
 2023-07-02 10:24:26,155 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,155 [model] Got input parameters: {'Omega_m': 0.5845237762772991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,155 [classy] Got parameters {'Omega_m': 0.5845237762772991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,155 [classy] Computing new state
 2023-07-02 10:24:26,155 [classy] Setting parameters: {'Omega_m': 0.5845237762772991, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.27836859667431}
 2023-07-02 10:24:26,202 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,203 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62855
 2023-07-02 10:24:26,204 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,204 [model] Posterior to be computed for parameters {'Omega_m': 0.06924054558443976}
 2023-07-02 10:24:26,204 [prior] Evaluating prior at array([0.06924055])
 2023-07-02 10:24:26,204 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:26,204 [model] Posterior to be computed for parameters {'Omega_m': 0.5985162204616779}
 2023-07-02 10:24:26,204 [prior] Evaluating prior at array([0.59851622])
 2023-07-02 10:24:26,204 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,204 [model] Got input parameters: {'Omega_m': 0.5985162204616779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,204 [classy] Got parameters {'Omega_m': 0.5985162204616779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,204 [classy] Computing new state
 2023-07-02 10:24:26,204 [classy] Setting parameters: {'Omega_m': 0.5985162204616779, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.37101734279705}
 2023-07-02 10:24:26,251 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.84012
 2023-07-02 10:24:26,253 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,253 [model] Posterior to be computed for parameters {'Omega_m': 0.2775269429012641}
 2023-07-02 10:24:26,253 [prior] Evaluating prior at array([0.27752694])
 2023-07-02 10:24:26,254 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,254 [model] Got input parameters: {'Omega_m': 0.2775269429012641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,254 [classy] Got parameters {'Omega_m': 0.2775269429012641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,254 [classy] Computing new state
 2023-07-02 10:24:26,254 [classy] Setting parameters: {'Omega_m': 0.2775269429012641, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.6883259660247}
 2023-07-02 10:24:26,301 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,303 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0821969
 2023-07-02 10:24:26,303 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,303 [mcmc] New sample, #163:
   Omega_m:0.4731495
 2023-07-02 10:24:26,304 [model] Posterior to be computed for parameters {'Omega_m': 0.16395279632349347}
 2023-07-02 10:24:26,304 [prior] Evaluating prior at array([0.1639528])
 2023-07-02 10:24:26,304 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,304 [model] Got input parameters: {'Omega_m': 0.16395279632349347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,304 [classy] Got parameters {'Omega_m': 0.16395279632349347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,304 [classy] Computing new state
 2023-07-02 10:24:26,304 [classy] Setting parameters: {'Omega_m': 0.16395279632349347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.2110087133082}
 2023-07-02 10:24:26,351 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,353 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.09419
 2023-07-02 10:24:26,353 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,353 [model] Posterior to be computed for parameters {'Omega_m': 0.2100183328556683}
 2023-07-02 10:24:26,353 [prior] Evaluating prior at array([0.21001833])
 2023-07-02 10:24:26,353 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,353 [model] Got input parameters: {'Omega_m': 0.2100183328556683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,354 [classy] Got parameters {'Omega_m': 0.2100183328556683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,354 [classy] Computing new state
 2023-07-02 10:24:26,354 [classy] Setting parameters: {'Omega_m': 0.2100183328556683, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 161.76652434581797}
 2023-07-02 10:24:26,400 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,402 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.855817
 2023-07-02 10:24:26,402 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,402 [mcmc] New sample, #164:
   Omega_m:0.2775269
 2023-07-02 10:24:26,402 [model] Posterior to be computed for parameters {'Omega_m': 0.35683882831770697}
 2023-07-02 10:24:26,402 [prior] Evaluating prior at array([0.35683883])
 2023-07-02 10:24:26,403 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,403 [model] Got input parameters: {'Omega_m': 0.35683882831770697, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,403 [classy] Got parameters {'Omega_m': 0.35683882831770697, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,403 [classy] Computing new state
 2023-07-02 10:24:26,403 [classy] Setting parameters: {'Omega_m': 0.35683882831770697, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.2359771346703}
 2023-07-02 10:24:26,450 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.108718
 2023-07-02 10:24:26,452 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,452 [mcmc] New sample, #165:
   Omega_m:0.2100183
 2023-07-02 10:24:26,452 [model] Posterior to be computed for parameters {'Omega_m': 0.27206426005905776}
 2023-07-02 10:24:26,452 [prior] Evaluating prior at array([0.27206426])
 2023-07-02 10:24:26,452 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,452 [model] Got input parameters: {'Omega_m': 0.27206426005905776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,452 [classy] Got parameters {'Omega_m': 0.27206426005905776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,452 [classy] Computing new state
 2023-07-02 10:24:26,452 [classy] Setting parameters: {'Omega_m': 0.27206426005905776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.42336273891743}
 2023-07-02 10:24:26,504 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111442
 2023-07-02 10:24:26,506 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,506 [mcmc] New sample, #166:
   Omega_m:0.3568388
 2023-07-02 10:24:26,506 [model] Posterior to be computed for parameters {'Omega_m': 0.14282092452913356}
 2023-07-02 10:24:26,506 [prior] Evaluating prior at array([0.14282092])
 2023-07-02 10:24:26,506 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,506 [model] Got input parameters: {'Omega_m': 0.14282092452913356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,506 [classy] Got parameters {'Omega_m': 0.14282092452913356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,507 [classy] Computing new state
 2023-07-02 10:24:26,507 [classy] Setting parameters: {'Omega_m': 0.14282092452913356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.66174457862428}
 2023-07-02 10:24:26,557 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,559 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.95065
 2023-07-02 10:24:26,559 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,559 [model] Posterior to be computed for parameters {'Omega_m': -0.26293376211527425}
 2023-07-02 10:24:26,559 [prior] Evaluating prior at array([-0.26293376])
 2023-07-02 10:24:26,560 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:26,560 [model] Posterior to be computed for parameters {'Omega_m': 1.1045725082869593}
 2023-07-02 10:24:26,560 [prior] Evaluating prior at array([1.10457251])
 2023-07-02 10:24:26,560 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:26,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3884939697145821}
 2023-07-02 10:24:26,560 [prior] Evaluating prior at array([0.38849397])
 2023-07-02 10:24:26,560 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,560 [model] Got input parameters: {'Omega_m': 0.3884939697145821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,560 [classy] Got parameters {'Omega_m': 0.3884939697145821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,560 [classy] Computing new state
 2023-07-02 10:24:26,560 [classy] Setting parameters: {'Omega_m': 0.3884939697145821, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.990168970512}
 2023-07-02 10:24:26,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.297146
 2023-07-02 10:24:26,613 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,613 [model] Posterior to be computed for parameters {'Omega_m': 0.25568947353622556}
 2023-07-02 10:24:26,613 [prior] Evaluating prior at array([0.25568947])
 2023-07-02 10:24:26,613 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,613 [model] Got input parameters: {'Omega_m': 0.25568947353622556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,613 [classy] Got parameters {'Omega_m': 0.25568947353622556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,613 [classy] Computing new state
 2023-07-02 10:24:26,613 [classy] Setting parameters: {'Omega_m': 0.25568947353622556, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.70412042524313}
 2023-07-02 10:24:26,664 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,666 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.229941
 2023-07-02 10:24:26,667 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,667 [mcmc] New sample, #167:
   Omega_m:0.2720643
 2023-07-02 10:24:26,667 [model] Posterior to be computed for parameters {'Omega_m': -0.12012007550950393}
 2023-07-02 10:24:26,667 [prior] Evaluating prior at array([-0.12012008])
 2023-07-02 10:24:26,667 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:26,667 [model] Posterior to be computed for parameters {'Omega_m': 0.047758830547878856}
 2023-07-02 10:24:26,667 [prior] Evaluating prior at array([0.04775883])
 2023-07-02 10:24:26,667 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:26,667 [model] Posterior to be computed for parameters {'Omega_m': 0.1424692906878532}
 2023-07-02 10:24:26,667 [prior] Evaluating prior at array([0.14246929])
 2023-07-02 10:24:26,667 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,667 [model] Got input parameters: {'Omega_m': 0.1424692906878532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,667 [classy] Got parameters {'Omega_m': 0.1424692906878532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,667 [classy] Computing new state
 2023-07-02 10:24:26,668 [classy] Setting parameters: {'Omega_m': 0.1424692906878532, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,717 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.73943969517296}
 2023-07-02 10:24:26,717 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,719 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.96681
 2023-07-02 10:24:26,719 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,719 [model] Posterior to be computed for parameters {'Omega_m': 0.43445417868177993}
 2023-07-02 10:24:26,719 [prior] Evaluating prior at array([0.43445418])
 2023-07-02 10:24:26,719 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,719 [model] Got input parameters: {'Omega_m': 0.43445417868177993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,719 [classy] Got parameters {'Omega_m': 0.43445417868177993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,719 [classy] Computing new state
 2023-07-02 10:24:26,719 [classy] Setting parameters: {'Omega_m': 0.43445417868177993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.69783423555538}
 2023-07-02 10:24:26,767 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.694648
 2023-07-02 10:24:26,769 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,769 [model] Posterior to be computed for parameters {'Omega_m': -0.02269367400022987}
 2023-07-02 10:24:26,769 [prior] Evaluating prior at array([-0.02269367])
 2023-07-02 10:24:26,769 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:26,769 [model] Posterior to be computed for parameters {'Omega_m': 0.5685277025739688}
 2023-07-02 10:24:26,769 [prior] Evaluating prior at array([0.5685277])
 2023-07-02 10:24:26,770 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,770 [model] Got input parameters: {'Omega_m': 0.5685277025739688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,770 [classy] Got parameters {'Omega_m': 0.5685277025739688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,770 [classy] Computing new state
 2023-07-02 10:24:26,770 [classy] Setting parameters: {'Omega_m': 0.5685277025739688, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,817 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.34379622318833}
 2023-07-02 10:24:26,817 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,819 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.39142
 2023-07-02 10:24:26,819 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,819 [model] Posterior to be computed for parameters {'Omega_m': 0.8050832595443578}
 2023-07-02 10:24:26,819 [prior] Evaluating prior at array([0.80508326])
 2023-07-02 10:24:26,819 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,819 [model] Got input parameters: {'Omega_m': 0.8050832595443578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,819 [classy] Got parameters {'Omega_m': 0.8050832595443578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,819 [classy] Computing new state
 2023-07-02 10:24:26,819 [classy] Setting parameters: {'Omega_m': 0.8050832595443578, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.11855680193099}
 2023-07-02 10:24:26,864 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.23864
 2023-07-02 10:24:26,866 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,866 [model] Posterior to be computed for parameters {'Omega_m': 0.6927934489172098}
 2023-07-02 10:24:26,866 [prior] Evaluating prior at array([0.69279345])
 2023-07-02 10:24:26,867 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,867 [model] Got input parameters: {'Omega_m': 0.6927934489172098, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,867 [classy] Got parameters {'Omega_m': 0.6927934489172098, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,867 [classy] Computing new state
 2023-07-02 10:24:26,867 [classy] Setting parameters: {'Omega_m': 0.6927934489172098, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.78687977312518}
 2023-07-02 10:24:26,912 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,914 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.34276
 2023-07-02 10:24:26,914 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,914 [model] Posterior to be computed for parameters {'Omega_m': 0.23325763467043187}
 2023-07-02 10:24:26,914 [prior] Evaluating prior at array([0.23325763])
 2023-07-02 10:24:26,915 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,915 [model] Got input parameters: {'Omega_m': 0.23325763467043187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,915 [classy] Got parameters {'Omega_m': 0.23325763467043187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,915 [classy] Computing new state
 2023-07-02 10:24:26,915 [classy] Setting parameters: {'Omega_m': 0.23325763467043187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:26,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.03360777233948}
 2023-07-02 10:24:26,961 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:26,963 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.47697
 2023-07-02 10:24:26,963 [model] Computed derived parameters: {}
 2023-07-02 10:24:26,963 [mcmc] New sample, #168:
   Omega_m:0.2556895
 2023-07-02 10:24:26,963 [model] Posterior to be computed for parameters {'Omega_m': 0.1422117643113403}
 2023-07-02 10:24:26,963 [prior] Evaluating prior at array([0.14221176])
 2023-07-02 10:24:26,963 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:26,963 [model] Got input parameters: {'Omega_m': 0.1422117643113403, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,963 [classy] Got parameters {'Omega_m': 0.1422117643113403, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:26,963 [classy] Computing new state
 2023-07-02 10:24:26,963 [classy] Setting parameters: {'Omega_m': 0.1422117643113403, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.79641830869977}
 2023-07-02 10:24:27,011 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,014 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.97869
 2023-07-02 10:24:27,014 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,014 [model] Posterior to be computed for parameters {'Omega_m': -0.009196565651528071}
 2023-07-02 10:24:27,015 [prior] Evaluating prior at array([-0.00919657])
 2023-07-02 10:24:27,015 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,015 [model] Posterior to be computed for parameters {'Omega_m': 0.534066959013109}
 2023-07-02 10:24:27,015 [prior] Evaluating prior at array([0.53406696])
 2023-07-02 10:24:27,015 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,015 [model] Got input parameters: {'Omega_m': 0.534066959013109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,015 [classy] Got parameters {'Omega_m': 0.534066959013109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,015 [classy] Computing new state
 2023-07-02 10:24:27,015 [classy] Setting parameters: {'Omega_m': 0.534066959013109, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,071 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.74834780876553}
 2023-07-02 10:24:27,071 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,074 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.90036
 2023-07-02 10:24:27,074 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,074 [mcmc] New sample, #169:
   Omega_m:0.2332576
 2023-07-02 10:24:27,074 [model] Posterior to be computed for parameters {'Omega_m': 0.10478821118155307}
 2023-07-02 10:24:27,074 [prior] Evaluating prior at array([0.10478821])
 2023-07-02 10:24:27,074 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,074 [model] Got input parameters: {'Omega_m': 0.10478821118155307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,074 [classy] Got parameters {'Omega_m': 0.10478821118155307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,074 [classy] Computing new state
 2023-07-02 10:24:27,074 [classy] Setting parameters: {'Omega_m': 0.10478821118155307, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,119 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.88359980630298}
 2023-07-02 10:24:27,119 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,121 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.14778
 2023-07-02 10:24:27,121 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,121 [model] Posterior to be computed for parameters {'Omega_m': 0.550668738047621}
 2023-07-02 10:24:27,122 [prior] Evaluating prior at array([0.55066874])
 2023-07-02 10:24:27,122 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,122 [model] Got input parameters: {'Omega_m': 0.550668738047621, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,122 [classy] Got parameters {'Omega_m': 0.550668738047621, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,122 [classy] Computing new state
 2023-07-02 10:24:27,122 [classy] Setting parameters: {'Omega_m': 0.550668738047621, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,168 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.57061084606978}
 2023-07-02 10:24:27,168 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,170 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.13331
 2023-07-02 10:24:27,170 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,170 [mcmc] New sample, #170:
   Omega_m:0.534067
 2023-07-02 10:24:27,170 [model] Posterior to be computed for parameters {'Omega_m': 0.6007601829917492}
 2023-07-02 10:24:27,170 [prior] Evaluating prior at array([0.60076018])
 2023-07-02 10:24:27,170 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,170 [model] Got input parameters: {'Omega_m': 0.6007601829917492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,170 [classy] Got parameters {'Omega_m': 0.6007601829917492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,170 [classy] Computing new state
 2023-07-02 10:24:27,170 [classy] Setting parameters: {'Omega_m': 0.6007601829917492, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.22756796216372}
 2023-07-02 10:24:27,218 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.87438
 2023-07-02 10:24:27,220 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,220 [model] Posterior to be computed for parameters {'Omega_m': 0.4526248853094927}
 2023-07-02 10:24:27,220 [prior] Evaluating prior at array([0.45262489])
 2023-07-02 10:24:27,220 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,220 [model] Got input parameters: {'Omega_m': 0.4526248853094927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,220 [classy] Got parameters {'Omega_m': 0.4526248853094927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,220 [classy] Computing new state
 2023-07-02 10:24:27,220 [classy] Setting parameters: {'Omega_m': 0.4526248853094927, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.12094456354563}
 2023-07-02 10:24:27,268 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,270 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.884374
 2023-07-02 10:24:27,270 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,270 [mcmc] New sample, #171:
   Omega_m:0.5506687
 2023-07-02 10:24:27,270 [model] Posterior to be computed for parameters {'Omega_m': 0.12507670821837036}
 2023-07-02 10:24:27,270 [prior] Evaluating prior at array([0.12507671])
 2023-07-02 10:24:27,270 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,270 [model] Got input parameters: {'Omega_m': 0.12507670821837036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,270 [classy] Got parameters {'Omega_m': 0.12507670821837036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,271 [classy] Computing new state
 2023-07-02 10:24:27,271 [classy] Setting parameters: {'Omega_m': 0.12507670821837036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 178.74797904890733}
 2023-07-02 10:24:27,317 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.85545
 2023-07-02 10:24:27,319 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,319 [model] Posterior to be computed for parameters {'Omega_m': 0.6676719936567093}
 2023-07-02 10:24:27,319 [prior] Evaluating prior at array([0.66767199])
 2023-07-02 10:24:27,319 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,319 [model] Got input parameters: {'Omega_m': 0.6676719936567093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,319 [classy] Got parameters {'Omega_m': 0.6676719936567093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,319 [classy] Computing new state
 2023-07-02 10:24:27,319 [classy] Setting parameters: {'Omega_m': 0.6676719936567093, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,364 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.19181827627244}
 2023-07-02 10:24:27,364 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,366 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.93157
 2023-07-02 10:24:27,366 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,366 [model] Posterior to be computed for parameters {'Omega_m': 0.757040022077594}
 2023-07-02 10:24:27,366 [prior] Evaluating prior at array([0.75704002])
 2023-07-02 10:24:27,366 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,366 [model] Got input parameters: {'Omega_m': 0.757040022077594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,366 [classy] Got parameters {'Omega_m': 0.757040022077594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,366 [classy] Computing new state
 2023-07-02 10:24:27,367 [classy] Setting parameters: {'Omega_m': 0.757040022077594, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,412 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.43069203095706}
 2023-07-02 10:24:27,412 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,414 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.41855
 2023-07-02 10:24:27,414 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,414 [model] Posterior to be computed for parameters {'Omega_m': 0.5341352573318914}
 2023-07-02 10:24:27,414 [prior] Evaluating prior at array([0.53413526])
 2023-07-02 10:24:27,414 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,414 [model] Got input parameters: {'Omega_m': 0.5341352573318914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,414 [classy] Got parameters {'Omega_m': 0.5341352573318914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,414 [classy] Computing new state
 2023-07-02 10:24:27,414 [classy] Setting parameters: {'Omega_m': 0.5341352573318914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.74342532430178}
 2023-07-02 10:24:27,461 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.90131
 2023-07-02 10:24:27,463 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,463 [mcmc] New sample, #172:
   Omega_m:0.4526249
 2023-07-02 10:24:27,463 [model] Posterior to be computed for parameters {'Omega_m': 0.2764139728732288}
 2023-07-02 10:24:27,463 [prior] Evaluating prior at array([0.27641397])
 2023-07-02 10:24:27,463 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,463 [model] Got input parameters: {'Omega_m': 0.2764139728732288, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,463 [classy] Got parameters {'Omega_m': 0.2764139728732288, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,463 [classy] Computing new state
 2023-07-02 10:24:27,463 [classy] Setting parameters: {'Omega_m': 0.2764139728732288, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.83707758514967}
 2023-07-02 10:24:27,509 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0877608
 2023-07-02 10:24:27,511 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,511 [mcmc] New sample, #173:
   Omega_m:0.5341353
 2023-07-02 10:24:27,511 [model] Posterior to be computed for parameters {'Omega_m': -0.04424440025705728}
 2023-07-02 10:24:27,511 [prior] Evaluating prior at array([-0.0442444])
 2023-07-02 10:24:27,511 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,512 [model] Posterior to be computed for parameters {'Omega_m': 0.5266753853360975}
 2023-07-02 10:24:27,512 [prior] Evaluating prior at array([0.52667539])
 2023-07-02 10:24:27,512 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,512 [model] Got input parameters: {'Omega_m': 0.5266753853360975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,512 [classy] Got parameters {'Omega_m': 0.5266753853360975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,512 [classy] Computing new state
 2023-07-02 10:24:27,512 [classy] Setting parameters: {'Omega_m': 0.5266753853360975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.28479833561015}
 2023-07-02 10:24:27,559 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,561 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.79903
 2023-07-02 10:24:27,561 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,561 [model] Posterior to be computed for parameters {'Omega_m': 0.05567446170158566}
 2023-07-02 10:24:27,561 [prior] Evaluating prior at array([0.05567446])
 2023-07-02 10:24:27,561 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,561 [model] Posterior to be computed for parameters {'Omega_m': 0.5413965954638591}
 2023-07-02 10:24:27,561 [prior] Evaluating prior at array([0.5413966])
 2023-07-02 10:24:27,561 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,561 [model] Got input parameters: {'Omega_m': 0.5413965954638591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,561 [classy] Got parameters {'Omega_m': 0.5413965954638591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,561 [classy] Computing new state
 2023-07-02 10:24:27,561 [classy] Setting parameters: {'Omega_m': 0.5413965954638591, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.22382391579825}
 2023-07-02 10:24:27,608 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,610 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00232
 2023-07-02 10:24:27,610 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,610 [model] Posterior to be computed for parameters {'Omega_m': 0.5154868577245266}
 2023-07-02 10:24:27,610 [prior] Evaluating prior at array([0.51548686])
 2023-07-02 10:24:27,610 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,610 [model] Got input parameters: {'Omega_m': 0.5154868577245266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,610 [classy] Got parameters {'Omega_m': 0.5154868577245266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,610 [classy] Computing new state
 2023-07-02 10:24:27,610 [classy] Setting parameters: {'Omega_m': 0.5154868577245266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,657 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.11159440930913}
 2023-07-02 10:24:27,657 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,659 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.64864
 2023-07-02 10:24:27,659 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,659 [model] Posterior to be computed for parameters {'Omega_m': 0.5991998935214596}
 2023-07-02 10:24:27,659 [prior] Evaluating prior at array([0.59919989])
 2023-07-02 10:24:27,659 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,659 [model] Got input parameters: {'Omega_m': 0.5991998935214596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,660 [classy] Got parameters {'Omega_m': 0.5991998935214596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,660 [classy] Computing new state
 2023-07-02 10:24:27,660 [classy] Setting parameters: {'Omega_m': 0.5991998935214596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.32725275527292}
 2023-07-02 10:24:27,707 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,708 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.85055
 2023-07-02 10:24:27,709 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,709 [model] Posterior to be computed for parameters {'Omega_m': 0.13900100346682256}
 2023-07-02 10:24:27,709 [prior] Evaluating prior at array([0.139001])
 2023-07-02 10:24:27,709 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,709 [model] Got input parameters: {'Omega_m': 0.13900100346682256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,709 [classy] Got parameters {'Omega_m': 0.13900100346682256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,709 [classy] Computing new state
 2023-07-02 10:24:27,709 [classy] Setting parameters: {'Omega_m': 0.13900100346682256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.51259965267232}
 2023-07-02 10:24:27,756 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.12983
 2023-07-02 10:24:27,758 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,758 [model] Posterior to be computed for parameters {'Omega_m': 0.26773400495235694}
 2023-07-02 10:24:27,758 [prior] Evaluating prior at array([0.267734])
 2023-07-02 10:24:27,758 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,758 [model] Got input parameters: {'Omega_m': 0.26773400495235694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,758 [classy] Got parameters {'Omega_m': 0.26773400495235694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,758 [classy] Computing new state
 2023-07-02 10:24:27,758 [classy] Setting parameters: {'Omega_m': 0.26773400495235694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,806 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.01503623821222}
 2023-07-02 10:24:27,806 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,807 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138167
 2023-07-02 10:24:27,808 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,808 [mcmc] New sample, #174:
   Omega_m:0.276414
 2023-07-02 10:24:27,808 [model] Posterior to be computed for parameters {'Omega_m': 0.45183786622000616}
 2023-07-02 10:24:27,808 [prior] Evaluating prior at array([0.45183787])
 2023-07-02 10:24:27,808 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,808 [model] Got input parameters: {'Omega_m': 0.45183786622000616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,808 [classy] Got parameters {'Omega_m': 0.45183786622000616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,808 [classy] Computing new state
 2023-07-02 10:24:27,808 [classy] Setting parameters: {'Omega_m': 0.45183786622000616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,855 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.1879490254829}
 2023-07-02 10:24:27,855 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.875825
 2023-07-02 10:24:27,857 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,857 [mcmc] New sample, #175:
   Omega_m:0.267734
 2023-07-02 10:24:27,857 [model] Posterior to be computed for parameters {'Omega_m': 0.3085329635489119}
 2023-07-02 10:24:27,857 [prior] Evaluating prior at array([0.30853296])
 2023-07-02 10:24:27,857 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,857 [model] Got input parameters: {'Omega_m': 0.3085329635489119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,857 [classy] Got parameters {'Omega_m': 0.3085329635489119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,857 [classy] Computing new state
 2023-07-02 10:24:27,857 [classy] Setting parameters: {'Omega_m': 0.3085329635489119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73823652512266}
 2023-07-02 10:24:27,905 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00116921
 2023-07-02 10:24:27,907 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,907 [mcmc] New sample, #176:
   Omega_m:0.4518379
 2023-07-02 10:24:27,907 [model] Posterior to be computed for parameters {'Omega_m': -0.03285669777687322}
 2023-07-02 10:24:27,907 [prior] Evaluating prior at array([-0.0328567])
 2023-07-02 10:24:27,907 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,907 [model] Posterior to be computed for parameters {'Omega_m': 0.5304728679004929}
 2023-07-02 10:24:27,907 [prior] Evaluating prior at array([0.53047287])
 2023-07-02 10:24:27,907 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,907 [model] Got input parameters: {'Omega_m': 0.5304728679004929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,907 [classy] Got parameters {'Omega_m': 0.5304728679004929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,907 [classy] Computing new state
 2023-07-02 10:24:27,907 [classy] Setting parameters: {'Omega_m': 0.5304728679004929, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:27,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.0082292709288}
 2023-07-02 10:24:27,955 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:27,957 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.85091
 2023-07-02 10:24:27,957 [model] Computed derived parameters: {}
 2023-07-02 10:24:27,957 [model] Posterior to be computed for parameters {'Omega_m': -0.08845110240715992}
 2023-07-02 10:24:27,957 [prior] Evaluating prior at array([-0.0884511])
 2023-07-02 10:24:27,957 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,957 [model] Posterior to be computed for parameters {'Omega_m': 1.3580768616683812}
 2023-07-02 10:24:27,957 [prior] Evaluating prior at array([1.35807686])
 2023-07-02 10:24:27,957 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,957 [model] Posterior to be computed for parameters {'Omega_m': 0.04270312622917444}
 2023-07-02 10:24:27,957 [prior] Evaluating prior at array([0.04270313])
 2023-07-02 10:24:27,957 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:27,958 [model] Posterior to be computed for parameters {'Omega_m': 0.41553439362310207}
 2023-07-02 10:24:27,958 [prior] Evaluating prior at array([0.41553439])
 2023-07-02 10:24:27,958 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:27,958 [model] Got input parameters: {'Omega_m': 0.41553439362310207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,958 [classy] Got parameters {'Omega_m': 0.41553439362310207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:27,958 [classy] Computing new state
 2023-07-02 10:24:27,958 [classy] Setting parameters: {'Omega_m': 0.41553439362310207, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.4094049992323}
 2023-07-02 10:24:28,005 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,007 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.515515
 2023-07-02 10:24:28,007 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,007 [model] Posterior to be computed for parameters {'Omega_m': 0.5909026749520173}
 2023-07-02 10:24:28,007 [prior] Evaluating prior at array([0.59090267])
 2023-07-02 10:24:28,007 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,007 [model] Got input parameters: {'Omega_m': 0.5909026749520173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,007 [classy] Got parameters {'Omega_m': 0.5909026749520173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,007 [classy] Computing new state
 2023-07-02 10:24:28,007 [classy] Setting parameters: {'Omega_m': 0.5909026749520173, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.86194680451645}
 2023-07-02 10:24:28,055 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.72454
 2023-07-02 10:24:28,057 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,057 [model] Posterior to be computed for parameters {'Omega_m': -0.0832441033156755}
 2023-07-02 10:24:28,057 [prior] Evaluating prior at array([-0.0832441])
 2023-07-02 10:24:28,057 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,058 [model] Posterior to be computed for parameters {'Omega_m': 0.2851000731093252}
 2023-07-02 10:24:28,058 [prior] Evaluating prior at array([0.28510007])
 2023-07-02 10:24:28,058 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,058 [model] Got input parameters: {'Omega_m': 0.2851000731093252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,058 [classy] Got parameters {'Omega_m': 0.2851000731093252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,058 [classy] Computing new state
 2023-07-02 10:24:28,058 [classy] Setting parameters: {'Omega_m': 0.2851000731093252, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.6894681204715}
 2023-07-02 10:24:28,105 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,106 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0495185
 2023-07-02 10:24:28,107 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,107 [mcmc] New sample, #177:
   Omega_m:0.308533
 2023-07-02 10:24:28,107 [model] Posterior to be computed for parameters {'Omega_m': 0.47332113587248015}
 2023-07-02 10:24:28,107 [prior] Evaluating prior at array([0.47332114])
 2023-07-02 10:24:28,107 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,107 [model] Got input parameters: {'Omega_m': 0.47332113587248015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,107 [classy] Got parameters {'Omega_m': 0.47332113587248015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,107 [classy] Computing new state
 2023-07-02 10:24:28,107 [classy] Setting parameters: {'Omega_m': 0.47332113587248015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.39896641565284}
 2023-07-02 10:24:28,156 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.11906
 2023-07-02 10:24:28,158 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,158 [model] Posterior to be computed for parameters {'Omega_m': -0.0208845242336802}
 2023-07-02 10:24:28,158 [prior] Evaluating prior at array([-0.02088452])
 2023-07-02 10:24:28,158 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,158 [model] Posterior to be computed for parameters {'Omega_m': 0.17422918548014144}
 2023-07-02 10:24:28,158 [prior] Evaluating prior at array([0.17422919])
 2023-07-02 10:24:28,158 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,158 [model] Got input parameters: {'Omega_m': 0.17422918548014144, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,158 [classy] Got parameters {'Omega_m': 0.17422918548014144, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,158 [classy] Computing new state
 2023-07-02 10:24:28,159 [classy] Setting parameters: {'Omega_m': 0.17422918548014144, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.18946311664695}
 2023-07-02 10:24:28,205 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.75085
 2023-07-02 10:24:28,207 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,207 [model] Posterior to be computed for parameters {'Omega_m': 0.7483208209499159}
 2023-07-02 10:24:28,207 [prior] Evaluating prior at array([0.74832082])
 2023-07-02 10:24:28,207 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,207 [model] Got input parameters: {'Omega_m': 0.7483208209499159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,207 [classy] Got parameters {'Omega_m': 0.7483208209499159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,207 [classy] Computing new state
 2023-07-02 10:24:28,207 [classy] Setting parameters: {'Omega_m': 0.7483208209499159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.86756945572505}
 2023-07-02 10:24:28,253 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,255 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.27092
 2023-07-02 10:24:28,255 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,255 [model] Posterior to be computed for parameters {'Omega_m': 0.5270729908760221}
 2023-07-02 10:24:28,255 [prior] Evaluating prior at array([0.52707299])
 2023-07-02 10:24:28,255 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,255 [model] Got input parameters: {'Omega_m': 0.5270729908760221, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,255 [classy] Got parameters {'Omega_m': 0.5270729908760221, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,255 [classy] Computing new state
 2023-07-02 10:24:28,255 [classy] Setting parameters: {'Omega_m': 0.5270729908760221, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.25574585074364}
 2023-07-02 10:24:28,301 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,304 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.80444
 2023-07-02 10:24:28,304 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,304 [mcmc] New sample, #178:
   Omega_m:0.2851001
 2023-07-02 10:24:28,304 [model] Posterior to be computed for parameters {'Omega_m': 0.2403619553169652}
 2023-07-02 10:24:28,304 [prior] Evaluating prior at array([0.24036196])
 2023-07-02 10:24:28,305 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,305 [model] Got input parameters: {'Omega_m': 0.2403619553169652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,305 [classy] Got parameters {'Omega_m': 0.2403619553169652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,305 [classy] Computing new state
 2023-07-02 10:24:28,305 [classy] Setting parameters: {'Omega_m': 0.2403619553169652, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.95186704056877}
 2023-07-02 10:24:28,351 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,354 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.387194
 2023-07-02 10:24:28,354 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,354 [mcmc] New sample, #179:
   Omega_m:0.527073
 2023-07-02 10:24:28,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3817540439306617}
 2023-07-02 10:24:28,354 [prior] Evaluating prior at array([0.38175404])
 2023-07-02 10:24:28,354 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,354 [model] Got input parameters: {'Omega_m': 0.3817540439306617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,354 [classy] Got parameters {'Omega_m': 0.3817540439306617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,354 [classy] Computing new state
 2023-07-02 10:24:28,354 [classy] Setting parameters: {'Omega_m': 0.3817540439306617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.659972009885}
 2023-07-02 10:24:28,400 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,403 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.250477
 2023-07-02 10:24:28,403 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,403 [mcmc] New sample, #180:
   Omega_m:0.240362
 2023-07-02 10:24:28,403 [model] Posterior to be computed for parameters {'Omega_m': 0.5108929214218408}
 2023-07-02 10:24:28,403 [prior] Evaluating prior at array([0.51089292])
 2023-07-02 10:24:28,403 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,403 [model] Got input parameters: {'Omega_m': 0.5108929214218408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,403 [classy] Got parameters {'Omega_m': 0.5108929214218408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,403 [classy] Computing new state
 2023-07-02 10:24:28,403 [classy] Setting parameters: {'Omega_m': 0.5108929214218408, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.45633321788398}
 2023-07-02 10:24:28,450 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,453 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.588
 2023-07-02 10:24:28,453 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,453 [model] Posterior to be computed for parameters {'Omega_m': 0.06918960955578157}
 2023-07-02 10:24:28,453 [prior] Evaluating prior at array([0.06918961])
 2023-07-02 10:24:28,453 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,453 [model] Posterior to be computed for parameters {'Omega_m': 0.1850103480498319}
 2023-07-02 10:24:28,453 [prior] Evaluating prior at array([0.18501035])
 2023-07-02 10:24:28,453 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,453 [model] Got input parameters: {'Omega_m': 0.1850103480498319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,453 [classy] Got parameters {'Omega_m': 0.1850103480498319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,453 [classy] Computing new state
 2023-07-02 10:24:28,454 [classy] Setting parameters: {'Omega_m': 0.1850103480498319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.15874294749455}
 2023-07-02 10:24:28,504 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.43533
 2023-07-02 10:24:28,506 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,506 [mcmc] New sample, #181:
   Omega_m:0.381754
 2023-07-02 10:24:28,506 [model] Posterior to be computed for parameters {'Omega_m': 0.08242770385051884}
 2023-07-02 10:24:28,506 [prior] Evaluating prior at array([0.0824277])
 2023-07-02 10:24:28,506 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,506 [model] Posterior to be computed for parameters {'Omega_m': 0.2859260770913983}
 2023-07-02 10:24:28,506 [prior] Evaluating prior at array([0.28592608])
 2023-07-02 10:24:28,506 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,506 [model] Got input parameters: {'Omega_m': 0.2859260770913983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,506 [classy] Got parameters {'Omega_m': 0.2859260770913983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,506 [classy] Computing new state
 2023-07-02 10:24:28,506 [classy] Setting parameters: {'Omega_m': 0.2859260770913983, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,558 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.58190192554164}
 2023-07-02 10:24:28,558 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,560 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0464874
 2023-07-02 10:24:28,560 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,560 [mcmc] New sample, #182:
   Omega_m:0.1850103
 2023-07-02 10:24:28,560 [model] Posterior to be computed for parameters {'Omega_m': 0.640498793144292}
 2023-07-02 10:24:28,560 [prior] Evaluating prior at array([0.64049879])
 2023-07-02 10:24:28,561 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,561 [model] Got input parameters: {'Omega_m': 0.640498793144292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,561 [classy] Got parameters {'Omega_m': 0.640498793144292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,561 [classy] Computing new state
 2023-07-02 10:24:28,561 [classy] Setting parameters: {'Omega_m': 0.640498793144292, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.77667081684497}
 2023-07-02 10:24:28,610 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.49473
 2023-07-02 10:24:28,612 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,612 [model] Posterior to be computed for parameters {'Omega_m': 0.6158417773805812}
 2023-07-02 10:24:28,612 [prior] Evaluating prior at array([0.61584178])
 2023-07-02 10:24:28,612 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,612 [model] Got input parameters: {'Omega_m': 0.6158417773805812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,612 [classy] Got parameters {'Omega_m': 0.6158417773805812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,612 [classy] Computing new state
 2023-07-02 10:24:28,612 [classy] Setting parameters: {'Omega_m': 0.6158417773805812, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.27782175578739}
 2023-07-02 10:24:28,663 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,666 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.10691
 2023-07-02 10:24:28,666 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,666 [model] Posterior to be computed for parameters {'Omega_m': 0.18381101836547764}
 2023-07-02 10:24:28,666 [prior] Evaluating prior at array([0.18381102])
 2023-07-02 10:24:28,666 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,666 [model] Got input parameters: {'Omega_m': 0.18381101836547764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,666 [classy] Got parameters {'Omega_m': 0.18381101836547764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,666 [classy] Computing new state
 2023-07-02 10:24:28,666 [classy] Setting parameters: {'Omega_m': 0.18381101836547764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.38030381078997}
 2023-07-02 10:24:28,714 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.46831
 2023-07-02 10:24:28,716 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,716 [model] Posterior to be computed for parameters {'Omega_m': 0.4944286144698772}
 2023-07-02 10:24:28,716 [prior] Evaluating prior at array([0.49442861])
 2023-07-02 10:24:28,716 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,716 [model] Got input parameters: {'Omega_m': 0.4944286144698772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,716 [classy] Got parameters {'Omega_m': 0.4944286144698772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,716 [classy] Computing new state
 2023-07-02 10:24:28,716 [classy] Setting parameters: {'Omega_m': 0.4944286144698772, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.71816953033564}
 2023-07-02 10:24:28,764 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.3763
 2023-07-02 10:24:28,766 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,766 [model] Posterior to be computed for parameters {'Omega_m': 0.23034075303903057}
 2023-07-02 10:24:28,766 [prior] Evaluating prior at array([0.23034075])
 2023-07-02 10:24:28,766 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,766 [model] Got input parameters: {'Omega_m': 0.23034075303903057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,766 [classy] Got parameters {'Omega_m': 0.23034075303903057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,766 [classy] Computing new state
 2023-07-02 10:24:28,766 [classy] Setting parameters: {'Omega_m': 0.23034075303903057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,813 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.48549358881976}
 2023-07-02 10:24:28,813 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,815 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.517161
 2023-07-02 10:24:28,815 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,815 [mcmc] New sample, #183:
   Omega_m:0.2859261
 2023-07-02 10:24:28,815 [model] Posterior to be computed for parameters {'Omega_m': 0.010159662476791592}
 2023-07-02 10:24:28,815 [prior] Evaluating prior at array([0.01015966])
 2023-07-02 10:24:28,816 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,816 [model] Posterior to be computed for parameters {'Omega_m': -0.33642953335879144}
 2023-07-02 10:24:28,816 [prior] Evaluating prior at array([-0.33642953])
 2023-07-02 10:24:28,816 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,816 [model] Posterior to be computed for parameters {'Omega_m': 0.20254903196726934}
 2023-07-02 10:24:28,816 [prior] Evaluating prior at array([0.20254903])
 2023-07-02 10:24:28,816 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,816 [model] Got input parameters: {'Omega_m': 0.20254903196726934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,816 [classy] Got parameters {'Omega_m': 0.20254903196726934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,816 [classy] Computing new state
 2023-07-02 10:24:28,816 [classy] Setting parameters: {'Omega_m': 0.20254903196726934, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.03484031123614}
 2023-07-02 10:24:28,864 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.00851
 2023-07-02 10:24:28,866 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,866 [mcmc] New sample, #184:
   Omega_m:0.2303408
 2023-07-02 10:24:28,866 [model] Posterior to be computed for parameters {'Omega_m': 0.11143582711414192}
 2023-07-02 10:24:28,866 [prior] Evaluating prior at array([0.11143583])
 2023-07-02 10:24:28,866 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,866 [model] Got input parameters: {'Omega_m': 0.11143582711414192, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,866 [classy] Got parameters {'Omega_m': 0.11143582711414192, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,866 [classy] Computing new state
 2023-07-02 10:24:28,866 [classy] Setting parameters: {'Omega_m': 0.11143582711414192, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.14100128578502}
 2023-07-02 10:24:28,912 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,914 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.69027
 2023-07-02 10:24:28,915 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,915 [model] Posterior to be computed for parameters {'Omega_m': 0.3019958858575965}
 2023-07-02 10:24:28,915 [prior] Evaluating prior at array([0.30199589])
 2023-07-02 10:24:28,915 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,915 [model] Got input parameters: {'Omega_m': 0.3019958858575965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,915 [classy] Got parameters {'Omega_m': 0.3019958858575965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,915 [classy] Computing new state
 2023-07-02 10:24:28,915 [classy] Setting parameters: {'Omega_m': 0.3019958858575965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:28,962 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.541242924564}
 2023-07-02 10:24:28,962 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:28,964 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00712767
 2023-07-02 10:24:28,964 [model] Computed derived parameters: {}
 2023-07-02 10:24:28,964 [mcmc] New sample, #185:
   Omega_m:0.202549
 2023-07-02 10:24:28,964 [model] Posterior to be computed for parameters {'Omega_m': -0.006710484738526312}
 2023-07-02 10:24:28,964 [prior] Evaluating prior at array([-0.00671048])
 2023-07-02 10:24:28,964 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:28,964 [model] Posterior to be computed for parameters {'Omega_m': 0.13218920182756003}
 2023-07-02 10:24:28,964 [prior] Evaluating prior at array([0.1321892])
 2023-07-02 10:24:28,964 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:28,964 [model] Got input parameters: {'Omega_m': 0.13218920182756003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,965 [classy] Got parameters {'Omega_m': 0.13218920182756003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:28,965 [classy] Computing new state
 2023-07-02 10:24:28,965 [classy] Setting parameters: {'Omega_m': 0.13218920182756003, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 177.0682986296394}
 2023-07-02 10:24:29,011 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.47004
 2023-07-02 10:24:29,013 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,013 [mcmc] New sample, #186:
   Omega_m:0.3019959
 2023-07-02 10:24:29,014 [model] Posterior to be computed for parameters {'Omega_m': -0.2018324909461672}
 2023-07-02 10:24:29,014 [prior] Evaluating prior at array([-0.20183249])
 2023-07-02 10:24:29,014 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:29,014 [model] Posterior to be computed for parameters {'Omega_m': -0.152491160976961}
 2023-07-02 10:24:29,014 [prior] Evaluating prior at array([-0.15249116])
 2023-07-02 10:24:29,014 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:29,014 [model] Posterior to be computed for parameters {'Omega_m': 0.18610113894472463}
 2023-07-02 10:24:29,014 [prior] Evaluating prior at array([0.18610114])
 2023-07-02 10:24:29,014 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,014 [model] Got input parameters: {'Omega_m': 0.18610113894472463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,014 [classy] Got parameters {'Omega_m': 0.18610113894472463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,014 [classy] Computing new state
 2023-07-02 10:24:29,014 [classy] Setting parameters: {'Omega_m': 0.18610113894472463, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,062 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.95816042121862}
 2023-07-02 10:24:29,062 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,064 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.40578
 2023-07-02 10:24:29,065 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,065 [mcmc] New sample, #187:
   Omega_m:0.1321892
 2023-07-02 10:24:29,065 [model] Posterior to be computed for parameters {'Omega_m': 0.6886665112664525}
 2023-07-02 10:24:29,065 [prior] Evaluating prior at array([0.68866651])
 2023-07-02 10:24:29,065 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,065 [model] Got input parameters: {'Omega_m': 0.6886665112664525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,065 [classy] Got parameters {'Omega_m': 0.6886665112664525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,065 [classy] Computing new state
 2023-07-02 10:24:29,065 [classy] Setting parameters: {'Omega_m': 0.6886665112664525, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.01387886099977}
 2023-07-02 10:24:29,109 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.27478
 2023-07-02 10:24:29,111 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,111 [model] Posterior to be computed for parameters {'Omega_m': 0.25298577815102413}
 2023-07-02 10:24:29,111 [prior] Evaluating prior at array([0.25298578])
 2023-07-02 10:24:29,111 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,111 [model] Got input parameters: {'Omega_m': 0.25298577815102413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,111 [classy] Got parameters {'Omega_m': 0.25298577815102413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,112 [classy] Computing new state
 2023-07-02 10:24:29,112 [classy] Setting parameters: {'Omega_m': 0.25298577815102413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.09239383345}
 2023-07-02 10:24:29,158 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.254256
 2023-07-02 10:24:29,160 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,160 [mcmc] New sample, #188:
   Omega_m:0.1861011
 2023-07-02 10:24:29,160 [model] Posterior to be computed for parameters {'Omega_m': 0.3043960178728972}
 2023-07-02 10:24:29,160 [prior] Evaluating prior at array([0.30439602])
 2023-07-02 10:24:29,160 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,160 [model] Got input parameters: {'Omega_m': 0.3043960178728972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,160 [classy] Got parameters {'Omega_m': 0.3043960178728972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,160 [classy] Computing new state
 2023-07-02 10:24:29,160 [classy] Setting parameters: {'Omega_m': 0.3043960178728972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,207 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24465841576716}
 2023-07-02 10:24:29,207 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,209 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00429598
 2023-07-02 10:24:29,209 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,209 [mcmc] New sample, #189:
   Omega_m:0.2529858
 2023-07-02 10:24:29,209 [model] Posterior to be computed for parameters {'Omega_m': 0.13894279846467986}
 2023-07-02 10:24:29,209 [prior] Evaluating prior at array([0.1389428])
 2023-07-02 10:24:29,209 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,209 [model] Got input parameters: {'Omega_m': 0.13894279846467986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,209 [classy] Got parameters {'Omega_m': 0.13894279846467986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,209 [classy] Computing new state
 2023-07-02 10:24:29,209 [classy] Setting parameters: {'Omega_m': 0.13894279846467986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.52568368528713}
 2023-07-02 10:24:29,256 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,258 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.13262
 2023-07-02 10:24:29,258 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,258 [model] Posterior to be computed for parameters {'Omega_m': 0.27146184702395915}
 2023-07-02 10:24:29,258 [prior] Evaluating prior at array([0.27146185])
 2023-07-02 10:24:29,258 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,258 [model] Got input parameters: {'Omega_m': 0.27146184702395915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,258 [classy] Got parameters {'Omega_m': 0.27146184702395915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,258 [classy] Computing new state
 2023-07-02 10:24:29,258 [classy] Setting parameters: {'Omega_m': 0.27146184702395915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.50519655712574}
 2023-07-02 10:24:29,305 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,307 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.11497
 2023-07-02 10:24:29,307 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,307 [mcmc] New sample, #190:
   Omega_m:0.304396
 2023-07-02 10:24:29,307 [model] Posterior to be computed for parameters {'Omega_m': 0.483127237762323}
 2023-07-02 10:24:29,307 [prior] Evaluating prior at array([0.48312724])
 2023-07-02 10:24:29,307 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,307 [model] Got input parameters: {'Omega_m': 0.483127237762323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,307 [classy] Got parameters {'Omega_m': 0.483127237762323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,307 [classy] Computing new state
 2023-07-02 10:24:29,307 [classy] Setting parameters: {'Omega_m': 0.483127237762323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.60900267309165}
 2023-07-02 10:24:29,354 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.23646
 2023-07-02 10:24:29,356 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,356 [model] Posterior to be computed for parameters {'Omega_m': 0.3892638309317183}
 2023-07-02 10:24:29,356 [prior] Evaluating prior at array([0.38926383])
 2023-07-02 10:24:29,356 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,356 [model] Got input parameters: {'Omega_m': 0.3892638309317183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,356 [classy] Got parameters {'Omega_m': 0.3892638309317183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,357 [classy] Computing new state
 2023-07-02 10:24:29,357 [classy] Setting parameters: {'Omega_m': 0.3892638309317183, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.91435668177454}
 2023-07-02 10:24:29,402 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.302687
 2023-07-02 10:24:29,405 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,405 [mcmc] New sample, #191:
   Omega_m:0.2714618
 2023-07-02 10:24:29,405 [model] Posterior to be computed for parameters {'Omega_m': 0.4831783281387563}
 2023-07-02 10:24:29,405 [prior] Evaluating prior at array([0.48317833])
 2023-07-02 10:24:29,406 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,406 [model] Got input parameters: {'Omega_m': 0.4831783281387563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,406 [classy] Got parameters {'Omega_m': 0.4831783281387563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,406 [classy] Computing new state
 2023-07-02 10:24:29,406 [classy] Setting parameters: {'Omega_m': 0.4831783281387563, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,451 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.6049284726945}
 2023-07-02 10:24:29,451 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,453 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.23708
 2023-07-02 10:24:29,453 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,454 [mcmc] New sample, #192:
   Omega_m:0.3892638
 2023-07-02 10:24:29,454 [model] Posterior to be computed for parameters {'Omega_m': 0.6000221929121535}
 2023-07-02 10:24:29,454 [prior] Evaluating prior at array([0.60002219])
 2023-07-02 10:24:29,454 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,454 [model] Got input parameters: {'Omega_m': 0.6000221929121535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,454 [classy] Got parameters {'Omega_m': 0.6000221929121535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,454 [classy] Computing new state
 2023-07-02 10:24:29,454 [classy] Setting parameters: {'Omega_m': 0.6000221929121535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.2746838949577}
 2023-07-02 10:24:29,500 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,502 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.8631
 2023-07-02 10:24:29,502 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,502 [model] Posterior to be computed for parameters {'Omega_m': 0.754922288752434}
 2023-07-02 10:24:29,502 [prior] Evaluating prior at array([0.75492229])
 2023-07-02 10:24:29,502 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,502 [model] Got input parameters: {'Omega_m': 0.754922288752434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,502 [classy] Got parameters {'Omega_m': 0.754922288752434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,503 [classy] Computing new state
 2023-07-02 10:24:29,503 [classy] Setting parameters: {'Omega_m': 0.754922288752434, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,548 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.53629530572549}
 2023-07-02 10:24:29,548 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,550 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.38265
 2023-07-02 10:24:29,550 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,550 [model] Posterior to be computed for parameters {'Omega_m': 0.724634429393231}
 2023-07-02 10:24:29,550 [prior] Evaluating prior at array([0.72463443])
 2023-07-02 10:24:29,551 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,551 [model] Got input parameters: {'Omega_m': 0.724634429393231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,551 [classy] Got parameters {'Omega_m': 0.724634429393231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,551 [classy] Computing new state
 2023-07-02 10:24:29,551 [classy] Setting parameters: {'Omega_m': 0.724634429393231, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.0830850418334}
 2023-07-02 10:24:29,596 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,598 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.87221
 2023-07-02 10:24:29,598 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,598 [model] Posterior to be computed for parameters {'Omega_m': 0.4888087006092323}
 2023-07-02 10:24:29,598 [prior] Evaluating prior at array([0.4888087])
 2023-07-02 10:24:29,598 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,598 [model] Got input parameters: {'Omega_m': 0.4888087006092323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,598 [classy] Got parameters {'Omega_m': 0.4888087006092323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,598 [classy] Computing new state
 2023-07-02 10:24:29,598 [classy] Setting parameters: {'Omega_m': 0.4888087006092323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,645 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.15858372339014}
 2023-07-02 10:24:29,645 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,647 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.30618
 2023-07-02 10:24:29,647 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,647 [mcmc] New sample, #193:
   Omega_m:0.4831783
 2023-07-02 10:24:29,647 [model] Posterior to be computed for parameters {'Omega_m': 0.9127037765380227}
 2023-07-02 10:24:29,647 [prior] Evaluating prior at array([0.91270378])
 2023-07-02 10:24:29,648 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,648 [model] Got input parameters: {'Omega_m': 0.9127037765380227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,648 [classy] Got parameters {'Omega_m': 0.9127037765380227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,648 [classy] Computing new state
 2023-07-02 10:24:29,648 [classy] Setting parameters: {'Omega_m': 0.9127037765380227, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.45290818306594}
 2023-07-02 10:24:29,696 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.09856
 2023-07-02 10:24:29,697 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,698 [model] Posterior to be computed for parameters {'Omega_m': 0.3474968270023766}
 2023-07-02 10:24:29,698 [prior] Evaluating prior at array([0.34749683])
 2023-07-02 10:24:29,698 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,698 [model] Got input parameters: {'Omega_m': 0.3474968270023766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,698 [classy] Got parameters {'Omega_m': 0.3474968270023766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,698 [classy] Computing new state
 2023-07-02 10:24:29,698 [classy] Setting parameters: {'Omega_m': 0.3474968270023766, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2450117324434}
 2023-07-02 10:24:29,745 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,747 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0692969
 2023-07-02 10:24:29,747 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,747 [mcmc] New sample, #194:
   Omega_m:0.4888087
 2023-07-02 10:24:29,747 [model] Posterior to be computed for parameters {'Omega_m': 0.023597584485858025}
 2023-07-02 10:24:29,747 [prior] Evaluating prior at array([0.02359758])
 2023-07-02 10:24:29,747 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:29,748 [model] Posterior to be computed for parameters {'Omega_m': -0.019508109722111755}
 2023-07-02 10:24:29,748 [prior] Evaluating prior at array([-0.01950811])
 2023-07-02 10:24:29,748 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:29,748 [model] Posterior to be computed for parameters {'Omega_m': 0.15857228394240894}
 2023-07-02 10:24:29,748 [prior] Evaluating prior at array([0.15857228])
 2023-07-02 10:24:29,748 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,748 [model] Got input parameters: {'Omega_m': 0.15857228394240894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,748 [classy] Got parameters {'Omega_m': 0.15857228394240894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,748 [classy] Computing new state
 2023-07-02 10:24:29,748 [classy] Setting parameters: {'Omega_m': 0.15857228394240894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.3051964927806}
 2023-07-02 10:24:29,794 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,796 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.29203
 2023-07-02 10:24:29,796 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,796 [model] Posterior to be computed for parameters {'Omega_m': 0.473006373903228}
 2023-07-02 10:24:29,796 [prior] Evaluating prior at array([0.47300637])
 2023-07-02 10:24:29,796 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,796 [model] Got input parameters: {'Omega_m': 0.473006373903228, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,796 [classy] Got parameters {'Omega_m': 0.473006373903228, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,796 [classy] Computing new state
 2023-07-02 10:24:29,796 [classy] Setting parameters: {'Omega_m': 0.473006373903228, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.42459421715336}
 2023-07-02 10:24:29,842 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,844 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.11535
 2023-07-02 10:24:29,844 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,844 [model] Posterior to be computed for parameters {'Omega_m': 0.34897290181681667}
 2023-07-02 10:24:29,844 [prior] Evaluating prior at array([0.3489729])
 2023-07-02 10:24:29,844 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,844 [model] Got input parameters: {'Omega_m': 0.34897290181681667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,844 [classy] Got parameters {'Omega_m': 0.34897290181681667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,844 [classy] Computing new state
 2023-07-02 10:24:29,844 [classy] Setting parameters: {'Omega_m': 0.34897290181681667, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0839421607422}
 2023-07-02 10:24:29,891 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,893 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0749875
 2023-07-02 10:24:29,893 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,893 [mcmc] New sample, #195:
   Omega_m:0.3474968
 2023-07-02 10:24:29,893 [model] Posterior to be computed for parameters {'Omega_m': 0.42868800916654143}
 2023-07-02 10:24:29,893 [prior] Evaluating prior at array([0.42868801])
 2023-07-02 10:24:29,893 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,893 [model] Got input parameters: {'Omega_m': 0.42868800916654143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,893 [classy] Got parameters {'Omega_m': 0.42868800916654143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,893 [classy] Computing new state
 2023-07-02 10:24:29,893 [classy] Setting parameters: {'Omega_m': 0.42868800916654143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,940 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.21169451725174}
 2023-07-02 10:24:29,940 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,942 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.637958
 2023-07-02 10:24:29,942 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,942 [model] Posterior to be computed for parameters {'Omega_m': 0.5977114820660548}
 2023-07-02 10:24:29,942 [prior] Evaluating prior at array([0.59771148])
 2023-07-02 10:24:29,942 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,943 [model] Got input parameters: {'Omega_m': 0.5977114820660548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,943 [classy] Got parameters {'Omega_m': 0.5977114820660548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,943 [classy] Computing new state
 2023-07-02 10:24:29,943 [classy] Setting parameters: {'Omega_m': 0.5977114820660548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:29,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.42260238598074}
 2023-07-02 10:24:29,989 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:29,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.82785
 2023-07-02 10:24:29,991 [model] Computed derived parameters: {}
 2023-07-02 10:24:29,991 [model] Posterior to be computed for parameters {'Omega_m': 0.4149618726835698}
 2023-07-02 10:24:29,991 [prior] Evaluating prior at array([0.41496187])
 2023-07-02 10:24:29,991 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:29,991 [model] Got input parameters: {'Omega_m': 0.4149618726835698, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,991 [classy] Got parameters {'Omega_m': 0.4149618726835698, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:29,991 [classy] Computing new state
 2023-07-02 10:24:29,991 [classy] Setting parameters: {'Omega_m': 0.4149618726835698, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.4623631975701}
 2023-07-02 10:24:30,040 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,041 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.510412
 2023-07-02 10:24:30,041 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,042 [mcmc] New sample, #196:
   Omega_m:0.3489729
 2023-07-02 10:24:30,042 [model] Posterior to be computed for parameters {'Omega_m': 0.10964605242509334}
 2023-07-02 10:24:30,042 [prior] Evaluating prior at array([0.10964605])
 2023-07-02 10:24:30,042 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,042 [model] Got input parameters: {'Omega_m': 0.10964605242509334, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,042 [classy] Got parameters {'Omega_m': 0.10964605242509334, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,042 [classy] Computing new state
 2023-07-02 10:24:30,042 [classy] Setting parameters: {'Omega_m': 0.10964605242509334, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.60414861927933}
 2023-07-02 10:24:30,088 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.80998
 2023-07-02 10:24:30,090 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,090 [model] Posterior to be computed for parameters {'Omega_m': 0.31103396972410113}
 2023-07-02 10:24:30,090 [prior] Evaluating prior at array([0.31103397])
 2023-07-02 10:24:30,090 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,091 [model] Got input parameters: {'Omega_m': 0.31103396972410113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,091 [classy] Got parameters {'Omega_m': 0.31103396972410113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,091 [classy] Computing new state
 2023-07-02 10:24:30,091 [classy] Setting parameters: {'Omega_m': 0.31103396972410113, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,138 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43496799132515}
 2023-07-02 10:24:30,138 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,140 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000331776
 2023-07-02 10:24:30,140 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,140 [mcmc] New sample, #197:
   Omega_m:0.4149619
 2023-07-02 10:24:30,140 [model] Posterior to be computed for parameters {'Omega_m': 0.2764323159134341}
 2023-07-02 10:24:30,140 [prior] Evaluating prior at array([0.27643232])
 2023-07-02 10:24:30,140 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,140 [model] Got input parameters: {'Omega_m': 0.2764323159134341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,140 [classy] Got parameters {'Omega_m': 0.2764323159134341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,140 [classy] Computing new state
 2023-07-02 10:24:30,140 [classy] Setting parameters: {'Omega_m': 0.2764323159134341, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.83462352972455}
 2023-07-02 10:24:30,187 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0876677
 2023-07-02 10:24:30,189 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,189 [mcmc] New sample, #198:
   Omega_m:0.311034
 2023-07-02 10:24:30,189 [model] Posterior to be computed for parameters {'Omega_m': 0.6009290252802659}
 2023-07-02 10:24:30,189 [prior] Evaluating prior at array([0.60092903])
 2023-07-02 10:24:30,189 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,189 [model] Got input parameters: {'Omega_m': 0.6009290252802659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,189 [classy] Got parameters {'Omega_m': 0.6009290252802659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,189 [classy] Computing new state
 2023-07-02 10:24:30,189 [classy] Setting parameters: {'Omega_m': 0.6009290252802659, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.21679802378137}
 2023-07-02 10:24:30,236 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.87696
 2023-07-02 10:24:30,238 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,238 [model] Posterior to be computed for parameters {'Omega_m': 0.23330121042142024}
 2023-07-02 10:24:30,238 [prior] Evaluating prior at array([0.23330121])
 2023-07-02 10:24:30,238 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,238 [model] Got input parameters: {'Omega_m': 0.23330121042142024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,239 [classy] Got parameters {'Omega_m': 0.23330121042142024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,239 [classy] Computing new state
 2023-07-02 10:24:30,239 [classy] Setting parameters: {'Omega_m': 0.23330121042142024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.0268921630566}
 2023-07-02 10:24:30,286 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,288 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.476385
 2023-07-02 10:24:30,288 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,288 [mcmc] New sample, #199:
   Omega_m:0.2764323
 2023-07-02 10:24:30,288 [model] Posterior to be computed for parameters {'Omega_m': 0.2768722639101802}
 2023-07-02 10:24:30,288 [prior] Evaluating prior at array([0.27687226])
 2023-07-02 10:24:30,288 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,288 [model] Got input parameters: {'Omega_m': 0.2768722639101802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,288 [classy] Got parameters {'Omega_m': 0.2768722639101802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,288 [classy] Computing new state
 2023-07-02 10:24:30,288 [classy] Setting parameters: {'Omega_m': 0.2768722639101802, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.77576384892626}
 2023-07-02 10:24:30,336 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0854456
 2023-07-02 10:24:30,338 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,338 [mcmc] New sample, #200:
   Omega_m:0.2333012
 2023-07-02 10:24:30,338 [mcmc] Learn + convergence test @ 200 samples accepted.
 2023-07-02 10:24:30,338 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:30,343 [mcmc]  - Acceptance rate: 0.541
 2023-07-02 10:24:30,343 [mcmc]  - Condition number = 1
 2023-07-02 10:24:30,343 [mcmc]  - Eigenvalues = array([0.0890007])
 2023-07-02 10:24:30,344 [mcmc]  - Convergence of means: R-1 = 0.089001 after 160 accepted steps
 2023-07-02 10:24:30,344 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:30,344 [mcmc] array([[0.01207759]])
 2023-07-02 10:24:30,354 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:30,354 [model] Posterior to be computed for parameters {'Omega_m': 0.39977621242772454}
 2023-07-02 10:24:30,354 [prior] Evaluating prior at array([0.39977621])
 2023-07-02 10:24:30,354 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,354 [model] Got input parameters: {'Omega_m': 0.39977621242772454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,354 [classy] Got parameters {'Omega_m': 0.39977621242772454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,354 [classy] Computing new state
 2023-07-02 10:24:30,354 [classy] Setting parameters: {'Omega_m': 0.39977621242772454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,401 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.89320060193035}
 2023-07-02 10:24:30,401 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,403 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.382442
 2023-07-02 10:24:30,403 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,403 [model] Posterior to be computed for parameters {'Omega_m': 0.40945932246365413}
 2023-07-02 10:24:30,403 [prior] Evaluating prior at array([0.40945932])
 2023-07-02 10:24:30,403 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,403 [model] Got input parameters: {'Omega_m': 0.40945932246365413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,404 [classy] Got parameters {'Omega_m': 0.40945932246365413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,404 [classy] Computing new state
 2023-07-02 10:24:30,404 [classy] Setting parameters: {'Omega_m': 0.40945932246365413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.97493316651716}
 2023-07-02 10:24:30,451 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.462382
 2023-07-02 10:24:30,452 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,452 [mcmc] New sample, #201:
   Omega_m:0.2768723
 2023-07-02 10:24:30,453 [model] Posterior to be computed for parameters {'Omega_m': 0.4441384854211399}
 2023-07-02 10:24:30,453 [prior] Evaluating prior at array([0.44413849])
 2023-07-02 10:24:30,453 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,453 [model] Got input parameters: {'Omega_m': 0.4441384854211399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,453 [classy] Got parameters {'Omega_m': 0.4441384854211399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,453 [classy] Computing new state
 2023-07-02 10:24:30,453 [classy] Setting parameters: {'Omega_m': 0.4441384854211399, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,499 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.84954734478455}
 2023-07-02 10:24:30,500 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,501 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.793744
 2023-07-02 10:24:30,501 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,501 [mcmc] New sample, #202:
   Omega_m:0.4094593
 2023-07-02 10:24:30,502 [model] Posterior to be computed for parameters {'Omega_m': 0.14298380621549012}
 2023-07-02 10:24:30,502 [prior] Evaluating prior at array([0.14298381])
 2023-07-02 10:24:30,502 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,502 [model] Got input parameters: {'Omega_m': 0.14298380621549012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,502 [classy] Got parameters {'Omega_m': 0.14298380621549012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,502 [classy] Computing new state
 2023-07-02 10:24:30,502 [classy] Setting parameters: {'Omega_m': 0.14298380621549012, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.62579877364738}
 2023-07-02 10:24:30,549 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,551 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.94319
 2023-07-02 10:24:30,551 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,551 [model] Posterior to be computed for parameters {'Omega_m': 0.5780826341881788}
 2023-07-02 10:24:30,551 [prior] Evaluating prior at array([0.57808263])
 2023-07-02 10:24:30,551 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,551 [model] Got input parameters: {'Omega_m': 0.5780826341881788, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,551 [classy] Got parameters {'Omega_m': 0.5780826341881788, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,551 [classy] Computing new state
 2023-07-02 10:24:30,551 [classy] Setting parameters: {'Omega_m': 0.5780826341881788, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.70371322695571}
 2023-07-02 10:24:30,598 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.53242
 2023-07-02 10:24:30,600 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,600 [model] Posterior to be computed for parameters {'Omega_m': 0.5877231945791805}
 2023-07-02 10:24:30,600 [prior] Evaluating prior at array([0.58772319])
 2023-07-02 10:24:30,601 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,601 [model] Got input parameters: {'Omega_m': 0.5877231945791805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,601 [classy] Got parameters {'Omega_m': 0.5877231945791805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,601 [classy] Computing new state
 2023-07-02 10:24:30,601 [classy] Setting parameters: {'Omega_m': 0.5877231945791805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,648 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.06891222441007}
 2023-07-02 10:24:30,648 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,650 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.6766
 2023-07-02 10:24:30,650 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,650 [model] Posterior to be computed for parameters {'Omega_m': 0.6088468355592735}
 2023-07-02 10:24:30,650 [prior] Evaluating prior at array([0.60884684])
 2023-07-02 10:24:30,650 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,650 [model] Got input parameters: {'Omega_m': 0.6088468355592735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,650 [classy] Got parameters {'Omega_m': 0.6088468355592735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,650 [classy] Computing new state
 2023-07-02 10:24:30,650 [classy] Setting parameters: {'Omega_m': 0.6088468355592735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.71523923051315}
 2023-07-02 10:24:30,698 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,700 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.99859
 2023-07-02 10:24:30,700 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,700 [model] Posterior to be computed for parameters {'Omega_m': 0.4496948047295908}
 2023-07-02 10:24:30,700 [prior] Evaluating prior at array([0.4496948])
 2023-07-02 10:24:30,700 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,700 [model] Got input parameters: {'Omega_m': 0.4496948047295908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,700 [classy] Got parameters {'Omega_m': 0.4496948047295908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,700 [classy] Computing new state
 2023-07-02 10:24:30,700 [classy] Setting parameters: {'Omega_m': 0.4496948047295908, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.37098705090028}
 2023-07-02 10:24:30,747 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,749 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.852693
 2023-07-02 10:24:30,749 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,749 [mcmc] New sample, #203:
   Omega_m:0.4441385
 2023-07-02 10:24:30,749 [model] Posterior to be computed for parameters {'Omega_m': 0.7592819383855134}
 2023-07-02 10:24:30,749 [prior] Evaluating prior at array([0.75928194])
 2023-07-02 10:24:30,749 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,749 [model] Got input parameters: {'Omega_m': 0.7592819383855134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,749 [classy] Got parameters {'Omega_m': 0.7592819383855134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,749 [classy] Computing new state
 2023-07-02 10:24:30,749 [classy] Setting parameters: {'Omega_m': 0.7592819383855134, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.3192500866383}
 2023-07-02 10:24:30,796 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.45657
 2023-07-02 10:24:30,798 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,798 [model] Posterior to be computed for parameters {'Omega_m': 0.5846212824845307}
 2023-07-02 10:24:30,798 [prior] Evaluating prior at array([0.58462128])
 2023-07-02 10:24:30,798 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,798 [model] Got input parameters: {'Omega_m': 0.5846212824845307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,798 [classy] Got parameters {'Omega_m': 0.5846212824845307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,798 [classy] Computing new state
 2023-07-02 10:24:30,798 [classy] Setting parameters: {'Omega_m': 0.5846212824845307, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.27196649181626}
 2023-07-02 10:24:30,845 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.63002
 2023-07-02 10:24:30,847 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,847 [mcmc] New sample, #204:
   Omega_m:0.4496948
 2023-07-02 10:24:30,848 [model] Posterior to be computed for parameters {'Omega_m': 0.4125472726067002}
 2023-07-02 10:24:30,848 [prior] Evaluating prior at array([0.41254727])
 2023-07-02 10:24:30,848 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,848 [model] Got input parameters: {'Omega_m': 0.4125472726067002, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,848 [classy] Got parameters {'Omega_m': 0.4125472726067002, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,848 [classy] Computing new state
 2023-07-02 10:24:30,848 [classy] Setting parameters: {'Omega_m': 0.4125472726067002, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,896 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.6864804978648}
 2023-07-02 10:24:30,896 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,898 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.48911
 2023-07-02 10:24:30,898 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,898 [mcmc] New sample, #205:
   Omega_m:0.5846213
 2023-07-02 10:24:30,898 [model] Posterior to be computed for parameters {'Omega_m': 0.4910212406897691}
 2023-07-02 10:24:30,898 [prior] Evaluating prior at array([0.49102124])
 2023-07-02 10:24:30,898 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,898 [model] Got input parameters: {'Omega_m': 0.4910212406897691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,898 [classy] Got parameters {'Omega_m': 0.4910212406897691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,898 [classy] Computing new state
 2023-07-02 10:24:30,898 [classy] Setting parameters: {'Omega_m': 0.4910212406897691, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.9845895086321}
 2023-07-02 10:24:30,947 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,948 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.33365
 2023-07-02 10:24:30,949 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,949 [mcmc] New sample, #206:
   Omega_m:0.4125473
 2023-07-02 10:24:30,949 [model] Posterior to be computed for parameters {'Omega_m': 0.42290287760102485}
 2023-07-02 10:24:30,949 [prior] Evaluating prior at array([0.42290288])
 2023-07-02 10:24:30,949 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,949 [model] Got input parameters: {'Omega_m': 0.42290287760102485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,949 [classy] Got parameters {'Omega_m': 0.42290287760102485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,949 [classy] Computing new state
 2023-07-02 10:24:30,949 [classy] Setting parameters: {'Omega_m': 0.42290287760102485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:30,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.73400938536898}
 2023-07-02 10:24:30,996 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:30,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.582902
 2023-07-02 10:24:30,998 [model] Computed derived parameters: {}
 2023-07-02 10:24:30,998 [mcmc] New sample, #207:
   Omega_m:0.4910212
 2023-07-02 10:24:30,998 [model] Posterior to be computed for parameters {'Omega_m': 1.0275799849851428}
 2023-07-02 10:24:30,998 [prior] Evaluating prior at array([1.02757998])
 2023-07-02 10:24:30,998 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:30,999 [model] Posterior to be computed for parameters {'Omega_m': 0.4741551942600836}
 2023-07-02 10:24:30,999 [prior] Evaluating prior at array([0.47415519])
 2023-07-02 10:24:30,999 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:30,999 [model] Got input parameters: {'Omega_m': 0.4741551942600836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,999 [classy] Got parameters {'Omega_m': 0.4741551942600836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:30,999 [classy] Computing new state
 2023-07-02 10:24:30,999 [classy] Setting parameters: {'Omega_m': 0.4741551942600836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.3311402707497}
 2023-07-02 10:24:31,048 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.1289
 2023-07-02 10:24:31,050 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,050 [mcmc] New sample, #208:
   Omega_m:0.4229029
 2023-07-02 10:24:31,050 [model] Posterior to be computed for parameters {'Omega_m': 0.25800103099466554}
 2023-07-02 10:24:31,050 [prior] Evaluating prior at array([0.25800103])
 2023-07-02 10:24:31,050 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,050 [model] Got input parameters: {'Omega_m': 0.25800103099466554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,050 [classy] Got parameters {'Omega_m': 0.25800103099466554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,050 [classy] Computing new state
 2023-07-02 10:24:31,050 [classy] Setting parameters: {'Omega_m': 0.25800103099466554, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,097 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.37484695687075}
 2023-07-02 10:24:31,097 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,099 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.21026
 2023-07-02 10:24:31,099 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,100 [mcmc] New sample, #209:
   Omega_m:0.4741552
 2023-07-02 10:24:31,100 [model] Posterior to be computed for parameters {'Omega_m': 0.09595403832211036}
 2023-07-02 10:24:31,100 [prior] Evaluating prior at array([0.09595404])
 2023-07-02 10:24:31,100 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,100 [model] Posterior to be computed for parameters {'Omega_m': 0.4288716374893335}
 2023-07-02 10:24:31,100 [prior] Evaluating prior at array([0.42887164])
 2023-07-02 10:24:31,100 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,100 [model] Got input parameters: {'Omega_m': 0.4288716374893335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,100 [classy] Got parameters {'Omega_m': 0.4288716374893335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,100 [classy] Computing new state
 2023-07-02 10:24:31,100 [classy] Setting parameters: {'Omega_m': 0.4288716374893335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.19522580392893}
 2023-07-02 10:24:31,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.639736
 2023-07-02 10:24:31,149 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,149 [mcmc] New sample, #210:
   Omega_m:0.258001
 2023-07-02 10:24:31,150 [model] Posterior to be computed for parameters {'Omega_m': 0.6144137273158524}
 2023-07-02 10:24:31,150 [prior] Evaluating prior at array([0.61441373])
 2023-07-02 10:24:31,150 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,150 [model] Got input parameters: {'Omega_m': 0.6144137273158524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,150 [classy] Got parameters {'Omega_m': 0.6144137273158524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,150 [classy] Computing new state
 2023-07-02 10:24:31,150 [classy] Setting parameters: {'Omega_m': 0.6144137273158524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.36669930040973}
 2023-07-02 10:24:31,199 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,201 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.08473
 2023-07-02 10:24:31,201 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,201 [model] Posterior to be computed for parameters {'Omega_m': 0.6372338092097729}
 2023-07-02 10:24:31,201 [prior] Evaluating prior at array([0.63723381])
 2023-07-02 10:24:31,201 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,201 [model] Got input parameters: {'Omega_m': 0.6372338092097729, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,201 [classy] Got parameters {'Omega_m': 0.6372338092097729, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,201 [classy] Computing new state
 2023-07-02 10:24:31,201 [classy] Setting parameters: {'Omega_m': 0.6372338092097729, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,247 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.97190396094658}
 2023-07-02 10:24:31,247 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.44287
 2023-07-02 10:24:31,248 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,249 [model] Posterior to be computed for parameters {'Omega_m': 0.7474858842956685}
 2023-07-02 10:24:31,249 [prior] Evaluating prior at array([0.74748588])
 2023-07-02 10:24:31,249 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,249 [model] Got input parameters: {'Omega_m': 0.7474858842956685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,249 [classy] Got parameters {'Omega_m': 0.7474858842956685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,249 [classy] Computing new state
 2023-07-02 10:24:31,249 [classy] Setting parameters: {'Omega_m': 0.7474858842956685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.90970047286305}
 2023-07-02 10:24:31,295 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.25681
 2023-07-02 10:24:31,297 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,297 [model] Posterior to be computed for parameters {'Omega_m': 0.025480139707055982}
 2023-07-02 10:24:31,297 [prior] Evaluating prior at array([0.02548014])
 2023-07-02 10:24:31,297 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,298 [model] Posterior to be computed for parameters {'Omega_m': 0.17670400208050535}
 2023-07-02 10:24:31,298 [prior] Evaluating prior at array([0.176704])
 2023-07-02 10:24:31,298 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,298 [model] Got input parameters: {'Omega_m': 0.17670400208050535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,298 [classy] Got parameters {'Omega_m': 0.17670400208050535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,298 [classy] Computing new state
 2023-07-02 10:24:31,298 [classy] Setting parameters: {'Omega_m': 0.17670400208050535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.71543062241756}
 2023-07-02 10:24:31,345 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.67455
 2023-07-02 10:24:31,347 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,347 [model] Posterior to be computed for parameters {'Omega_m': 0.7410241377155051}
 2023-07-02 10:24:31,347 [prior] Evaluating prior at array([0.74102414])
 2023-07-02 10:24:31,347 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,347 [model] Got input parameters: {'Omega_m': 0.7410241377155051, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,347 [classy] Got parameters {'Omega_m': 0.7410241377155051, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,347 [classy] Computing new state
 2023-07-02 10:24:31,347 [classy] Setting parameters: {'Omega_m': 0.7410241377155051, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,392 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.23750355048745}
 2023-07-02 10:24:31,393 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,394 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.1477
 2023-07-02 10:24:31,394 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,394 [model] Posterior to be computed for parameters {'Omega_m': 0.40250901173834935}
 2023-07-02 10:24:31,394 [prior] Evaluating prior at array([0.40250901])
 2023-07-02 10:24:31,395 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,395 [model] Got input parameters: {'Omega_m': 0.40250901173834935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,395 [classy] Got parameters {'Omega_m': 0.40250901173834935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,395 [classy] Computing new state
 2023-07-02 10:24:31,395 [classy] Setting parameters: {'Omega_m': 0.40250901173834935, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,441 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.63191361364528}
 2023-07-02 10:24:31,441 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.404393
 2023-07-02 10:24:31,443 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,443 [mcmc] New sample, #211:
   Omega_m:0.4288716
 2023-07-02 10:24:31,443 [model] Posterior to be computed for parameters {'Omega_m': 0.22511625774384023}
 2023-07-02 10:24:31,443 [prior] Evaluating prior at array([0.22511626])
 2023-07-02 10:24:31,444 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,444 [model] Got input parameters: {'Omega_m': 0.22511625774384023, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,444 [classy] Got parameters {'Omega_m': 0.22511625774384023, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,444 [classy] Computing new state
 2023-07-02 10:24:31,444 [classy] Setting parameters: {'Omega_m': 0.22511625774384023, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.30642796073212}
 2023-07-02 10:24:31,490 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.594197
 2023-07-02 10:24:31,492 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,492 [mcmc] New sample, #212:
   Omega_m:0.402509
 2023-07-02 10:24:31,492 [model] Posterior to be computed for parameters {'Omega_m': 0.6222113997661323}
 2023-07-02 10:24:31,492 [prior] Evaluating prior at array([0.6222114])
 2023-07-02 10:24:31,492 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,492 [model] Got input parameters: {'Omega_m': 0.6222113997661323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,492 [classy] Got parameters {'Omega_m': 0.6222113997661323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,492 [classy] Computing new state
 2023-07-02 10:24:31,492 [classy] Setting parameters: {'Omega_m': 0.6222113997661323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.88401794168351}
 2023-07-02 10:24:31,539 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,540 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.20623
 2023-07-02 10:24:31,541 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,541 [model] Posterior to be computed for parameters {'Omega_m': 0.3525670562097206}
 2023-07-02 10:24:31,541 [prior] Evaluating prior at array([0.35256706])
 2023-07-02 10:24:31,541 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,541 [model] Got input parameters: {'Omega_m': 0.3525670562097206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,541 [classy] Got parameters {'Omega_m': 0.3525670562097206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,541 [classy] Computing new state
 2023-07-02 10:24:31,541 [classy] Setting parameters: {'Omega_m': 0.3525670562097206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,588 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.69433305990663}
 2023-07-02 10:24:31,588 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,590 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0896969
 2023-07-02 10:24:31,590 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,590 [mcmc] New sample, #213:
   Omega_m:0.2251163
 2023-07-02 10:24:31,590 [model] Posterior to be computed for parameters {'Omega_m': 0.06835437233581043}
 2023-07-02 10:24:31,590 [prior] Evaluating prior at array([0.06835437])
 2023-07-02 10:24:31,590 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,590 [model] Posterior to be computed for parameters {'Omega_m': 0.46154693755984616}
 2023-07-02 10:24:31,590 [prior] Evaluating prior at array([0.46154694])
 2023-07-02 10:24:31,590 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,590 [model] Got input parameters: {'Omega_m': 0.46154693755984616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,590 [classy] Got parameters {'Omega_m': 0.46154693755984616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,590 [classy] Computing new state
 2023-07-02 10:24:31,590 [classy] Setting parameters: {'Omega_m': 0.46154693755984616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,637 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.3692622688547}
 2023-07-02 10:24:31,637 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,638 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.983261
 2023-07-02 10:24:31,639 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,639 [mcmc] New sample, #214:
   Omega_m:0.3525671
 2023-07-02 10:24:31,639 [model] Posterior to be computed for parameters {'Omega_m': 0.5015665817715478}
 2023-07-02 10:24:31,639 [prior] Evaluating prior at array([0.50156658])
 2023-07-02 10:24:31,639 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,639 [model] Got input parameters: {'Omega_m': 0.5015665817715478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,639 [classy] Got parameters {'Omega_m': 0.5015665817715478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,639 [classy] Computing new state
 2023-07-02 10:24:31,639 [classy] Setting parameters: {'Omega_m': 0.5015665817715478, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,687 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.1660120798404}
 2023-07-02 10:24:31,687 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,688 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.46696
 2023-07-02 10:24:31,688 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,688 [model] Posterior to be computed for parameters {'Omega_m': 0.06170264801410158}
 2023-07-02 10:24:31,689 [prior] Evaluating prior at array([0.06170265])
 2023-07-02 10:24:31,689 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,689 [model] Posterior to be computed for parameters {'Omega_m': 0.1371097498100874}
 2023-07-02 10:24:31,689 [prior] Evaluating prior at array([0.13710975])
 2023-07-02 10:24:31,689 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,689 [model] Got input parameters: {'Omega_m': 0.1371097498100874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,689 [classy] Got parameters {'Omega_m': 0.1371097498100874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,689 [classy] Computing new state
 2023-07-02 10:24:31,689 [classy] Setting parameters: {'Omega_m': 0.1371097498100874, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.93953038852771}
 2023-07-02 10:24:31,735 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,737 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.22158
 2023-07-02 10:24:31,737 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,737 [mcmc] New sample, #215:
   Omega_m:0.4615469
 2023-07-02 10:24:31,737 [model] Posterior to be computed for parameters {'Omega_m': 0.11477095070434704}
 2023-07-02 10:24:31,737 [prior] Evaluating prior at array([0.11477095])
 2023-07-02 10:24:31,737 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,737 [model] Got input parameters: {'Omega_m': 0.11477095070434704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,737 [classy] Got parameters {'Omega_m': 0.11477095070434704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,737 [classy] Computing new state
 2023-07-02 10:24:31,737 [classy] Setting parameters: {'Omega_m': 0.11477095070434704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 181.28947726684834}
 2023-07-02 10:24:31,782 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.47376
 2023-07-02 10:24:31,784 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,784 [mcmc] New sample, #216:
   Omega_m:0.1371097
 2023-07-02 10:24:31,785 [model] Posterior to be computed for parameters {'Omega_m': 0.056568275142955066}
 2023-07-02 10:24:31,785 [prior] Evaluating prior at array([0.05656828])
 2023-07-02 10:24:31,785 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,785 [model] Posterior to be computed for parameters {'Omega_m': 0.19699181886933703}
 2023-07-02 10:24:31,785 [prior] Evaluating prior at array([0.19699182])
 2023-07-02 10:24:31,785 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,785 [model] Got input parameters: {'Omega_m': 0.19699181886933703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,785 [classy] Got parameters {'Omega_m': 0.19699181886933703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,785 [classy] Computing new state
 2023-07-02 10:24:31,785 [classy] Setting parameters: {'Omega_m': 0.19699181886933703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,830 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.0018385280909}
 2023-07-02 10:24:31,830 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.13296
 2023-07-02 10:24:31,832 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,832 [mcmc] New sample, #217:
   Omega_m:0.114771
 2023-07-02 10:24:31,833 [model] Posterior to be computed for parameters {'Omega_m': -0.128973361162794}
 2023-07-02 10:24:31,833 [prior] Evaluating prior at array([-0.12897336])
 2023-07-02 10:24:31,833 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,833 [model] Posterior to be computed for parameters {'Omega_m': 0.3149837179339865}
 2023-07-02 10:24:31,833 [prior] Evaluating prior at array([0.31498372])
 2023-07-02 10:24:31,833 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,833 [model] Got input parameters: {'Omega_m': 0.3149837179339865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,833 [classy] Got parameters {'Omega_m': 0.3149837179339865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,833 [classy] Computing new state
 2023-07-02 10:24:31,833 [classy] Setting parameters: {'Omega_m': 0.3149837179339865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96038851820035}
 2023-07-02 10:24:31,879 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000583307
 2023-07-02 10:24:31,881 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,882 [mcmc] New sample, #218:
   Omega_m:0.1969918
 2023-07-02 10:24:31,882 [model] Posterior to be computed for parameters {'Omega_m': 0.7898587727972055}
 2023-07-02 10:24:31,882 [prior] Evaluating prior at array([0.78985877])
 2023-07-02 10:24:31,882 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,882 [model] Got input parameters: {'Omega_m': 0.7898587727972055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,882 [classy] Got parameters {'Omega_m': 0.7898587727972055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,882 [classy] Computing new state
 2023-07-02 10:24:31,882 [classy] Setting parameters: {'Omega_m': 0.7898587727972055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,927 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.83440036181766}
 2023-07-02 10:24:31,927 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,929 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.97771
 2023-07-02 10:24:31,929 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,929 [model] Posterior to be computed for parameters {'Omega_m': -0.011094309867537677}
 2023-07-02 10:24:31,929 [prior] Evaluating prior at array([-0.01109431])
 2023-07-02 10:24:31,929 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:31,929 [model] Posterior to be computed for parameters {'Omega_m': 0.6330035361536757}
 2023-07-02 10:24:31,929 [prior] Evaluating prior at array([0.63300354])
 2023-07-02 10:24:31,929 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,929 [model] Got input parameters: {'Omega_m': 0.6330035361536757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,929 [classy] Got parameters {'Omega_m': 0.6330035361536757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,929 [classy] Computing new state
 2023-07-02 10:24:31,929 [classy] Setting parameters: {'Omega_m': 0.6330035361536757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:31,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.22643530201442}
 2023-07-02 10:24:31,974 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:31,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.3759
 2023-07-02 10:24:31,976 [model] Computed derived parameters: {}
 2023-07-02 10:24:31,976 [model] Posterior to be computed for parameters {'Omega_m': 0.3790015944150532}
 2023-07-02 10:24:31,976 [prior] Evaluating prior at array([0.37900159])
 2023-07-02 10:24:31,977 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:31,977 [model] Got input parameters: {'Omega_m': 0.3790015944150532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,977 [classy] Got parameters {'Omega_m': 0.3790015944150532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:31,977 [classy] Computing new state
 2023-07-02 10:24:31,977 [classy] Setting parameters: {'Omega_m': 0.3790015944150532, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.93669904033018}
 2023-07-02 10:24:32,025 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,027 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.232387
 2023-07-02 10:24:32,027 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,028 [mcmc] New sample, #219:
   Omega_m:0.3149837
 2023-07-02 10:24:32,028 [model] Posterior to be computed for parameters {'Omega_m': -0.05493501885983937}
 2023-07-02 10:24:32,028 [prior] Evaluating prior at array([-0.05493502])
 2023-07-02 10:24:32,028 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,028 [model] Posterior to be computed for parameters {'Omega_m': 0.014414403899369821}
 2023-07-02 10:24:32,028 [prior] Evaluating prior at array([0.0144144])
 2023-07-02 10:24:32,028 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,028 [model] Posterior to be computed for parameters {'Omega_m': 0.37444104820366886}
 2023-07-02 10:24:32,028 [prior] Evaluating prior at array([0.37444105])
 2023-07-02 10:24:32,029 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,029 [model] Got input parameters: {'Omega_m': 0.37444104820366886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,029 [classy] Got parameters {'Omega_m': 0.37444104820366886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,029 [classy] Computing new state
 2023-07-02 10:24:32,029 [classy] Setting parameters: {'Omega_m': 0.37444104820366886, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.3993849707718}
 2023-07-02 10:24:32,077 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,079 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.203688
 2023-07-02 10:24:32,079 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,079 [mcmc] New sample, #220:
   Omega_m:0.3790016
 2023-07-02 10:24:32,079 [model] Posterior to be computed for parameters {'Omega_m': 0.35445990696561325}
 2023-07-02 10:24:32,079 [prior] Evaluating prior at array([0.35445991])
 2023-07-02 10:24:32,079 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,079 [model] Got input parameters: {'Omega_m': 0.35445990696561325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,079 [classy] Got parameters {'Omega_m': 0.35445990696561325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,079 [classy] Computing new state
 2023-07-02 10:24:32,079 [classy] Setting parameters: {'Omega_m': 0.35445990696561325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,126 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.49060846888224}
 2023-07-02 10:24:32,126 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0979216
 2023-07-02 10:24:32,128 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,128 [mcmc] New sample, #221:
   Omega_m:0.374441
 2023-07-02 10:24:32,128 [model] Posterior to be computed for parameters {'Omega_m': 0.010407866457893045}
 2023-07-02 10:24:32,128 [prior] Evaluating prior at array([0.01040787])
 2023-07-02 10:24:32,128 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,128 [model] Posterior to be computed for parameters {'Omega_m': 0.4372127213425229}
 2023-07-02 10:24:32,128 [prior] Evaluating prior at array([0.43721272])
 2023-07-02 10:24:32,129 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,129 [model] Got input parameters: {'Omega_m': 0.4372127213425229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,129 [classy] Got parameters {'Omega_m': 0.4372127213425229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,129 [classy] Computing new state
 2023-07-02 10:24:32,129 [classy] Setting parameters: {'Omega_m': 0.4372127213425229, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,176 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.4543351311791}
 2023-07-02 10:24:32,177 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,179 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.72239
 2023-07-02 10:24:32,179 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,179 [model] Posterior to be computed for parameters {'Omega_m': -0.028788031729014063}
 2023-07-02 10:24:32,179 [prior] Evaluating prior at array([-0.02878803])
 2023-07-02 10:24:32,179 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,179 [model] Posterior to be computed for parameters {'Omega_m': 0.13942951698460262}
 2023-07-02 10:24:32,179 [prior] Evaluating prior at array([0.13942952])
 2023-07-02 10:24:32,179 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,179 [model] Got input parameters: {'Omega_m': 0.13942951698460262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,179 [classy] Got parameters {'Omega_m': 0.13942951698460262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,179 [classy] Computing new state
 2023-07-02 10:24:32,179 [classy] Setting parameters: {'Omega_m': 0.13942951698460262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.41639018254972}
 2023-07-02 10:24:32,226 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,228 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.10932
 2023-07-02 10:24:32,228 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,229 [model] Posterior to be computed for parameters {'Omega_m': 1.1306563201067692}
 2023-07-02 10:24:32,229 [prior] Evaluating prior at array([1.13065632])
 2023-07-02 10:24:32,229 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,229 [model] Posterior to be computed for parameters {'Omega_m': 0.5987534654370779}
 2023-07-02 10:24:32,229 [prior] Evaluating prior at array([0.59875347])
 2023-07-02 10:24:32,229 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,229 [model] Got input parameters: {'Omega_m': 0.5987534654370779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,229 [classy] Got parameters {'Omega_m': 0.5987534654370779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,229 [classy] Computing new state
 2023-07-02 10:24:32,229 [classy] Setting parameters: {'Omega_m': 0.5987534654370779, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.35582537489515}
 2023-07-02 10:24:32,276 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.84373
 2023-07-02 10:24:32,278 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,278 [model] Posterior to be computed for parameters {'Omega_m': 0.5729794005909123}
 2023-07-02 10:24:32,279 [prior] Evaluating prior at array([0.5729794])
 2023-07-02 10:24:32,279 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,279 [model] Got input parameters: {'Omega_m': 0.5729794005909123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,279 [classy] Got parameters {'Omega_m': 0.5729794005909123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,279 [classy] Computing new state
 2023-07-02 10:24:32,279 [classy] Setting parameters: {'Omega_m': 0.5729794005909123, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,325 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.0442080950109}
 2023-07-02 10:24:32,325 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,327 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.45687
 2023-07-02 10:24:32,327 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,327 [model] Posterior to be computed for parameters {'Omega_m': 0.3275877786593559}
 2023-07-02 10:24:32,327 [prior] Evaluating prior at array([0.32758778])
 2023-07-02 10:24:32,327 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,327 [model] Got input parameters: {'Omega_m': 0.3275877786593559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,327 [classy] Got parameters {'Omega_m': 0.3275877786593559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,327 [classy] Computing new state
 2023-07-02 10:24:32,328 [classy] Setting parameters: {'Omega_m': 0.3275877786593559, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,375 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.48075793743797}
 2023-07-02 10:24:32,375 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,378 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0136823
 2023-07-02 10:24:32,378 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,378 [mcmc] New sample, #222:
   Omega_m:0.3544599
 2023-07-02 10:24:32,378 [model] Posterior to be computed for parameters {'Omega_m': 0.5312377323801267}
 2023-07-02 10:24:32,378 [prior] Evaluating prior at array([0.53123773])
 2023-07-02 10:24:32,378 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,378 [model] Got input parameters: {'Omega_m': 0.5312377323801267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,378 [classy] Got parameters {'Omega_m': 0.5312377323801267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,378 [classy] Computing new state
 2023-07-02 10:24:32,378 [classy] Setting parameters: {'Omega_m': 0.5312377323801267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.95277388258557}
 2023-07-02 10:24:32,425 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,427 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.8614
 2023-07-02 10:24:32,427 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,427 [model] Posterior to be computed for parameters {'Omega_m': -0.08690170860879098}
 2023-07-02 10:24:32,427 [prior] Evaluating prior at array([-0.08690171])
 2023-07-02 10:24:32,428 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,428 [model] Posterior to be computed for parameters {'Omega_m': 0.8466787969089373}
 2023-07-02 10:24:32,428 [prior] Evaluating prior at array([0.8466788])
 2023-07-02 10:24:32,428 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,428 [model] Got input parameters: {'Omega_m': 0.8466787969089373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,428 [classy] Got parameters {'Omega_m': 0.8466787969089373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,428 [classy] Computing new state
 2023-07-02 10:24:32,428 [classy] Setting parameters: {'Omega_m': 0.8466787969089373, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.23687875386601}
 2023-07-02 10:24:32,474 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.95515
 2023-07-02 10:24:32,476 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,476 [model] Posterior to be computed for parameters {'Omega_m': 0.06326783462421692}
 2023-07-02 10:24:32,476 [prior] Evaluating prior at array([0.06326783])
 2023-07-02 10:24:32,476 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,476 [model] Posterior to be computed for parameters {'Omega_m': -0.07742049823993286}
 2023-07-02 10:24:32,477 [prior] Evaluating prior at array([-0.0774205])
 2023-07-02 10:24:32,477 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,477 [model] Posterior to be computed for parameters {'Omega_m': 0.2929580961679103}
 2023-07-02 10:24:32,477 [prior] Evaluating prior at array([0.2929581])
 2023-07-02 10:24:32,477 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,477 [model] Got input parameters: {'Omega_m': 0.2929580961679103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,477 [classy] Got parameters {'Omega_m': 0.2929580961679103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,477 [classy] Computing new state
 2023-07-02 10:24:32,477 [classy] Setting parameters: {'Omega_m': 0.2929580961679103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.67698059855854}
 2023-07-02 10:24:32,524 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,526 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247688
 2023-07-02 10:24:32,526 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,526 [mcmc] New sample, #223:
   Omega_m:0.3275878
 2023-07-02 10:24:32,526 [model] Posterior to be computed for parameters {'Omega_m': 0.24900554767871463}
 2023-07-02 10:24:32,526 [prior] Evaluating prior at array([0.24900555])
 2023-07-02 10:24:32,526 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,526 [model] Got input parameters: {'Omega_m': 0.24900554767871463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,526 [classy] Got parameters {'Omega_m': 0.24900554767871463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,526 [classy] Computing new state
 2023-07-02 10:24:32,526 [classy] Setting parameters: {'Omega_m': 0.24900554767871463, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.67026826376588}
 2023-07-02 10:24:32,575 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.292654
 2023-07-02 10:24:32,577 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,577 [mcmc] New sample, #224:
   Omega_m:0.2929581
 2023-07-02 10:24:32,577 [model] Posterior to be computed for parameters {'Omega_m': 0.12053604369995527}
 2023-07-02 10:24:32,577 [prior] Evaluating prior at array([0.12053604])
 2023-07-02 10:24:32,577 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,578 [model] Got input parameters: {'Omega_m': 0.12053604369995527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,578 [classy] Got parameters {'Omega_m': 0.12053604369995527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,578 [classy] Computing new state
 2023-07-02 10:24:32,578 [classy] Setting parameters: {'Omega_m': 0.12053604369995527, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.85143618228784}
 2023-07-02 10:24:32,625 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.11873
 2023-07-02 10:24:32,627 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,627 [model] Posterior to be computed for parameters {'Omega_m': 0.35619731640537233}
 2023-07-02 10:24:32,627 [prior] Evaluating prior at array([0.35619732])
 2023-07-02 10:24:32,627 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,627 [model] Got input parameters: {'Omega_m': 0.35619731640537233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,627 [classy] Got parameters {'Omega_m': 0.35619731640537233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,627 [classy] Computing new state
 2023-07-02 10:24:32,627 [classy] Setting parameters: {'Omega_m': 0.35619731640537233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.30448975792928}
 2023-07-02 10:24:32,674 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,676 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105756
 2023-07-02 10:24:32,676 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,676 [mcmc] New sample, #225:
   Omega_m:0.2490055
 2023-07-02 10:24:32,676 [model] Posterior to be computed for parameters {'Omega_m': -0.14203509696661865}
 2023-07-02 10:24:32,676 [prior] Evaluating prior at array([-0.1420351])
 2023-07-02 10:24:32,676 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,677 [model] Posterior to be computed for parameters {'Omega_m': 0.22272736046232783}
 2023-07-02 10:24:32,677 [prior] Evaluating prior at array([0.22272736])
 2023-07-02 10:24:32,677 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,677 [model] Got input parameters: {'Omega_m': 0.22272736046232783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,677 [classy] Got parameters {'Omega_m': 0.22272736046232783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,677 [classy] Computing new state
 2023-07-02 10:24:32,677 [classy] Setting parameters: {'Omega_m': 0.22272736046232783, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,725 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.68684505707603}
 2023-07-02 10:24:32,725 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,726 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.631646
 2023-07-02 10:24:32,726 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,726 [mcmc] New sample, #226:
   Omega_m:0.3561973
 2023-07-02 10:24:32,727 [model] Posterior to be computed for parameters {'Omega_m': 0.2420100057978665}
 2023-07-02 10:24:32,727 [prior] Evaluating prior at array([0.24201001])
 2023-07-02 10:24:32,727 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,727 [model] Got input parameters: {'Omega_m': 0.2420100057978665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,727 [classy] Got parameters {'Omega_m': 0.2420100057978665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,727 [classy] Computing new state
 2023-07-02 10:24:32,727 [classy] Setting parameters: {'Omega_m': 0.2420100057978665, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.70462966349186}
 2023-07-02 10:24:32,775 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,777 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.367954
 2023-07-02 10:24:32,777 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,778 [mcmc] New sample, #227:
   Omega_m:0.2227274
 2023-07-02 10:24:32,778 [model] Posterior to be computed for parameters {'Omega_m': -0.2880944412945442}
 2023-07-02 10:24:32,778 [prior] Evaluating prior at array([-0.28809444])
 2023-07-02 10:24:32,778 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,778 [model] Posterior to be computed for parameters {'Omega_m': 0.17376400957053717}
 2023-07-02 10:24:32,778 [prior] Evaluating prior at array([0.17376401])
 2023-07-02 10:24:32,778 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,778 [model] Got input parameters: {'Omega_m': 0.17376400957053717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,778 [classy] Got parameters {'Omega_m': 0.17376400957053717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,778 [classy] Computing new state
 2023-07-02 10:24:32,778 [classy] Setting parameters: {'Omega_m': 0.17376400957053717, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,825 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.2791009955139}
 2023-07-02 10:24:32,825 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.76546
 2023-07-02 10:24:32,827 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,827 [model] Posterior to be computed for parameters {'Omega_m': 0.37607891751964456}
 2023-07-02 10:24:32,827 [prior] Evaluating prior at array([0.37607892])
 2023-07-02 10:24:32,828 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,828 [model] Got input parameters: {'Omega_m': 0.37607891751964456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,828 [classy] Got parameters {'Omega_m': 0.37607891751964456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,828 [classy] Computing new state
 2023-07-02 10:24:32,828 [classy] Setting parameters: {'Omega_m': 0.37607891751964456, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.2326036317528}
 2023-07-02 10:24:32,875 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,876 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.213811
 2023-07-02 10:24:32,876 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,876 [mcmc] New sample, #228:
   Omega_m:0.24201
 2023-07-02 10:24:32,877 [model] Posterior to be computed for parameters {'Omega_m': 0.24173620959475497}
 2023-07-02 10:24:32,877 [prior] Evaluating prior at array([0.24173621])
 2023-07-02 10:24:32,877 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,877 [model] Got input parameters: {'Omega_m': 0.24173620959475497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,877 [classy] Got parameters {'Omega_m': 0.24173620959475497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,877 [classy] Computing new state
 2023-07-02 10:24:32,877 [classy] Setting parameters: {'Omega_m': 0.24173620959475497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.74560690621124}
 2023-07-02 10:24:32,923 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,925 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.371109
 2023-07-02 10:24:32,925 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,925 [mcmc] New sample, #229:
   Omega_m:0.3760789
 2023-07-02 10:24:32,925 [model] Posterior to be computed for parameters {'Omega_m': 0.4630671777635974}
 2023-07-02 10:24:32,926 [prior] Evaluating prior at array([0.46306718])
 2023-07-02 10:24:32,926 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,926 [model] Got input parameters: {'Omega_m': 0.4630671777635974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,926 [classy] Got parameters {'Omega_m': 0.4630671777635974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,926 [classy] Computing new state
 2023-07-02 10:24:32,926 [classy] Setting parameters: {'Omega_m': 0.4630671777635974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:32,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.24261779669033}
 2023-07-02 10:24:32,974 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:32,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.00046
 2023-07-02 10:24:32,976 [model] Computed derived parameters: {}
 2023-07-02 10:24:32,976 [mcmc] New sample, #230:
   Omega_m:0.2417362
 2023-07-02 10:24:32,976 [model] Posterior to be computed for parameters {'Omega_m': -0.04617548613570244}
 2023-07-02 10:24:32,976 [prior] Evaluating prior at array([-0.04617549])
 2023-07-02 10:24:32,976 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:32,976 [model] Posterior to be computed for parameters {'Omega_m': 0.5084495329767831}
 2023-07-02 10:24:32,976 [prior] Evaluating prior at array([0.50844953])
 2023-07-02 10:24:32,976 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:32,976 [model] Got input parameters: {'Omega_m': 0.5084495329767831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,976 [classy] Got parameters {'Omega_m': 0.5084495329767831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:32,976 [classy] Computing new state
 2023-07-02 10:24:32,976 [classy] Setting parameters: {'Omega_m': 0.5084495329767831, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,024 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.64099228377574}
 2023-07-02 10:24:33,024 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,025 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.55602
 2023-07-02 10:24:33,026 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,026 [model] Posterior to be computed for parameters {'Omega_m': 0.45372739983027693}
 2023-07-02 10:24:33,026 [prior] Evaluating prior at array([0.4537274])
 2023-07-02 10:24:33,026 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,026 [model] Got input parameters: {'Omega_m': 0.45372739983027693, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,026 [classy] Got parameters {'Omega_m': 0.45372739983027693, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,026 [classy] Computing new state
 2023-07-02 10:24:33,026 [classy] Setting parameters: {'Omega_m': 0.45372739983027693, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.02726825839167}
 2023-07-02 10:24:33,073 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.896399
 2023-07-02 10:24:33,075 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,075 [mcmc] New sample, #231:
   Omega_m:0.4630672
 2023-07-02 10:24:33,075 [model] Posterior to be computed for parameters {'Omega_m': 0.13922503701932348}
 2023-07-02 10:24:33,075 [prior] Evaluating prior at array([0.13922504])
 2023-07-02 10:24:33,075 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,075 [model] Got input parameters: {'Omega_m': 0.13922503701932348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,075 [classy] Got parameters {'Omega_m': 0.13922503701932348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,075 [classy] Computing new state
 2023-07-02 10:24:33,075 [classy] Setting parameters: {'Omega_m': 0.13922503701932348, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,121 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.46227642795697}
 2023-07-02 10:24:33,122 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,123 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.1191
 2023-07-02 10:24:33,123 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,123 [model] Posterior to be computed for parameters {'Omega_m': 0.6681493144498616}
 2023-07-02 10:24:33,123 [prior] Evaluating prior at array([0.66814931])
 2023-07-02 10:24:33,124 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,124 [model] Got input parameters: {'Omega_m': 0.6681493144498616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,124 [classy] Got parameters {'Omega_m': 0.6681493144498616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,124 [classy] Computing new state
 2023-07-02 10:24:33,124 [classy] Setting parameters: {'Omega_m': 0.6681493144498616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.16460068319117}
 2023-07-02 10:24:33,170 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,172 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.93932
 2023-07-02 10:24:33,172 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,172 [model] Posterior to be computed for parameters {'Omega_m': 0.30842019410662236}
 2023-07-02 10:24:33,172 [prior] Evaluating prior at array([0.30842019])
 2023-07-02 10:24:33,172 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,172 [model] Got input parameters: {'Omega_m': 0.30842019410662236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,172 [classy] Got parameters {'Omega_m': 0.30842019410662236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,172 [classy] Computing new state
 2023-07-02 10:24:33,172 [classy] Setting parameters: {'Omega_m': 0.30842019410662236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75196195744363}
 2023-07-02 10:24:33,219 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,221 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00122548
 2023-07-02 10:24:33,221 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,221 [mcmc] New sample, #232:
   Omega_m:0.4537274
 2023-07-02 10:24:33,221 [model] Posterior to be computed for parameters {'Omega_m': 0.512447156396256}
 2023-07-02 10:24:33,221 [prior] Evaluating prior at array([0.51244716])
 2023-07-02 10:24:33,222 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,222 [model] Got input parameters: {'Omega_m': 0.512447156396256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,222 [classy] Got parameters {'Omega_m': 0.512447156396256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,222 [classy] Computing new state
 2023-07-02 10:24:33,222 [classy] Setting parameters: {'Omega_m': 0.512447156396256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.3393509652851}
 2023-07-02 10:24:33,268 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,270 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.60844
 2023-07-02 10:24:33,270 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,270 [model] Posterior to be computed for parameters {'Omega_m': 0.12771750202596754}
 2023-07-02 10:24:33,270 [prior] Evaluating prior at array([0.1277175])
 2023-07-02 10:24:33,270 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,270 [model] Got input parameters: {'Omega_m': 0.12771750202596754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,270 [classy] Got parameters {'Omega_m': 0.12771750202596754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,270 [classy] Computing new state
 2023-07-02 10:24:33,270 [classy] Setting parameters: {'Omega_m': 0.12771750202596754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 178.1175155376701}
 2023-07-02 10:24:33,317 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.7086
 2023-07-02 10:24:33,319 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,319 [model] Posterior to be computed for parameters {'Omega_m': 0.3192442160939121}
 2023-07-02 10:24:33,319 [prior] Evaluating prior at array([0.31924422])
 2023-07-02 10:24:33,319 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,319 [model] Got input parameters: {'Omega_m': 0.3192442160939121, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,319 [classy] Got parameters {'Omega_m': 0.3192442160939121, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,319 [classy] Computing new state
 2023-07-02 10:24:33,319 [classy] Setting parameters: {'Omega_m': 0.3192442160939121, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.45442538004215}
 2023-07-02 10:24:33,367 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,369 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00295811
 2023-07-02 10:24:33,369 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,369 [mcmc] New sample, #233:
   Omega_m:0.3084202
 2023-07-02 10:24:33,369 [model] Posterior to be computed for parameters {'Omega_m': -0.013384066519635696}
 2023-07-02 10:24:33,370 [prior] Evaluating prior at array([-0.01338407])
 2023-07-02 10:24:33,370 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,370 [model] Posterior to be computed for parameters {'Omega_m': 0.14284616853265178}
 2023-07-02 10:24:33,370 [prior] Evaluating prior at array([0.14284617])
 2023-07-02 10:24:33,370 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,370 [model] Got input parameters: {'Omega_m': 0.14284616853265178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,370 [classy] Got parameters {'Omega_m': 0.14284616853265178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,370 [classy] Computing new state
 2023-07-02 10:24:33,370 [classy] Setting parameters: {'Omega_m': 0.14284616853265178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.6561708028375}
 2023-07-02 10:24:33,417 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.94949
 2023-07-02 10:24:33,419 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,419 [model] Posterior to be computed for parameters {'Omega_m': 0.4335893109601029}
 2023-07-02 10:24:33,419 [prior] Evaluating prior at array([0.43358931])
 2023-07-02 10:24:33,419 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,419 [model] Got input parameters: {'Omega_m': 0.4335893109601029, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,419 [classy] Got parameters {'Omega_m': 0.4335893109601029, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,419 [classy] Computing new state
 2023-07-02 10:24:33,420 [classy] Setting parameters: {'Omega_m': 0.4335893109601029, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,467 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.77448732094166}
 2023-07-02 10:24:33,467 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,469 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.686032
 2023-07-02 10:24:33,469 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,469 [model] Posterior to be computed for parameters {'Omega_m': -0.1615018933220546}
 2023-07-02 10:24:33,469 [prior] Evaluating prior at array([-0.16150189])
 2023-07-02 10:24:33,469 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,470 [model] Posterior to be computed for parameters {'Omega_m': 0.2762744002800014}
 2023-07-02 10:24:33,470 [prior] Evaluating prior at array([0.2762744])
 2023-07-02 10:24:33,470 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,470 [model] Got input parameters: {'Omega_m': 0.2762744002800014, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,470 [classy] Got parameters {'Omega_m': 0.2762744002800014, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,470 [classy] Computing new state
 2023-07-02 10:24:33,470 [classy] Setting parameters: {'Omega_m': 0.2762744002800014, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.85576884001404}
 2023-07-02 10:24:33,517 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,519 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0884728
 2023-07-02 10:24:33,519 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,519 [mcmc] New sample, #234:
   Omega_m:0.3192442
 2023-07-02 10:24:33,519 [model] Posterior to be computed for parameters {'Omega_m': 0.2716699759177384}
 2023-07-02 10:24:33,519 [prior] Evaluating prior at array([0.27166998])
 2023-07-02 10:24:33,519 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,519 [model] Got input parameters: {'Omega_m': 0.2716699759177384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,519 [classy] Got parameters {'Omega_m': 0.2716699759177384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,519 [classy] Computing new state
 2023-07-02 10:24:33,519 [classy] Setting parameters: {'Omega_m': 0.2716699759177384, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,567 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.47690619816993}
 2023-07-02 10:24:33,567 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,569 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113744
 2023-07-02 10:24:33,569 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,569 [mcmc] New sample, #235:
   Omega_m:0.2762744
 2023-07-02 10:24:33,569 [model] Posterior to be computed for parameters {'Omega_m': -0.11503300504359948}
 2023-07-02 10:24:33,569 [prior] Evaluating prior at array([-0.11503301])
 2023-07-02 10:24:33,569 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,569 [model] Posterior to be computed for parameters {'Omega_m': 0.40297137044710585}
 2023-07-02 10:24:33,569 [prior] Evaluating prior at array([0.40297137])
 2023-07-02 10:24:33,570 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,570 [model] Got input parameters: {'Omega_m': 0.40297137044710585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,570 [classy] Got parameters {'Omega_m': 0.40297137044710585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,570 [classy] Computing new state
 2023-07-02 10:24:33,570 [classy] Setting parameters: {'Omega_m': 0.40297137044710585, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.5878734637502}
 2023-07-02 10:24:33,617 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,619 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.408155
 2023-07-02 10:24:33,619 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,619 [mcmc] New sample, #236:
   Omega_m:0.27167
 2023-07-02 10:24:33,619 [model] Posterior to be computed for parameters {'Omega_m': 0.28947475971423997}
 2023-07-02 10:24:33,619 [prior] Evaluating prior at array([0.28947476])
 2023-07-02 10:24:33,619 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,619 [model] Got input parameters: {'Omega_m': 0.28947475971423997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,619 [classy] Got parameters {'Omega_m': 0.28947475971423997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,619 [classy] Computing new state
 2023-07-02 10:24:33,619 [classy] Setting parameters: {'Omega_m': 0.28947475971423997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12285891340065}
 2023-07-02 10:24:33,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0346247
 2023-07-02 10:24:33,669 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,669 [mcmc] New sample, #237:
   Omega_m:0.4029714
 2023-07-02 10:24:33,669 [model] Posterior to be computed for parameters {'Omega_m': 0.6520331057528294}
 2023-07-02 10:24:33,669 [prior] Evaluating prior at array([0.65203311])
 2023-07-02 10:24:33,670 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,670 [model] Got input parameters: {'Omega_m': 0.6520331057528294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,670 [classy] Got parameters {'Omega_m': 0.6520331057528294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,670 [classy] Computing new state
 2023-07-02 10:24:33,670 [classy] Setting parameters: {'Omega_m': 0.6520331057528294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.09535881837297}
 2023-07-02 10:24:33,714 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.67904
 2023-07-02 10:24:33,716 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,716 [model] Posterior to be computed for parameters {'Omega_m': -0.04800350756211064}
 2023-07-02 10:24:33,716 [prior] Evaluating prior at array([-0.04800351])
 2023-07-02 10:24:33,716 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,716 [model] Posterior to be computed for parameters {'Omega_m': -0.07608471914594006}
 2023-07-02 10:24:33,716 [prior] Evaluating prior at array([-0.07608472])
 2023-07-02 10:24:33,716 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,716 [model] Posterior to be computed for parameters {'Omega_m': 0.5545258838541829}
 2023-07-02 10:24:33,716 [prior] Evaluating prior at array([0.55452588])
 2023-07-02 10:24:33,716 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,716 [model] Got input parameters: {'Omega_m': 0.5545258838541829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,716 [classy] Got parameters {'Omega_m': 0.5545258838541829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,716 [classy] Computing new state
 2023-07-02 10:24:33,716 [classy] Setting parameters: {'Omega_m': 0.5545258838541829, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,763 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.30221650635134}
 2023-07-02 10:24:33,763 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,765 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.18842
 2023-07-02 10:24:33,765 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,765 [model] Posterior to be computed for parameters {'Omega_m': 0.12204130112340264}
 2023-07-02 10:24:33,765 [prior] Evaluating prior at array([0.1220413])
 2023-07-02 10:24:33,765 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,765 [model] Got input parameters: {'Omega_m': 0.12204130112340264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,765 [classy] Got parameters {'Omega_m': 0.12204130112340264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,765 [classy] Computing new state
 2023-07-02 10:24:33,766 [classy] Setting parameters: {'Omega_m': 0.12204130112340264, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,811 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.4828667381155}
 2023-07-02 10:24:33,812 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.02991
 2023-07-02 10:24:33,813 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,814 [model] Posterior to be computed for parameters {'Omega_m': 0.14359989896195383}
 2023-07-02 10:24:33,814 [prior] Evaluating prior at array([0.1435999])
 2023-07-02 10:24:33,814 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,814 [model] Got input parameters: {'Omega_m': 0.14359989896195383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,814 [classy] Got parameters {'Omega_m': 0.14359989896195383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,814 [classy] Computing new state
 2023-07-02 10:24:33,814 [classy] Setting parameters: {'Omega_m': 0.14359989896195383, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.49007888323177}
 2023-07-02 10:24:33,861 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,862 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.9151
 2023-07-02 10:24:33,863 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,863 [model] Posterior to be computed for parameters {'Omega_m': 0.2024111535861598}
 2023-07-02 10:24:33,863 [prior] Evaluating prior at array([0.20241115])
 2023-07-02 10:24:33,863 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,863 [model] Got input parameters: {'Omega_m': 0.2024111535861598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,863 [classy] Got parameters {'Omega_m': 0.2024111535861598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,863 [classy] Computing new state
 2023-07-02 10:24:33,863 [classy] Setting parameters: {'Omega_m': 0.2024111535861598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.05858666769473}
 2023-07-02 10:24:33,910 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,911 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.01148
 2023-07-02 10:24:33,912 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,912 [model] Posterior to be computed for parameters {'Omega_m': -0.04804387944963395}
 2023-07-02 10:24:33,912 [prior] Evaluating prior at array([-0.04804388])
 2023-07-02 10:24:33,912 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,912 [model] Posterior to be computed for parameters {'Omega_m': -0.06866448485059123}
 2023-07-02 10:24:33,912 [prior] Evaluating prior at array([-0.06866448])
 2023-07-02 10:24:33,912 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,912 [model] Posterior to be computed for parameters {'Omega_m': 0.5931348943540837}
 2023-07-02 10:24:33,912 [prior] Evaluating prior at array([0.59313489])
 2023-07-02 10:24:33,912 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,912 [model] Got input parameters: {'Omega_m': 0.5931348943540837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,912 [classy] Got parameters {'Omega_m': 0.5931348943540837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,912 [classy] Computing new state
 2023-07-02 10:24:33,912 [classy] Setting parameters: {'Omega_m': 0.5931348943540837, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:33,959 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.71733251908825}
 2023-07-02 10:24:33,959 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:33,961 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.75831
 2023-07-02 10:24:33,961 [model] Computed derived parameters: {}
 2023-07-02 10:24:33,961 [model] Posterior to be computed for parameters {'Omega_m': 0.044430873028144496}
 2023-07-02 10:24:33,961 [prior] Evaluating prior at array([0.04443087])
 2023-07-02 10:24:33,961 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,962 [model] Posterior to be computed for parameters {'Omega_m': 0.05154808696009494}
 2023-07-02 10:24:33,962 [prior] Evaluating prior at array([0.05154809])
 2023-07-02 10:24:33,962 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:33,962 [model] Posterior to be computed for parameters {'Omega_m': 0.43554585558239867}
 2023-07-02 10:24:33,962 [prior] Evaluating prior at array([0.43554586])
 2023-07-02 10:24:33,962 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:33,962 [model] Got input parameters: {'Omega_m': 0.43554585558239867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,962 [classy] Got parameters {'Omega_m': 0.43554585558239867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:33,962 [classy] Computing new state
 2023-07-02 10:24:33,962 [classy] Setting parameters: {'Omega_m': 0.43554585558239867, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.60129361113044}
 2023-07-02 10:24:34,008 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,010 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.705579
 2023-07-02 10:24:34,010 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,011 [model] Posterior to be computed for parameters {'Omega_m': -0.08653025345603838}
 2023-07-02 10:24:34,011 [prior] Evaluating prior at array([-0.08653025])
 2023-07-02 10:24:34,011 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,011 [model] Posterior to be computed for parameters {'Omega_m': 0.9883640264557586}
 2023-07-02 10:24:34,011 [prior] Evaluating prior at array([0.98836403])
 2023-07-02 10:24:34,011 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,011 [model] Got input parameters: {'Omega_m': 0.9883640264557586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,011 [classy] Got parameters {'Omega_m': 0.9883640264557586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,011 [classy] Computing new state
 2023-07-02 10:24:34,011 [classy] Setting parameters: {'Omega_m': 0.9883640264557586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.530176673115}
 2023-07-02 10:24:34,057 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.40968
 2023-07-02 10:24:34,059 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,059 [model] Posterior to be computed for parameters {'Omega_m': 0.41415744512422503}
 2023-07-02 10:24:34,059 [prior] Evaluating prior at array([0.41415745])
 2023-07-02 10:24:34,060 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,060 [model] Got input parameters: {'Omega_m': 0.41415744512422503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,060 [classy] Got parameters {'Omega_m': 0.41415744512422503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,060 [classy] Computing new state
 2023-07-02 10:24:34,060 [classy] Setting parameters: {'Omega_m': 0.41415744512422503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.53688825656826}
 2023-07-02 10:24:34,106 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.503277
 2023-07-02 10:24:34,108 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,108 [mcmc] New sample, #238:
   Omega_m:0.2894748
 2023-07-02 10:24:34,108 [model] Posterior to be computed for parameters {'Omega_m': 0.17629057185848465}
 2023-07-02 10:24:34,108 [prior] Evaluating prior at array([0.17629057])
 2023-07-02 10:24:34,108 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,108 [model] Got input parameters: {'Omega_m': 0.17629057185848465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,109 [classy] Got parameters {'Omega_m': 0.17629057185848465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,109 [classy] Computing new state
 2023-07-02 10:24:34,109 [classy] Setting parameters: {'Omega_m': 0.17629057185848465, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.7942864521538}
 2023-07-02 10:24:34,154 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.68713
 2023-07-02 10:24:34,155 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,156 [model] Posterior to be computed for parameters {'Omega_m': 0.51894130877109}
 2023-07-02 10:24:34,156 [prior] Evaluating prior at array([0.51894131])
 2023-07-02 10:24:34,156 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,156 [model] Got input parameters: {'Omega_m': 0.51894130877109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,156 [classy] Got parameters {'Omega_m': 0.51894130877109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,156 [classy] Computing new state
 2023-07-02 10:24:34,156 [classy] Setting parameters: {'Omega_m': 0.51894130877109, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.85439837043637}
 2023-07-02 10:24:34,203 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,204 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.69467
 2023-07-02 10:24:34,204 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,205 [model] Posterior to be computed for parameters {'Omega_m': 0.30172682655491306}
 2023-07-02 10:24:34,205 [prior] Evaluating prior at array([0.30172683])
 2023-07-02 10:24:34,205 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,205 [model] Got input parameters: {'Omega_m': 0.30172682655491306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,205 [classy] Got parameters {'Omega_m': 0.30172682655491306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,205 [classy] Computing new state
 2023-07-02 10:24:34,205 [classy] Setting parameters: {'Omega_m': 0.30172682655491306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.57461921196614}
 2023-07-02 10:24:34,252 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00749249
 2023-07-02 10:24:34,253 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,254 [mcmc] New sample, #239:
   Omega_m:0.4141574
 2023-07-02 10:24:34,254 [model] Posterior to be computed for parameters {'Omega_m': -0.17205017840895137}
 2023-07-02 10:24:34,254 [prior] Evaluating prior at array([-0.17205018])
 2023-07-02 10:24:34,254 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,254 [model] Posterior to be computed for parameters {'Omega_m': 0.3632792186069551}
 2023-07-02 10:24:34,254 [prior] Evaluating prior at array([0.36327922])
 2023-07-02 10:24:34,254 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,254 [model] Got input parameters: {'Omega_m': 0.3632792186069551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,254 [classy] Got parameters {'Omega_m': 0.3632792186069551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,254 [classy] Computing new state
 2023-07-02 10:24:34,254 [classy] Setting parameters: {'Omega_m': 0.3632792186069551, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.55443720530906}
 2023-07-02 10:24:34,301 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,302 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140444
 2023-07-02 10:24:34,302 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,302 [mcmc] New sample, #240:
   Omega_m:0.3017268
 2023-07-02 10:24:34,303 [mcmc] Learn + convergence test @ 240 samples accepted.
 2023-07-02 10:24:34,303 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:34,307 [mcmc]  - Acceptance rate: 0.482
 2023-07-02 10:24:34,308 [mcmc]  - Condition number = 1
 2023-07-02 10:24:34,308 [mcmc]  - Eigenvalues = array([0.0293129])
 2023-07-02 10:24:34,308 [mcmc]  - Convergence of means: R-1 = 0.029313 after 192 accepted steps
 2023-07-02 10:24:34,308 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:34,308 [mcmc] array([[0.01056899]])
 2023-07-02 10:24:34,318 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:34,319 [model] Posterior to be computed for parameters {'Omega_m': 0.31502564044316034}
 2023-07-02 10:24:34,319 [prior] Evaluating prior at array([0.31502564])
 2023-07-02 10:24:34,319 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,320 [model] Got input parameters: {'Omega_m': 0.31502564044316034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,320 [classy] Got parameters {'Omega_m': 0.31502564044316034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,320 [classy] Computing new state
 2023-07-02 10:24:34,320 [classy] Setting parameters: {'Omega_m': 0.31502564044316034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.95538493399357}
 2023-07-02 10:24:34,365 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,367 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000596107
 2023-07-02 10:24:34,367 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,367 [mcmc] New sample, #241:
   Omega_m:0.3632792
 2023-07-02 10:24:34,367 [model] Posterior to be computed for parameters {'Omega_m': 0.715790827357236}
 2023-07-02 10:24:34,367 [prior] Evaluating prior at array([0.71579083])
 2023-07-02 10:24:34,368 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,368 [model] Got input parameters: {'Omega_m': 0.715790827357236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,368 [classy] Got parameters {'Omega_m': 0.715790827357236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,368 [classy] Computing new state
 2023-07-02 10:24:34,368 [classy] Setting parameters: {'Omega_m': 0.715790827357236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.54804867474522}
 2023-07-02 10:24:34,413 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,415 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.72434
 2023-07-02 10:24:34,415 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,415 [model] Posterior to be computed for parameters {'Omega_m': 0.043051841097762666}
 2023-07-02 10:24:34,415 [prior] Evaluating prior at array([0.04305184])
 2023-07-02 10:24:34,415 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,415 [model] Posterior to be computed for parameters {'Omega_m': 0.49004534774349}
 2023-07-02 10:24:34,415 [prior] Evaluating prior at array([0.49004535])
 2023-07-02 10:24:34,415 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,415 [model] Got input parameters: {'Omega_m': 0.49004534774349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,415 [classy] Got parameters {'Omega_m': 0.49004534774349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,415 [classy] Computing new state
 2023-07-02 10:24:34,415 [classy] Setting parameters: {'Omega_m': 0.49004534774349, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.06123809309858}
 2023-07-02 10:24:34,462 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.32151
 2023-07-02 10:24:34,463 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,463 [model] Posterior to be computed for parameters {'Omega_m': 0.22706458154749415}
 2023-07-02 10:24:34,463 [prior] Evaluating prior at array([0.22706458])
 2023-07-02 10:24:34,464 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,464 [model] Got input parameters: {'Omega_m': 0.22706458154749415, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,464 [classy] Got parameters {'Omega_m': 0.22706458154749415, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,464 [classy] Computing new state
 2023-07-02 10:24:34,464 [classy] Setting parameters: {'Omega_m': 0.22706458154749415, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.99852996411025}
 2023-07-02 10:24:34,510 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.564698
 2023-07-02 10:24:34,511 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,511 [mcmc] New sample, #242:
   Omega_m:0.3150256
 2023-07-02 10:24:34,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3973865477445214}
 2023-07-02 10:24:34,512 [prior] Evaluating prior at array([0.39738655])
 2023-07-02 10:24:34,512 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,512 [model] Got input parameters: {'Omega_m': 0.3973865477445214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,512 [classy] Got parameters {'Omega_m': 0.3973865477445214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,512 [classy] Computing new state
 2023-07-02 10:24:34,512 [classy] Setting parameters: {'Omega_m': 0.3973865477445214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.1230724732596}
 2023-07-02 10:24:34,557 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,559 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.363652
 2023-07-02 10:24:34,559 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,559 [mcmc] New sample, #243:
   Omega_m:0.2270646
 2023-07-02 10:24:34,560 [model] Posterior to be computed for parameters {'Omega_m': -0.06350734434247052}
 2023-07-02 10:24:34,560 [prior] Evaluating prior at array([-0.06350734])
 2023-07-02 10:24:34,560 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,560 [model] Posterior to be computed for parameters {'Omega_m': 0.2871379829814817}
 2023-07-02 10:24:34,560 [prior] Evaluating prior at array([0.28713798])
 2023-07-02 10:24:34,560 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,560 [model] Got input parameters: {'Omega_m': 0.2871379829814817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,560 [classy] Got parameters {'Omega_m': 0.2871379829814817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,560 [classy] Computing new state
 2023-07-02 10:24:34,560 [classy] Setting parameters: {'Omega_m': 0.2871379829814817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.42457977600435}
 2023-07-02 10:24:34,606 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,608 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0422261
 2023-07-02 10:24:34,608 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,608 [mcmc] New sample, #244:
   Omega_m:0.3973865
 2023-07-02 10:24:34,608 [model] Posterior to be computed for parameters {'Omega_m': 0.8135940563711179}
 2023-07-02 10:24:34,608 [prior] Evaluating prior at array([0.81359406])
 2023-07-02 10:24:34,608 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,608 [model] Got input parameters: {'Omega_m': 0.8135940563711179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,608 [classy] Got parameters {'Omega_m': 0.8135940563711179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,608 [classy] Computing new state
 2023-07-02 10:24:34,608 [classy] Setting parameters: {'Omega_m': 0.8135940563711179, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.72487062043798}
 2023-07-02 10:24:34,654 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,656 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.38487
 2023-07-02 10:24:34,656 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,656 [model] Posterior to be computed for parameters {'Omega_m': 0.3453126659945814}
 2023-07-02 10:24:34,656 [prior] Evaluating prior at array([0.34531267])
 2023-07-02 10:24:34,656 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,656 [model] Got input parameters: {'Omega_m': 0.3453126659945814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,656 [classy] Got parameters {'Omega_m': 0.3453126659945814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,657 [classy] Computing new state
 2023-07-02 10:24:34,657 [classy] Setting parameters: {'Omega_m': 0.3453126659945814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.4844981018605}
 2023-07-02 10:24:34,704 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.061257
 2023-07-02 10:24:34,706 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,706 [mcmc] New sample, #245:
   Omega_m:0.287138
 2023-07-02 10:24:34,706 [model] Posterior to be computed for parameters {'Omega_m': 0.014814874050311455}
 2023-07-02 10:24:34,706 [prior] Evaluating prior at array([0.01481487])
 2023-07-02 10:24:34,707 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,707 [model] Posterior to be computed for parameters {'Omega_m': 0.1583518979919194}
 2023-07-02 10:24:34,707 [prior] Evaluating prior at array([0.1583519])
 2023-07-02 10:24:34,707 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,707 [model] Got input parameters: {'Omega_m': 0.1583518979919194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,707 [classy] Got parameters {'Omega_m': 0.1583518979919194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,707 [classy] Computing new state
 2023-07-02 10:24:34,707 [classy] Setting parameters: {'Omega_m': 0.1583518979919194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.35056401781728}
 2023-07-02 10:24:34,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.30041
 2023-07-02 10:24:34,755 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,755 [model] Posterior to be computed for parameters {'Omega_m': -0.07232789128491551}
 2023-07-02 10:24:34,755 [prior] Evaluating prior at array([-0.07232789])
 2023-07-02 10:24:34,755 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,755 [model] Posterior to be computed for parameters {'Omega_m': 0.4406047717389495}
 2023-07-02 10:24:34,755 [prior] Evaluating prior at array([0.44060477])
 2023-07-02 10:24:34,755 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,755 [model] Got input parameters: {'Omega_m': 0.4406047717389495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,755 [classy] Got parameters {'Omega_m': 0.4406047717389495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,755 [classy] Computing new state
 2023-07-02 10:24:34,755 [classy] Setting parameters: {'Omega_m': 0.4406047717389495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,802 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.15694856947442}
 2023-07-02 10:24:34,803 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,804 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.757042
 2023-07-02 10:24:34,804 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,804 [mcmc] New sample, #246:
   Omega_m:0.3453127
 2023-07-02 10:24:34,805 [model] Posterior to be computed for parameters {'Omega_m': 0.09135897796395381}
 2023-07-02 10:24:34,805 [prior] Evaluating prior at array([0.09135898])
 2023-07-02 10:24:34,805 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:34,805 [model] Posterior to be computed for parameters {'Omega_m': 0.7051282331099293}
 2023-07-02 10:24:34,805 [prior] Evaluating prior at array([0.70512823])
 2023-07-02 10:24:34,805 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,805 [model] Got input parameters: {'Omega_m': 0.7051282331099293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,805 [classy] Got parameters {'Omega_m': 0.7051282331099293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,805 [classy] Computing new state
 2023-07-02 10:24:34,805 [classy] Setting parameters: {'Omega_m': 0.7051282331099293, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.11697619286602}
 2023-07-02 10:24:34,851 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,853 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.54688
 2023-07-02 10:24:34,853 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,853 [model] Posterior to be computed for parameters {'Omega_m': 0.36034243431319973}
 2023-07-02 10:24:34,853 [prior] Evaluating prior at array([0.36034243])
 2023-07-02 10:24:34,853 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,853 [model] Got input parameters: {'Omega_m': 0.36034243431319973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,853 [classy] Got parameters {'Omega_m': 0.36034243431319973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,853 [classy] Computing new state
 2023-07-02 10:24:34,853 [classy] Setting parameters: {'Omega_m': 0.36034243431319973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.86380125617106}
 2023-07-02 10:24:34,900 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125532
 2023-07-02 10:24:34,902 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,902 [mcmc] New sample, #247:
   Omega_m:0.4406048
 2023-07-02 10:24:34,902 [model] Posterior to be computed for parameters {'Omega_m': 0.5257590469810414}
 2023-07-02 10:24:34,902 [prior] Evaluating prior at array([0.52575905])
 2023-07-02 10:24:34,902 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,902 [model] Got input parameters: {'Omega_m': 0.5257590469810414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,902 [classy] Got parameters {'Omega_m': 0.5257590469810414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,902 [classy] Computing new state
 2023-07-02 10:24:34,903 [classy] Setting parameters: {'Omega_m': 0.5257590469810414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.35184051667045}
 2023-07-02 10:24:34,950 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:34,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.78657
 2023-07-02 10:24:34,952 [model] Computed derived parameters: {}
 2023-07-02 10:24:34,952 [model] Posterior to be computed for parameters {'Omega_m': 0.33415319748408423}
 2023-07-02 10:24:34,952 [prior] Evaluating prior at array([0.3341532])
 2023-07-02 10:24:34,952 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:34,952 [model] Got input parameters: {'Omega_m': 0.33415319748408423, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,952 [classy] Got parameters {'Omega_m': 0.33415319748408423, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:34,952 [classy] Computing new state
 2023-07-02 10:24:34,952 [classy] Setting parameters: {'Omega_m': 0.33415319748408423, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:34,999 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.73017955827726}
 2023-07-02 10:24:34,999 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,001 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0275135
 2023-07-02 10:24:35,001 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,001 [mcmc] New sample, #248:
   Omega_m:0.3603424
 2023-07-02 10:24:35,001 [model] Posterior to be computed for parameters {'Omega_m': 0.6832175223342092}
 2023-07-02 10:24:35,001 [prior] Evaluating prior at array([0.68321752])
 2023-07-02 10:24:35,001 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,001 [model] Got input parameters: {'Omega_m': 0.6832175223342092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,001 [classy] Got parameters {'Omega_m': 0.6832175223342092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,002 [classy] Computing new state
 2023-07-02 10:24:35,002 [classy] Setting parameters: {'Omega_m': 0.6832175223342092, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.31586028291349}
 2023-07-02 10:24:35,049 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.18527
 2023-07-02 10:24:35,050 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,051 [model] Posterior to be computed for parameters {'Omega_m': 0.3440741346986685}
 2023-07-02 10:24:35,051 [prior] Evaluating prior at array([0.34407413])
 2023-07-02 10:24:35,051 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,051 [model] Got input parameters: {'Omega_m': 0.3440741346986685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,051 [classy] Got parameters {'Omega_m': 0.3440741346986685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,051 [classy] Computing new state
 2023-07-02 10:24:35,051 [classy] Setting parameters: {'Omega_m': 0.3440741346986685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.62092319159086}
 2023-07-02 10:24:35,099 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,101 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0569014
 2023-07-02 10:24:35,101 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,101 [mcmc] New sample, #249:
   Omega_m:0.3341532
 2023-07-02 10:24:35,101 [model] Posterior to be computed for parameters {'Omega_m': 0.44215330489697613}
 2023-07-02 10:24:35,101 [prior] Evaluating prior at array([0.4421533])
 2023-07-02 10:24:35,102 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,102 [model] Got input parameters: {'Omega_m': 0.44215330489697613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,102 [classy] Got parameters {'Omega_m': 0.44215330489697613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,102 [classy] Computing new state
 2023-07-02 10:24:35,102 [classy] Setting parameters: {'Omega_m': 0.44215330489697613, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.0219452172869}
 2023-07-02 10:24:35,149 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,151 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.773049
 2023-07-02 10:24:35,151 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,151 [mcmc] New sample, #250:
   Omega_m:0.3440741
 2023-07-02 10:24:35,151 [model] Posterior to be computed for parameters {'Omega_m': 0.44753478777966704}
 2023-07-02 10:24:35,151 [prior] Evaluating prior at array([0.44753479])
 2023-07-02 10:24:35,151 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,151 [model] Got input parameters: {'Omega_m': 0.44753478777966704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,151 [classy] Got parameters {'Omega_m': 0.44753478777966704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,151 [classy] Computing new state
 2023-07-02 10:24:35,151 [classy] Setting parameters: {'Omega_m': 0.44753478777966704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.55633865327076}
 2023-07-02 10:24:35,199 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,201 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.8296
 2023-07-02 10:24:35,201 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,201 [mcmc] New sample, #251:
   Omega_m:0.4421533
 2023-07-02 10:24:35,201 [model] Posterior to be computed for parameters {'Omega_m': 0.0074004595457976}
 2023-07-02 10:24:35,201 [prior] Evaluating prior at array([0.00740046])
 2023-07-02 10:24:35,201 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:35,201 [model] Posterior to be computed for parameters {'Omega_m': 0.47514889791446974}
 2023-07-02 10:24:35,201 [prior] Evaluating prior at array([0.4751489])
 2023-07-02 10:24:35,201 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,201 [model] Got input parameters: {'Omega_m': 0.47514889791446974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,201 [classy] Got parameters {'Omega_m': 0.47514889791446974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,201 [classy] Computing new state
 2023-07-02 10:24:35,201 [classy] Setting parameters: {'Omega_m': 0.47514889791446974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.25048356993895}
 2023-07-02 10:24:35,249 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14066
 2023-07-02 10:24:35,251 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,251 [mcmc] New sample, #252:
   Omega_m:0.4475348
 2023-07-02 10:24:35,251 [model] Posterior to be computed for parameters {'Omega_m': 0.763291990916198}
 2023-07-02 10:24:35,251 [prior] Evaluating prior at array([0.76329199])
 2023-07-02 10:24:35,251 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,251 [model] Got input parameters: {'Omega_m': 0.763291990916198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,251 [classy] Got parameters {'Omega_m': 0.763291990916198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,251 [classy] Computing new state
 2023-07-02 10:24:35,251 [classy] Setting parameters: {'Omega_m': 0.763291990916198, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,298 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.12080673048222}
 2023-07-02 10:24:35,298 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.52466
 2023-07-02 10:24:35,299 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,300 [model] Posterior to be computed for parameters {'Omega_m': 0.25389606941490783}
 2023-07-02 10:24:35,300 [prior] Evaluating prior at array([0.25389607])
 2023-07-02 10:24:35,300 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,300 [model] Got input parameters: {'Omega_m': 0.25389606941490783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,300 [classy] Got parameters {'Omega_m': 0.25389606941490783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,300 [classy] Computing new state
 2023-07-02 10:24:35,300 [classy] Setting parameters: {'Omega_m': 0.25389606941490783, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.9612875842454}
 2023-07-02 10:24:35,347 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,349 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.245912
 2023-07-02 10:24:35,349 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,349 [mcmc] New sample, #253:
   Omega_m:0.4751489
 2023-07-02 10:24:35,349 [model] Posterior to be computed for parameters {'Omega_m': 0.5035523193029205}
 2023-07-02 10:24:35,349 [prior] Evaluating prior at array([0.50355232])
 2023-07-02 10:24:35,349 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,349 [model] Got input parameters: {'Omega_m': 0.5035523193029205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,349 [classy] Got parameters {'Omega_m': 0.5035523193029205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,349 [classy] Computing new state
 2023-07-02 10:24:35,349 [classy] Setting parameters: {'Omega_m': 0.5035523193029205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,396 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.01380379923384}
 2023-07-02 10:24:35,397 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,399 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.49249
 2023-07-02 10:24:35,399 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,399 [model] Posterior to be computed for parameters {'Omega_m': 0.19934393492241625}
 2023-07-02 10:24:35,399 [prior] Evaluating prior at array([0.19934393])
 2023-07-02 10:24:35,399 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,399 [model] Got input parameters: {'Omega_m': 0.19934393492241625, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,399 [classy] Got parameters {'Omega_m': 0.19934393492241625, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,400 [classy] Computing new state
 2023-07-02 10:24:35,400 [classy] Setting parameters: {'Omega_m': 0.19934393492241625, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,446 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.5900623072125}
 2023-07-02 10:24:35,446 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,449 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.07912
 2023-07-02 10:24:35,449 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,449 [model] Posterior to be computed for parameters {'Omega_m': 0.26766418940777553}
 2023-07-02 10:24:35,449 [prior] Evaluating prior at array([0.26766419])
 2023-07-02 10:24:35,449 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,449 [model] Got input parameters: {'Omega_m': 0.26766418940777553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,449 [classy] Got parameters {'Omega_m': 0.26766418940777553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,449 [classy] Computing new state
 2023-07-02 10:24:35,449 [classy] Setting parameters: {'Omega_m': 0.26766418940777553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.02464293513242}
 2023-07-02 10:24:35,495 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,498 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138625
 2023-07-02 10:24:35,498 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,498 [mcmc] New sample, #254:
   Omega_m:0.2538961
 2023-07-02 10:24:35,498 [model] Posterior to be computed for parameters {'Omega_m': 0.09468278122576704}
 2023-07-02 10:24:35,498 [prior] Evaluating prior at array([0.09468278])
 2023-07-02 10:24:35,498 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:35,498 [model] Posterior to be computed for parameters {'Omega_m': 0.2586908273376082}
 2023-07-02 10:24:35,499 [prior] Evaluating prior at array([0.25869083])
 2023-07-02 10:24:35,499 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,499 [model] Got input parameters: {'Omega_m': 0.2586908273376082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,499 [classy] Got parameters {'Omega_m': 0.2586908273376082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,499 [classy] Computing new state
 2023-07-02 10:24:35,499 [classy] Setting parameters: {'Omega_m': 0.2586908273376082, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.27706515619906}
 2023-07-02 10:24:35,545 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,548 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.204581
 2023-07-02 10:24:35,548 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,548 [mcmc] New sample, #255:
   Omega_m:0.2676642
 2023-07-02 10:24:35,548 [model] Posterior to be computed for parameters {'Omega_m': -0.4189486526211731}
 2023-07-02 10:24:35,548 [prior] Evaluating prior at array([-0.41894865])
 2023-07-02 10:24:35,548 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:35,549 [model] Posterior to be computed for parameters {'Omega_m': 0.23243332303169287}
 2023-07-02 10:24:35,549 [prior] Evaluating prior at array([0.23243332])
 2023-07-02 10:24:35,549 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,549 [model] Got input parameters: {'Omega_m': 0.23243332303169287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,549 [classy] Got parameters {'Omega_m': 0.23243332303169287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,549 [classy] Computing new state
 2023-07-02 10:24:35,549 [classy] Setting parameters: {'Omega_m': 0.23243332303169287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.1608430267442}
 2023-07-02 10:24:35,598 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.488127
 2023-07-02 10:24:35,600 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,600 [mcmc] New sample, #256:
   Omega_m:0.2586908
 2023-07-02 10:24:35,600 [model] Posterior to be computed for parameters {'Omega_m': 0.3425795401572632}
 2023-07-02 10:24:35,600 [prior] Evaluating prior at array([0.34257954])
 2023-07-02 10:24:35,600 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,600 [model] Got input parameters: {'Omega_m': 0.3425795401572632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,600 [classy] Got parameters {'Omega_m': 0.3425795401572632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,600 [classy] Computing new state
 2023-07-02 10:24:35,600 [classy] Setting parameters: {'Omega_m': 0.3425795401572632, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,645 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.78616251378932}
 2023-07-02 10:24:35,646 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,648 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0518435
 2023-07-02 10:24:35,649 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,649 [mcmc] New sample, #257:
   Omega_m:0.2324333
 2023-07-02 10:24:35,649 [model] Posterior to be computed for parameters {'Omega_m': 0.5358663448071408}
 2023-07-02 10:24:35,649 [prior] Evaluating prior at array([0.53586634])
 2023-07-02 10:24:35,649 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,649 [model] Got input parameters: {'Omega_m': 0.5358663448071408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,649 [classy] Got parameters {'Omega_m': 0.5358663448071408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,649 [classy] Computing new state
 2023-07-02 10:24:35,649 [classy] Setting parameters: {'Omega_m': 0.5358663448071408, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.61890267443849}
 2023-07-02 10:24:35,698 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,700 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.92526
 2023-07-02 10:24:35,700 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,700 [model] Posterior to be computed for parameters {'Omega_m': 0.19448513918481194}
 2023-07-02 10:24:35,700 [prior] Evaluating prior at array([0.19448514])
 2023-07-02 10:24:35,700 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,700 [model] Got input parameters: {'Omega_m': 0.19448513918481194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,700 [classy] Got parameters {'Omega_m': 0.19448513918481194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,700 [classy] Computing new state
 2023-07-02 10:24:35,700 [classy] Setting parameters: {'Omega_m': 0.19448513918481194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.44481022917861}
 2023-07-02 10:24:35,747 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,749 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.19228
 2023-07-02 10:24:35,749 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,749 [mcmc] New sample, #258:
   Omega_m:0.3425795
 2023-07-02 10:24:35,749 [model] Posterior to be computed for parameters {'Omega_m': -0.2696260730425051}
 2023-07-02 10:24:35,749 [prior] Evaluating prior at array([-0.26962607])
 2023-07-02 10:24:35,750 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:35,750 [model] Posterior to be computed for parameters {'Omega_m': 0.24197848541038083}
 2023-07-02 10:24:35,750 [prior] Evaluating prior at array([0.24197849])
 2023-07-02 10:24:35,750 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,750 [model] Got input parameters: {'Omega_m': 0.24197848541038083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,750 [classy] Got parameters {'Omega_m': 0.24197848541038083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,750 [classy] Computing new state
 2023-07-02 10:24:35,750 [classy] Setting parameters: {'Omega_m': 0.24197848541038083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,798 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.70934473984335}
 2023-07-02 10:24:35,798 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,800 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.368316
 2023-07-02 10:24:35,800 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,800 [mcmc] New sample, #259:
   Omega_m:0.1944851
 2023-07-02 10:24:35,800 [model] Posterior to be computed for parameters {'Omega_m': 0.669964820249099}
 2023-07-02 10:24:35,800 [prior] Evaluating prior at array([0.66996482])
 2023-07-02 10:24:35,800 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,800 [model] Got input parameters: {'Omega_m': 0.669964820249099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,800 [classy] Got parameters {'Omega_m': 0.669964820249099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,800 [classy] Computing new state
 2023-07-02 10:24:35,801 [classy] Setting parameters: {'Omega_m': 0.669964820249099, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.06126384739129}
 2023-07-02 10:24:35,845 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.96882
 2023-07-02 10:24:35,848 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,848 [model] Posterior to be computed for parameters {'Omega_m': 0.4754647738298306}
 2023-07-02 10:24:35,848 [prior] Evaluating prior at array([0.47546477])
 2023-07-02 10:24:35,848 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,848 [model] Got input parameters: {'Omega_m': 0.4754647738298306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,849 [classy] Got parameters {'Omega_m': 0.4754647738298306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,849 [classy] Computing new state
 2023-07-02 10:24:35,849 [classy] Setting parameters: {'Omega_m': 0.4754647738298306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.22487984269478}
 2023-07-02 10:24:35,894 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14441
 2023-07-02 10:24:35,896 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,896 [model] Posterior to be computed for parameters {'Omega_m': 0.04831254976813887}
 2023-07-02 10:24:35,896 [prior] Evaluating prior at array([0.04831255])
 2023-07-02 10:24:35,896 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:35,897 [model] Posterior to be computed for parameters {'Omega_m': 0.1482742554819501}
 2023-07-02 10:24:35,897 [prior] Evaluating prior at array([0.14827426])
 2023-07-02 10:24:35,897 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,897 [model] Got input parameters: {'Omega_m': 0.1482742554819501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,897 [classy] Got parameters {'Omega_m': 0.1482742554819501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,897 [classy] Computing new state
 2023-07-02 10:24:35,897 [classy] Setting parameters: {'Omega_m': 0.1482742554819501, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.47268589787632}
 2023-07-02 10:24:35,947 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,949 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.70849
 2023-07-02 10:24:35,949 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,949 [model] Posterior to be computed for parameters {'Omega_m': 0.04535082997946693}
 2023-07-02 10:24:35,949 [prior] Evaluating prior at array([0.04535083])
 2023-07-02 10:24:35,949 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:35,949 [model] Posterior to be computed for parameters {'Omega_m': 0.25082544616248903}
 2023-07-02 10:24:35,949 [prior] Evaluating prior at array([0.25082545])
 2023-07-02 10:24:35,949 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,949 [model] Got input parameters: {'Omega_m': 0.25082544616248903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,949 [classy] Got parameters {'Omega_m': 0.25082544616248903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,949 [classy] Computing new state
 2023-07-02 10:24:35,949 [classy] Setting parameters: {'Omega_m': 0.25082544616248903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:35,995 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.40510940046903}
 2023-07-02 10:24:35,996 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:35,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.274707
 2023-07-02 10:24:35,998 [model] Computed derived parameters: {}
 2023-07-02 10:24:35,998 [mcmc] New sample, #260:
   Omega_m:0.2419785
 2023-07-02 10:24:35,998 [model] Posterior to be computed for parameters {'Omega_m': 0.49441129641189674}
 2023-07-02 10:24:35,998 [prior] Evaluating prior at array([0.4944113])
 2023-07-02 10:24:35,998 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:35,998 [model] Got input parameters: {'Omega_m': 0.49441129641189674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,998 [classy] Got parameters {'Omega_m': 0.49441129641189674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:35,998 [classy] Computing new state
 2023-07-02 10:24:35,998 [classy] Setting parameters: {'Omega_m': 0.49441129641189674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.7195185083725}
 2023-07-02 10:24:36,048 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,051 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.37608
 2023-07-02 10:24:36,051 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,051 [mcmc] New sample, #261:
   Omega_m:0.2508254
 2023-07-02 10:24:36,051 [model] Posterior to be computed for parameters {'Omega_m': 1.4009213072089395}
 2023-07-02 10:24:36,051 [prior] Evaluating prior at array([1.40092131])
 2023-07-02 10:24:36,051 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:36,051 [model] Posterior to be computed for parameters {'Omega_m': 1.0511254563929695}
 2023-07-02 10:24:36,051 [prior] Evaluating prior at array([1.05112546])
 2023-07-02 10:24:36,052 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:36,052 [model] Posterior to be computed for parameters {'Omega_m': 0.33671623275237167}
 2023-07-02 10:24:36,052 [prior] Evaluating prior at array([0.33671623])
 2023-07-02 10:24:36,052 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,052 [model] Got input parameters: {'Omega_m': 0.33671623275237167, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,052 [classy] Got parameters {'Omega_m': 0.33671623275237167, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,052 [classy] Computing new state
 2023-07-02 10:24:36,052 [classy] Setting parameters: {'Omega_m': 0.33671623275237167, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,101 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.44077752729874}
 2023-07-02 10:24:36,101 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,103 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0341484
 2023-07-02 10:24:36,103 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,103 [mcmc] New sample, #262:
   Omega_m:0.4944113
 2023-07-02 10:24:36,103 [model] Posterior to be computed for parameters {'Omega_m': 0.5776696490323929}
 2023-07-02 10:24:36,103 [prior] Evaluating prior at array([0.57766965])
 2023-07-02 10:24:36,103 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,103 [model] Got input parameters: {'Omega_m': 0.5776696490323929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,103 [classy] Got parameters {'Omega_m': 0.5776696490323929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,103 [classy] Computing new state
 2023-07-02 10:24:36,103 [classy] Setting parameters: {'Omega_m': 0.5776696490323929, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.73115406738957}
 2023-07-02 10:24:36,151 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.52629
 2023-07-02 10:24:36,152 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,152 [mcmc] New sample, #263:
   Omega_m:0.3367162
 2023-07-02 10:24:36,152 [model] Posterior to be computed for parameters {'Omega_m': 0.4018880896054711}
 2023-07-02 10:24:36,152 [prior] Evaluating prior at array([0.40188809])
 2023-07-02 10:24:36,153 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,153 [model] Got input parameters: {'Omega_m': 0.4018880896054711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,153 [classy] Got parameters {'Omega_m': 0.4018880896054711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,153 [classy] Computing new state
 2023-07-02 10:24:36,153 [classy] Setting parameters: {'Omega_m': 0.4018880896054711, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.69113303730134}
 2023-07-02 10:24:36,200 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.399362
 2023-07-02 10:24:36,202 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,202 [mcmc] New sample, #264:
   Omega_m:0.5776696
 2023-07-02 10:24:36,202 [model] Posterior to be computed for parameters {'Omega_m': 0.17708367556916405}
 2023-07-02 10:24:36,202 [prior] Evaluating prior at array([0.17708368])
 2023-07-02 10:24:36,203 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,203 [model] Got input parameters: {'Omega_m': 0.17708367556916405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,203 [classy] Got parameters {'Omega_m': 0.17708367556916405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,203 [classy] Computing new state
 2023-07-02 10:24:36,203 [classy] Setting parameters: {'Omega_m': 0.17708367556916405, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.6431315906166}
 2023-07-02 10:24:36,249 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.66306
 2023-07-02 10:24:36,251 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,251 [model] Posterior to be computed for parameters {'Omega_m': 0.8505636478000956}
 2023-07-02 10:24:36,251 [prior] Evaluating prior at array([0.85056365])
 2023-07-02 10:24:36,251 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,251 [model] Got input parameters: {'Omega_m': 0.8505636478000956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,251 [classy] Got parameters {'Omega_m': 0.8505636478000956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,251 [classy] Computing new state
 2023-07-02 10:24:36,251 [classy] Setting parameters: {'Omega_m': 0.8505636478000956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.06642259311982}
 2023-07-02 10:24:36,296 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.02228
 2023-07-02 10:24:36,299 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,299 [model] Posterior to be computed for parameters {'Omega_m': 0.00765252349926937}
 2023-07-02 10:24:36,299 [prior] Evaluating prior at array([0.00765252])
 2023-07-02 10:24:36,299 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:36,299 [model] Posterior to be computed for parameters {'Omega_m': 0.18434806569073553}
 2023-07-02 10:24:36,299 [prior] Evaluating prior at array([0.18434807])
 2023-07-02 10:24:36,299 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,299 [model] Got input parameters: {'Omega_m': 0.18434806569073553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,299 [classy] Got parameters {'Omega_m': 0.18434806569073553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,299 [classy] Computing new state
 2023-07-02 10:24:36,300 [classy] Setting parameters: {'Omega_m': 0.18434806569073553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.28095143349583}
 2023-07-02 10:24:36,344 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,346 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45347
 2023-07-02 10:24:36,346 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,347 [model] Posterior to be computed for parameters {'Omega_m': 0.25294945200723634}
 2023-07-02 10:24:36,347 [prior] Evaluating prior at array([0.25294945])
 2023-07-02 10:24:36,347 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,347 [model] Got input parameters: {'Omega_m': 0.25294945200723634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,347 [classy] Got parameters {'Omega_m': 0.25294945200723634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,347 [classy] Computing new state
 2023-07-02 10:24:36,347 [classy] Setting parameters: {'Omega_m': 0.25294945200723634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.09763710699846}
 2023-07-02 10:24:36,393 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,395 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.254593
 2023-07-02 10:24:36,395 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,395 [mcmc] New sample, #265:
   Omega_m:0.4018881
 2023-07-02 10:24:36,395 [model] Posterior to be computed for parameters {'Omega_m': 0.20762391451315676}
 2023-07-02 10:24:36,395 [prior] Evaluating prior at array([0.20762391])
 2023-07-02 10:24:36,395 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,395 [model] Got input parameters: {'Omega_m': 0.20762391451315676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,395 [classy] Got parameters {'Omega_m': 0.20762391451315676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,395 [classy] Computing new state
 2023-07-02 10:24:36,395 [classy] Setting parameters: {'Omega_m': 0.20762391451315676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.16924759509808}
 2023-07-02 10:24:36,442 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,444 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.902995
 2023-07-02 10:24:36,444 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,444 [mcmc] New sample, #266:
   Omega_m:0.2529495
 2023-07-02 10:24:36,444 [model] Posterior to be computed for parameters {'Omega_m': 0.16185614320184485}
 2023-07-02 10:24:36,444 [prior] Evaluating prior at array([0.16185614])
 2023-07-02 10:24:36,444 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,444 [model] Got input parameters: {'Omega_m': 0.16185614320184485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,444 [classy] Got parameters {'Omega_m': 0.16185614320184485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,444 [classy] Computing new state
 2023-07-02 10:24:36,444 [classy] Setting parameters: {'Omega_m': 0.16185614320184485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.63434306730588}
 2023-07-02 10:24:36,490 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.16973
 2023-07-02 10:24:36,492 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,492 [mcmc] New sample, #267:
   Omega_m:0.2076239
 2023-07-02 10:24:36,492 [model] Posterior to be computed for parameters {'Omega_m': -0.18943797647855606}
 2023-07-02 10:24:36,492 [prior] Evaluating prior at array([-0.18943798])
 2023-07-02 10:24:36,492 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:36,492 [model] Posterior to be computed for parameters {'Omega_m': 0.16725668375964547}
 2023-07-02 10:24:36,492 [prior] Evaluating prior at array([0.16725668])
 2023-07-02 10:24:36,493 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,493 [model] Got input parameters: {'Omega_m': 0.16725668375964547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,493 [classy] Got parameters {'Omega_m': 0.16725668375964547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,493 [classy] Computing new state
 2023-07-02 10:24:36,493 [classy] Setting parameters: {'Omega_m': 0.16725668375964547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.55154163522064}
 2023-07-02 10:24:36,539 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.97901
 2023-07-02 10:24:36,541 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,541 [mcmc] New sample, #268:
   Omega_m:0.1618561
 2023-07-02 10:24:36,541 [model] Posterior to be computed for parameters {'Omega_m': 0.4435351705972473}
 2023-07-02 10:24:36,541 [prior] Evaluating prior at array([0.44353517])
 2023-07-02 10:24:36,541 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,541 [model] Got input parameters: {'Omega_m': 0.4435351705972473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,541 [classy] Got parameters {'Omega_m': 0.4435351705972473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,541 [classy] Computing new state
 2023-07-02 10:24:36,541 [classy] Setting parameters: {'Omega_m': 0.4435351705972473, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,588 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.90186111654256}
 2023-07-02 10:24:36,588 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,590 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.787434
 2023-07-02 10:24:36,590 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,590 [mcmc] New sample, #269:
   Omega_m:0.1672567
 2023-07-02 10:24:36,590 [model] Posterior to be computed for parameters {'Omega_m': 0.39585642584929737}
 2023-07-02 10:24:36,590 [prior] Evaluating prior at array([0.39585643])
 2023-07-02 10:24:36,590 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,590 [model] Got input parameters: {'Omega_m': 0.39585642584929737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,590 [classy] Got parameters {'Omega_m': 0.39585642584929737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,590 [classy] Computing new state
 2023-07-02 10:24:36,590 [classy] Setting parameters: {'Omega_m': 0.39585642584929737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.27094987964205}
 2023-07-02 10:24:36,636 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,638 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.351822
 2023-07-02 10:24:36,638 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,638 [mcmc] New sample, #270:
   Omega_m:0.4435352
 2023-07-02 10:24:36,638 [model] Posterior to be computed for parameters {'Omega_m': 0.196328920332325}
 2023-07-02 10:24:36,638 [prior] Evaluating prior at array([0.19632892])
 2023-07-02 10:24:36,639 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,639 [model] Got input parameters: {'Omega_m': 0.196328920332325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,639 [classy] Got parameters {'Omega_m': 0.196328920332325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,639 [classy] Computing new state
 2023-07-02 10:24:36,639 [classy] Setting parameters: {'Omega_m': 0.196328920332325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.118560493476}
 2023-07-02 10:24:36,685 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14845
 2023-07-02 10:24:36,687 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,687 [mcmc] New sample, #271:
   Omega_m:0.3958564
 2023-07-02 10:24:36,687 [model] Posterior to be computed for parameters {'Omega_m': 0.13590762948900806}
 2023-07-02 10:24:36,687 [prior] Evaluating prior at array([0.13590763])
 2023-07-02 10:24:36,687 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,687 [model] Got input parameters: {'Omega_m': 0.13590762948900806, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,687 [classy] Got parameters {'Omega_m': 0.13590762948900806, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,687 [classy] Computing new state
 2023-07-02 10:24:36,688 [classy] Setting parameters: {'Omega_m': 0.13590762948900806, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.21287425332562}
 2023-07-02 10:24:36,734 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,735 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.28097
 2023-07-02 10:24:36,735 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,736 [model] Posterior to be computed for parameters {'Omega_m': -0.0567035791899653}
 2023-07-02 10:24:36,736 [prior] Evaluating prior at array([-0.05670358])
 2023-07-02 10:24:36,736 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:36,736 [model] Posterior to be computed for parameters {'Omega_m': -0.17903738361380053}
 2023-07-02 10:24:36,736 [prior] Evaluating prior at array([-0.17903738])
 2023-07-02 10:24:36,736 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:36,736 [model] Posterior to be computed for parameters {'Omega_m': 0.2653467234624885}
 2023-07-02 10:24:36,736 [prior] Evaluating prior at array([0.26534672])
 2023-07-02 10:24:36,736 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,736 [model] Got input parameters: {'Omega_m': 0.2653467234624885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,736 [classy] Got parameters {'Omega_m': 0.2653467234624885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,736 [classy] Computing new state
 2023-07-02 10:24:36,736 [classy] Setting parameters: {'Omega_m': 0.2653467234624885, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.3446820769581}
 2023-07-02 10:24:36,782 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.154282
 2023-07-02 10:24:36,784 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,784 [mcmc] New sample, #272:
   Omega_m:0.1963289
 2023-07-02 10:24:36,784 [model] Posterior to be computed for parameters {'Omega_m': 0.4248475712417653}
 2023-07-02 10:24:36,784 [prior] Evaluating prior at array([0.42484757])
 2023-07-02 10:24:36,784 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,785 [model] Got input parameters: {'Omega_m': 0.4248475712417653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,785 [classy] Got parameters {'Omega_m': 0.4248475712417653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,785 [classy] Computing new state
 2023-07-02 10:24:36,785 [classy] Setting parameters: {'Omega_m': 0.4248475712417653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,832 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.5576544370041}
 2023-07-02 10:24:36,832 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,833 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.601204
 2023-07-02 10:24:36,833 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,834 [model] Posterior to be computed for parameters {'Omega_m': 0.5680148171955208}
 2023-07-02 10:24:36,834 [prior] Evaluating prior at array([0.56801482])
 2023-07-02 10:24:36,834 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,834 [model] Got input parameters: {'Omega_m': 0.5680148171955208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,834 [classy] Got parameters {'Omega_m': 0.5680148171955208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,834 [classy] Computing new state
 2023-07-02 10:24:36,834 [classy] Setting parameters: {'Omega_m': 0.5680148171955208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.3784680091329}
 2023-07-02 10:24:36,881 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,882 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.38391
 2023-07-02 10:24:36,882 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,883 [model] Posterior to be computed for parameters {'Omega_m': 0.36286347346978975}
 2023-07-02 10:24:36,883 [prior] Evaluating prior at array([0.36286347])
 2023-07-02 10:24:36,883 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,883 [model] Got input parameters: {'Omega_m': 0.36286347346978975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,883 [classy] Got parameters {'Omega_m': 0.36286347346978975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,883 [classy] Computing new state
 2023-07-02 10:24:36,883 [classy] Setting parameters: {'Omega_m': 0.36286347346978975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.59809126242817}
 2023-07-02 10:24:36,929 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138289
 2023-07-02 10:24:36,931 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,931 [mcmc] New sample, #273:
   Omega_m:0.2653467
 2023-07-02 10:24:36,931 [model] Posterior to be computed for parameters {'Omega_m': 0.7437438715764731}
 2023-07-02 10:24:36,931 [prior] Evaluating prior at array([0.74374387])
 2023-07-02 10:24:36,931 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,931 [model] Got input parameters: {'Omega_m': 0.7437438715764731, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,931 [classy] Got parameters {'Omega_m': 0.7437438715764731, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,931 [classy] Computing new state
 2023-07-02 10:24:36,931 [classy] Setting parameters: {'Omega_m': 0.7437438715764731, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:36,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.09915664233431}
 2023-07-02 10:24:36,978 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:36,979 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.19359
 2023-07-02 10:24:36,979 [model] Computed derived parameters: {}
 2023-07-02 10:24:36,980 [model] Posterior to be computed for parameters {'Omega_m': 0.6627150847305496}
 2023-07-02 10:24:36,980 [prior] Evaluating prior at array([0.66271508])
 2023-07-02 10:24:36,980 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:36,980 [model] Got input parameters: {'Omega_m': 0.6627150847305496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,980 [classy] Got parameters {'Omega_m': 0.6627150847305496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:36,980 [classy] Computing new state
 2023-07-02 10:24:36,980 [classy] Setting parameters: {'Omega_m': 0.6627150847305496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.47573240531189}
 2023-07-02 10:24:37,033 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,035 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.85122
 2023-07-02 10:24:37,035 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,035 [model] Posterior to be computed for parameters {'Omega_m': 0.43047220982149575}
 2023-07-02 10:24:37,035 [prior] Evaluating prior at array([0.43047221])
 2023-07-02 10:24:37,035 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,035 [model] Got input parameters: {'Omega_m': 0.43047220982149575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,035 [classy] Got parameters {'Omega_m': 0.43047220982149575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,035 [classy] Computing new state
 2023-07-02 10:24:37,035 [classy] Setting parameters: {'Omega_m': 0.43047220982149575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.0519829464644}
 2023-07-02 10:24:37,082 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,084 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.655309
 2023-07-02 10:24:37,084 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,084 [mcmc] New sample, #274:
   Omega_m:0.3628635
 2023-07-02 10:24:37,084 [model] Posterior to be computed for parameters {'Omega_m': 0.4891440713808798}
 2023-07-02 10:24:37,084 [prior] Evaluating prior at array([0.48914407])
 2023-07-02 10:24:37,084 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,084 [model] Got input parameters: {'Omega_m': 0.4891440713808798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,084 [classy] Got parameters {'Omega_m': 0.4891440713808798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,084 [classy] Computing new state
 2023-07-02 10:24:37,085 [classy] Setting parameters: {'Omega_m': 0.4891440713808798, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,132 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.13216040401042}
 2023-07-02 10:24:37,132 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,134 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.31033
 2023-07-02 10:24:37,134 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,134 [mcmc] New sample, #275:
   Omega_m:0.4304722
 2023-07-02 10:24:37,134 [model] Posterior to be computed for parameters {'Omega_m': 0.9547213399664646}
 2023-07-02 10:24:37,134 [prior] Evaluating prior at array([0.95472134])
 2023-07-02 10:24:37,134 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,134 [model] Got input parameters: {'Omega_m': 0.9547213399664646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,134 [classy] Got parameters {'Omega_m': 0.9547213399664646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,134 [classy] Computing new state
 2023-07-02 10:24:37,134 [classy] Setting parameters: {'Omega_m': 0.9547213399664646, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.79714900995674}
 2023-07-02 10:24:37,181 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,183 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.82713
 2023-07-02 10:24:37,183 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,183 [model] Posterior to be computed for parameters {'Omega_m': 0.366412741174291}
 2023-07-02 10:24:37,183 [prior] Evaluating prior at array([0.36641274])
 2023-07-02 10:24:37,183 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,183 [model] Got input parameters: {'Omega_m': 0.366412741174291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,183 [classy] Got parameters {'Omega_m': 0.366412741174291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,183 [classy] Computing new state
 2023-07-02 10:24:37,183 [classy] Setting parameters: {'Omega_m': 0.366412741174291, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.2268861967495}
 2023-07-02 10:24:37,231 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,232 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.157164
 2023-07-02 10:24:37,233 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,233 [mcmc] New sample, #276:
   Omega_m:0.4891441
 2023-07-02 10:24:37,233 [model] Posterior to be computed for parameters {'Omega_m': 0.2793292224374933}
 2023-07-02 10:24:37,233 [prior] Evaluating prior at array([0.27932922])
 2023-07-02 10:24:37,233 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,233 [model] Got input parameters: {'Omega_m': 0.2793292224374933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,233 [classy] Got parameters {'Omega_m': 0.2793292224374933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,233 [classy] Computing new state
 2023-07-02 10:24:37,233 [classy] Setting parameters: {'Omega_m': 0.2793292224374933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.44852361158812}
 2023-07-02 10:24:37,281 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,282 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0736073
 2023-07-02 10:24:37,283 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,283 [mcmc] New sample, #277:
   Omega_m:0.3664127
 2023-07-02 10:24:37,283 [model] Posterior to be computed for parameters {'Omega_m': -0.45887873046397015}
 2023-07-02 10:24:37,283 [prior] Evaluating prior at array([-0.45887873])
 2023-07-02 10:24:37,283 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:37,283 [model] Posterior to be computed for parameters {'Omega_m': 0.08126904742367341}
 2023-07-02 10:24:37,283 [prior] Evaluating prior at array([0.08126905])
 2023-07-02 10:24:37,283 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:37,283 [model] Posterior to be computed for parameters {'Omega_m': 0.5450522016189925}
 2023-07-02 10:24:37,283 [prior] Evaluating prior at array([0.5450522])
 2023-07-02 10:24:37,283 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,283 [model] Got input parameters: {'Omega_m': 0.5450522016189925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,283 [classy] Got parameters {'Omega_m': 0.5450522016189925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,283 [classy] Computing new state
 2023-07-02 10:24:37,283 [classy] Setting parameters: {'Omega_m': 0.5450522016189925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.96492433812496}
 2023-07-02 10:24:37,333 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,335 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.05371
 2023-07-02 10:24:37,335 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,335 [mcmc] New sample, #278:
   Omega_m:0.2793292
 2023-07-02 10:24:37,335 [model] Posterior to be computed for parameters {'Omega_m': 0.9699614982179212}
 2023-07-02 10:24:37,335 [prior] Evaluating prior at array([0.9699615])
 2023-07-02 10:24:37,335 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,335 [model] Got input parameters: {'Omega_m': 0.9699614982179212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,335 [classy] Got parameters {'Omega_m': 0.9699614982179212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,335 [classy] Computing new state
 2023-07-02 10:24:37,335 [classy] Setting parameters: {'Omega_m': 0.9699614982179212, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,381 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.21700166276592}
 2023-07-02 10:24:37,381 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,383 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.09114
 2023-07-02 10:24:37,383 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,383 [model] Posterior to be computed for parameters {'Omega_m': 0.3230633915456744}
 2023-07-02 10:24:37,383 [prior] Evaluating prior at array([0.32306339])
 2023-07-02 10:24:37,383 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,383 [model] Got input parameters: {'Omega_m': 0.3230633915456744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,383 [classy] Got parameters {'Omega_m': 0.3230633915456744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,383 [classy] Computing new state
 2023-07-02 10:24:37,383 [classy] Setting parameters: {'Omega_m': 0.3230633915456744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.00595288651814}
 2023-07-02 10:24:37,431 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,433 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00688862
 2023-07-02 10:24:37,433 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,433 [mcmc] New sample, #279:
   Omega_m:0.5450522
 2023-07-02 10:24:37,433 [model] Posterior to be computed for parameters {'Omega_m': 0.41837574108630543}
 2023-07-02 10:24:37,433 [prior] Evaluating prior at array([0.41837574])
 2023-07-02 10:24:37,433 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,433 [model] Got input parameters: {'Omega_m': 0.41837574108630543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,433 [classy] Got parameters {'Omega_m': 0.41837574108630543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,433 [classy] Computing new state
 2023-07-02 10:24:37,433 [classy] Setting parameters: {'Omega_m': 0.41837574108630543, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.14761534235186}
 2023-07-02 10:24:37,481 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,482 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.541125
 2023-07-02 10:24:37,483 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,483 [mcmc] New sample, #280:
   Omega_m:0.3230634
 2023-07-02 10:24:37,483 [mcmc] Learn + convergence test @ 280 samples accepted.
 2023-07-02 10:24:37,483 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:37,487 [mcmc]  - Acceptance rate: 0.474
 2023-07-02 10:24:37,488 [mcmc]  - Condition number = 1
 2023-07-02 10:24:37,488 [mcmc]  - Eigenvalues = array([0.06868928])
 2023-07-02 10:24:37,488 [mcmc]  - Convergence of means: R-1 = 0.068689 after 224 accepted steps
 2023-07-02 10:24:37,488 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:37,488 [mcmc] array([[0.01198289]])
 2023-07-02 10:24:37,498 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:37,498 [model] Posterior to be computed for parameters {'Omega_m': 0.32061509034429425}
 2023-07-02 10:24:37,499 [prior] Evaluating prior at array([0.32061509])
 2023-07-02 10:24:37,499 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,499 [model] Got input parameters: {'Omega_m': 0.32061509034429425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,499 [classy] Got parameters {'Omega_m': 0.32061509034429425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,499 [classy] Computing new state
 2023-07-02 10:24:37,499 [classy] Setting parameters: {'Omega_m': 0.32061509034429425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2929013008537}
 2023-07-02 10:24:37,547 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,549 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00417566
 2023-07-02 10:24:37,549 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,549 [mcmc] New sample, #281:
   Omega_m:0.4183757
 2023-07-02 10:24:37,549 [model] Posterior to be computed for parameters {'Omega_m': 0.2814372444660057}
 2023-07-02 10:24:37,549 [prior] Evaluating prior at array([0.28143724])
 2023-07-02 10:24:37,549 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,549 [model] Got input parameters: {'Omega_m': 0.2814372444660057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,549 [classy] Got parameters {'Omega_m': 0.2814372444660057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,549 [classy] Computing new state
 2023-07-02 10:24:37,549 [classy] Setting parameters: {'Omega_m': 0.2814372444660057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.16970546432626}
 2023-07-02 10:24:37,596 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0642104
 2023-07-02 10:24:37,597 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,598 [mcmc] New sample, #282:
   Omega_m:0.3206151
 2023-07-02 10:24:37,598 [model] Posterior to be computed for parameters {'Omega_m': 0.7075316313666231}
 2023-07-02 10:24:37,598 [prior] Evaluating prior at array([0.70753163])
 2023-07-02 10:24:37,598 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,598 [model] Got input parameters: {'Omega_m': 0.7075316313666231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,598 [classy] Got parameters {'Omega_m': 0.7075316313666231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,598 [classy] Computing new state
 2023-07-02 10:24:37,598 [classy] Setting parameters: {'Omega_m': 0.7075316313666231, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.98792193242247}
 2023-07-02 10:24:37,643 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.5868
 2023-07-02 10:24:37,645 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,645 [model] Posterior to be computed for parameters {'Omega_m': 0.7393211057965723}
 2023-07-02 10:24:37,645 [prior] Evaluating prior at array([0.73932111])
 2023-07-02 10:24:37,645 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,645 [model] Got input parameters: {'Omega_m': 0.7393211057965723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,645 [classy] Got parameters {'Omega_m': 0.7393211057965723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,645 [classy] Computing new state
 2023-07-02 10:24:37,645 [classy] Setting parameters: {'Omega_m': 0.7393211057965723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.32441398789165}
 2023-07-02 10:24:37,692 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.11899
 2023-07-02 10:24:37,694 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,694 [model] Posterior to be computed for parameters {'Omega_m': 0.27659985427874534}
 2023-07-02 10:24:37,694 [prior] Evaluating prior at array([0.27659985])
 2023-07-02 10:24:37,694 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,694 [model] Got input parameters: {'Omega_m': 0.27659985427874534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,694 [classy] Got parameters {'Omega_m': 0.27659985427874534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,694 [classy] Computing new state
 2023-07-02 10:24:37,694 [classy] Setting parameters: {'Omega_m': 0.27659985427874534, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.81219843119393}
 2023-07-02 10:24:37,741 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,743 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0868177
 2023-07-02 10:24:37,743 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,743 [mcmc] New sample, #283:
   Omega_m:0.2814372
 2023-07-02 10:24:37,743 [model] Posterior to be computed for parameters {'Omega_m': 0.5462979332988132}
 2023-07-02 10:24:37,743 [prior] Evaluating prior at array([0.54629793])
 2023-07-02 10:24:37,743 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,743 [model] Got input parameters: {'Omega_m': 0.5462979332988132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,743 [classy] Got parameters {'Omega_m': 0.5462979332988132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,743 [classy] Computing new state
 2023-07-02 10:24:37,743 [classy] Setting parameters: {'Omega_m': 0.5462979332988132, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.87710226921777}
 2023-07-02 10:24:37,791 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,793 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.0713
 2023-07-02 10:24:37,793 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,793 [model] Posterior to be computed for parameters {'Omega_m': 0.03217486685824211}
 2023-07-02 10:24:37,793 [prior] Evaluating prior at array([0.03217487])
 2023-07-02 10:24:37,793 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:37,793 [model] Posterior to be computed for parameters {'Omega_m': 0.4691759196098264}
 2023-07-02 10:24:37,793 [prior] Evaluating prior at array([0.46917592])
 2023-07-02 10:24:37,793 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,793 [model] Got input parameters: {'Omega_m': 0.4691759196098264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,793 [classy] Got parameters {'Omega_m': 0.4691759196098264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,793 [classy] Computing new state
 2023-07-02 10:24:37,793 [classy] Setting parameters: {'Omega_m': 0.4691759196098264, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.73782438788174}
 2023-07-02 10:24:37,841 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.07058
 2023-07-02 10:24:37,842 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,843 [model] Posterior to be computed for parameters {'Omega_m': 0.23881576113396713}
 2023-07-02 10:24:37,843 [prior] Evaluating prior at array([0.23881576])
 2023-07-02 10:24:37,843 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,843 [model] Got input parameters: {'Omega_m': 0.23881576113396713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,843 [classy] Got parameters {'Omega_m': 0.23881576113396713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,843 [classy] Computing new state
 2023-07-02 10:24:37,843 [classy] Setting parameters: {'Omega_m': 0.23881576113396713, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.18507699064207}
 2023-07-02 10:24:37,890 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.40578
 2023-07-02 10:24:37,892 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,892 [mcmc] New sample, #284:
   Omega_m:0.2765999
 2023-07-02 10:24:37,892 [model] Posterior to be computed for parameters {'Omega_m': 0.06443702284386527}
 2023-07-02 10:24:37,892 [prior] Evaluating prior at array([0.06443702])
 2023-07-02 10:24:37,892 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:37,892 [model] Posterior to be computed for parameters {'Omega_m': 0.39023119070878287}
 2023-07-02 10:24:37,893 [prior] Evaluating prior at array([0.39023119])
 2023-07-02 10:24:37,893 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,893 [model] Got input parameters: {'Omega_m': 0.39023119070878287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,893 [classy] Got parameters {'Omega_m': 0.39023119070878287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,893 [classy] Computing new state
 2023-07-02 10:24:37,893 [classy] Setting parameters: {'Omega_m': 0.39023119070878287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.8192961169284}
 2023-07-02 10:24:37,939 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.309708
 2023-07-02 10:24:37,941 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,941 [mcmc] New sample, #285:
   Omega_m:0.2388158
 2023-07-02 10:24:37,941 [model] Posterior to be computed for parameters {'Omega_m': 0.30913952192418875}
 2023-07-02 10:24:37,941 [prior] Evaluating prior at array([0.30913952])
 2023-07-02 10:24:37,942 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,942 [model] Got input parameters: {'Omega_m': 0.30913952192418875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,942 [classy] Got parameters {'Omega_m': 0.30913952192418875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,942 [classy] Computing new state
 2023-07-02 10:24:37,942 [classy] Setting parameters: {'Omega_m': 0.30913952192418875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:37,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.66448628995425}
 2023-07-02 10:24:37,989 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:37,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000894084
 2023-07-02 10:24:37,991 [model] Computed derived parameters: {}
 2023-07-02 10:24:37,991 [mcmc] New sample, #286:
   Omega_m:0.3902312
 2023-07-02 10:24:37,991 [model] Posterior to be computed for parameters {'Omega_m': 0.17658623057298742}
 2023-07-02 10:24:37,991 [prior] Evaluating prior at array([0.17658623])
 2023-07-02 10:24:37,991 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:37,991 [model] Got input parameters: {'Omega_m': 0.17658623057298742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,991 [classy] Got parameters {'Omega_m': 0.17658623057298742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:37,991 [classy] Computing new state
 2023-07-02 10:24:37,991 [classy] Setting parameters: {'Omega_m': 0.17658623057298742, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.73787840239098}
 2023-07-02 10:24:38,038 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.67813
 2023-07-02 10:24:38,040 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,040 [model] Posterior to be computed for parameters {'Omega_m': 0.4859688854980242}
 2023-07-02 10:24:38,040 [prior] Evaluating prior at array([0.48596889])
 2023-07-02 10:24:38,041 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,041 [model] Got input parameters: {'Omega_m': 0.4859688854980242, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,041 [classy] Got parameters {'Omega_m': 0.4859688854980242, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,041 [classy] Computing new state
 2023-07-02 10:24:38,041 [classy] Setting parameters: {'Omega_m': 0.4859688854980242, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,089 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.38306535003525}
 2023-07-02 10:24:38,089 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,091 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.27118
 2023-07-02 10:24:38,091 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,091 [mcmc] New sample, #287:
   Omega_m:0.3091395
 2023-07-02 10:24:38,091 [model] Posterior to be computed for parameters {'Omega_m': 0.17387566990582798}
 2023-07-02 10:24:38,091 [prior] Evaluating prior at array([0.17387567])
 2023-07-02 10:24:38,091 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,091 [model] Got input parameters: {'Omega_m': 0.17387566990582798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,091 [classy] Got parameters {'Omega_m': 0.17387566990582798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,091 [classy] Computing new state
 2023-07-02 10:24:38,091 [classy] Setting parameters: {'Omega_m': 0.17387566990582798, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.25757090640656}
 2023-07-02 10:24:38,139 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,141 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.76195
 2023-07-02 10:24:38,141 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,141 [mcmc] New sample, #288:
   Omega_m:0.4859689
 2023-07-02 10:24:38,141 [model] Posterior to be computed for parameters {'Omega_m': 0.07667602019801659}
 2023-07-02 10:24:38,141 [prior] Evaluating prior at array([0.07667602])
 2023-07-02 10:24:38,141 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,141 [model] Posterior to be computed for parameters {'Omega_m': 0.15926508262501907}
 2023-07-02 10:24:38,141 [prior] Evaluating prior at array([0.15926508])
 2023-07-02 10:24:38,141 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,141 [model] Got input parameters: {'Omega_m': 0.15926508262501907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,141 [classy] Got parameters {'Omega_m': 0.15926508262501907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,141 [classy] Computing new state
 2023-07-02 10:24:38,141 [classy] Setting parameters: {'Omega_m': 0.15926508262501907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.1628759371795}
 2023-07-02 10:24:38,187 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,189 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.26582
 2023-07-02 10:24:38,189 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,189 [model] Posterior to be computed for parameters {'Omega_m': 0.27237560224794655}
 2023-07-02 10:24:38,189 [prior] Evaluating prior at array([0.2723756])
 2023-07-02 10:24:38,190 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,190 [model] Got input parameters: {'Omega_m': 0.27237560224794655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,190 [classy] Got parameters {'Omega_m': 0.27237560224794655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,190 [classy] Computing new state
 2023-07-02 10:24:38,190 [classy] Setting parameters: {'Omega_m': 0.27237560224794655, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,237 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.38113024440835}
 2023-07-02 10:24:38,237 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,239 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.109643
 2023-07-02 10:24:38,239 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,239 [mcmc] New sample, #289:
   Omega_m:0.1738757
 2023-07-02 10:24:38,239 [model] Posterior to be computed for parameters {'Omega_m': -0.13460393122207392}
 2023-07-02 10:24:38,239 [prior] Evaluating prior at array([-0.13460393])
 2023-07-02 10:24:38,239 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,240 [model] Posterior to be computed for parameters {'Omega_m': 0.503531186892616}
 2023-07-02 10:24:38,240 [prior] Evaluating prior at array([0.50353119])
 2023-07-02 10:24:38,240 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,240 [model] Got input parameters: {'Omega_m': 0.503531186892616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,240 [classy] Got parameters {'Omega_m': 0.503531186892616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,240 [classy] Computing new state
 2023-07-02 10:24:38,240 [classy] Setting parameters: {'Omega_m': 0.503531186892616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.01542106490226}
 2023-07-02 10:24:38,287 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,289 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.49222
 2023-07-02 10:24:38,289 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,289 [mcmc] New sample, #290:
   Omega_m:0.2723756
 2023-07-02 10:24:38,289 [model] Posterior to be computed for parameters {'Omega_m': 0.05085529592609095}
 2023-07-02 10:24:38,289 [prior] Evaluating prior at array([0.0508553])
 2023-07-02 10:24:38,289 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,290 [model] Posterior to be computed for parameters {'Omega_m': 0.2872807327584223}
 2023-07-02 10:24:38,290 [prior] Evaluating prior at array([0.28728073])
 2023-07-02 10:24:38,290 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,290 [model] Got input parameters: {'Omega_m': 0.2872807327584223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,290 [classy] Got parameters {'Omega_m': 0.2872807327584223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,290 [classy] Computing new state
 2023-07-02 10:24:38,290 [classy] Setting parameters: {'Omega_m': 0.2872807327584223, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.40608732854608}
 2023-07-02 10:24:38,336 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0417386
 2023-07-02 10:24:38,338 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,338 [mcmc] New sample, #291:
   Omega_m:0.5035312
 2023-07-02 10:24:38,338 [model] Posterior to be computed for parameters {'Omega_m': 0.027879423884548837}
 2023-07-02 10:24:38,338 [prior] Evaluating prior at array([0.02787942])
 2023-07-02 10:24:38,339 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,339 [model] Posterior to be computed for parameters {'Omega_m': 0.10582772645420122}
 2023-07-02 10:24:38,339 [prior] Evaluating prior at array([0.10582773])
 2023-07-02 10:24:38,339 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,339 [model] Got input parameters: {'Omega_m': 0.10582772645420122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,339 [classy] Got parameters {'Omega_m': 0.10582772645420122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,339 [classy] Computing new state
 2023-07-02 10:24:38,339 [classy] Setting parameters: {'Omega_m': 0.10582772645420122, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.60702231955432}
 2023-07-02 10:24:38,385 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.07388
 2023-07-02 10:24:38,387 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,387 [model] Posterior to be computed for parameters {'Omega_m': 0.5871076584549306}
 2023-07-02 10:24:38,387 [prior] Evaluating prior at array([0.58710766])
 2023-07-02 10:24:38,387 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,387 [model] Got input parameters: {'Omega_m': 0.5871076584549306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,388 [classy] Got parameters {'Omega_m': 0.5871076584549306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,388 [classy] Computing new state
 2023-07-02 10:24:38,388 [classy] Setting parameters: {'Omega_m': 0.5871076584549306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.10911559999538}
 2023-07-02 10:24:38,435 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.66734
 2023-07-02 10:24:38,436 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,436 [model] Posterior to be computed for parameters {'Omega_m': 0.5645305569812454}
 2023-07-02 10:24:38,437 [prior] Evaluating prior at array([0.56453056])
 2023-07-02 10:24:38,437 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,437 [model] Got input parameters: {'Omega_m': 0.5645305569812454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,437 [classy] Got parameters {'Omega_m': 0.5645305569812454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,437 [classy] Computing new state
 2023-07-02 10:24:38,437 [classy] Setting parameters: {'Omega_m': 0.5645305569812454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,483 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.61488948483871}
 2023-07-02 10:24:38,483 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,485 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.33302
 2023-07-02 10:24:38,485 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,485 [model] Posterior to be computed for parameters {'Omega_m': -0.10974533983213058}
 2023-07-02 10:24:38,485 [prior] Evaluating prior at array([-0.10974534])
 2023-07-02 10:24:38,485 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,485 [model] Posterior to be computed for parameters {'Omega_m': 0.20663883119354082}
 2023-07-02 10:24:38,485 [prior] Evaluating prior at array([0.20663883])
 2023-07-02 10:24:38,485 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,485 [model] Got input parameters: {'Omega_m': 0.20663883119354082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,485 [classy] Got parameters {'Omega_m': 0.20663883119354082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,485 [classy] Computing new state
 2023-07-02 10:24:38,485 [classy] Setting parameters: {'Omega_m': 0.20663883119354082, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.3359893495993}
 2023-07-02 10:24:38,533 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,534 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.922885
 2023-07-02 10:24:38,534 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,534 [model] Posterior to be computed for parameters {'Omega_m': 0.18633835346579897}
 2023-07-02 10:24:38,534 [prior] Evaluating prior at array([0.18633835])
 2023-07-02 10:24:38,535 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,535 [model] Got input parameters: {'Omega_m': 0.18633835346579897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,535 [classy] Got parameters {'Omega_m': 0.18633835346579897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,535 [classy] Computing new state
 2023-07-02 10:24:38,535 [classy] Setting parameters: {'Omega_m': 0.18633835346579897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.91465817579618}
 2023-07-02 10:24:38,580 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.39941
 2023-07-02 10:24:38,583 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,583 [mcmc] New sample, #292:
   Omega_m:0.2872807
 2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': -0.5938498460052375}
 2023-07-02 10:24:38,583 [prior] Evaluating prior at array([-0.59384985])
 2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': -0.04210819313575659}
 2023-07-02 10:24:38,583 [prior] Evaluating prior at array([-0.04210819])
 2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': -0.03164510637978149}
 2023-07-02 10:24:38,583 [prior] Evaluating prior at array([-0.03164511])
 2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': 0.724181102508786}
 2023-07-02 10:24:38,583 [prior] Evaluating prior at array([0.7241811])
 2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,584 [model] Got input parameters: {'Omega_m': 0.724181102508786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,584 [classy] Got parameters {'Omega_m': 0.724181102508786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,584 [classy] Computing new state
 2023-07-02 10:24:38,584 [classy] Setting parameters: {'Omega_m': 0.724181102508786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.10677125739237}
 2023-07-02 10:24:38,629 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.86462
 2023-07-02 10:24:38,631 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,631 [model] Posterior to be computed for parameters {'Omega_m': 0.07599604528463412}
 2023-07-02 10:24:38,631 [prior] Evaluating prior at array([0.07599605])
 2023-07-02 10:24:38,631 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,631 [model] Posterior to be computed for parameters {'Omega_m': -0.32929697417432446}
 2023-07-02 10:24:38,631 [prior] Evaluating prior at array([-0.32929697])
 2023-07-02 10:24:38,631 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,631 [model] Posterior to be computed for parameters {'Omega_m': 0.17230812171601428}
 2023-07-02 10:24:38,631 [prior] Evaluating prior at array([0.17230812])
 2023-07-02 10:24:38,631 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,631 [model] Got input parameters: {'Omega_m': 0.17230812171601428, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,631 [classy] Got parameters {'Omega_m': 0.17230812171601428, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,631 [classy] Computing new state
 2023-07-02 10:24:38,631 [classy] Setting parameters: {'Omega_m': 0.17230812171601428, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.56078738894445}
 2023-07-02 10:24:38,677 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,679 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.81174
 2023-07-02 10:24:38,679 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,679 [mcmc] New sample, #293:
   Omega_m:0.1863384
 2023-07-02 10:24:38,680 [model] Posterior to be computed for parameters {'Omega_m': 0.057573633348445286}
 2023-07-02 10:24:38,680 [prior] Evaluating prior at array([0.05757363])
 2023-07-02 10:24:38,680 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,680 [model] Posterior to be computed for parameters {'Omega_m': 0.48350611170517105}
 2023-07-02 10:24:38,680 [prior] Evaluating prior at array([0.48350611])
 2023-07-02 10:24:38,680 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,680 [model] Got input parameters: {'Omega_m': 0.48350611170517105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,680 [classy] Got parameters {'Omega_m': 0.48350611170517105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,680 [classy] Computing new state
 2023-07-02 10:24:38,680 [classy] Setting parameters: {'Omega_m': 0.48350611170517105, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.57880397928434}
 2023-07-02 10:24:38,726 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.24107
 2023-07-02 10:24:38,728 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,728 [mcmc] New sample, #294:
   Omega_m:0.1723081
 2023-07-02 10:24:38,728 [model] Posterior to be computed for parameters {'Omega_m': -0.10013983779386132}
 2023-07-02 10:24:38,728 [prior] Evaluating prior at array([-0.10013984])
 2023-07-02 10:24:38,729 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:38,729 [model] Posterior to be computed for parameters {'Omega_m': 0.7470228981307647}
 2023-07-02 10:24:38,729 [prior] Evaluating prior at array([0.7470229])
 2023-07-02 10:24:38,729 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,729 [model] Got input parameters: {'Omega_m': 0.7470228981307647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,729 [classy] Got parameters {'Omega_m': 0.7470228981307647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,729 [classy] Computing new state
 2023-07-02 10:24:38,729 [classy] Setting parameters: {'Omega_m': 0.7470228981307647, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,773 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.93308519913722}
 2023-07-02 10:24:38,774 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,775 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.24898
 2023-07-02 10:24:38,775 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,776 [model] Posterior to be computed for parameters {'Omega_m': 0.8250544186251356}
 2023-07-02 10:24:38,776 [prior] Evaluating prior at array([0.82505442])
 2023-07-02 10:24:38,776 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,776 [model] Got input parameters: {'Omega_m': 0.8250544186251356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,776 [classy] Got parameters {'Omega_m': 0.8250544186251356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,776 [classy] Computing new state
 2023-07-02 10:24:38,776 [classy] Setting parameters: {'Omega_m': 0.8250544186251356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,821 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.20194169158006}
 2023-07-02 10:24:38,821 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,823 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.58209
 2023-07-02 10:24:38,823 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,823 [model] Posterior to be computed for parameters {'Omega_m': 0.5840699966216292}
 2023-07-02 10:24:38,823 [prior] Evaluating prior at array([0.58407])
 2023-07-02 10:24:38,823 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,823 [model] Got input parameters: {'Omega_m': 0.5840699966216292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,823 [classy] Got parameters {'Omega_m': 0.5840699966216292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,823 [classy] Computing new state
 2023-07-02 10:24:38,823 [classy] Setting parameters: {'Omega_m': 0.5840699966216292, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,870 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.30817277338203}
 2023-07-02 10:24:38,870 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,872 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62175
 2023-07-02 10:24:38,872 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,873 [model] Posterior to be computed for parameters {'Omega_m': 0.6376665469913265}
 2023-07-02 10:24:38,873 [prior] Evaluating prior at array([0.63766655])
 2023-07-02 10:24:38,873 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,873 [model] Got input parameters: {'Omega_m': 0.6376665469913265, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,873 [classy] Got parameters {'Omega_m': 0.6376665469913265, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,873 [classy] Computing new state
 2023-07-02 10:24:38,873 [classy] Setting parameters: {'Omega_m': 0.6376665469913265, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.94596859058557}
 2023-07-02 10:24:38,918 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,920 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.44973
 2023-07-02 10:24:38,920 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,920 [model] Posterior to be computed for parameters {'Omega_m': 0.6104768795560938}
 2023-07-02 10:24:38,920 [prior] Evaluating prior at array([0.61047688])
 2023-07-02 10:24:38,920 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,920 [model] Got input parameters: {'Omega_m': 0.6104768795560938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,920 [classy] Got parameters {'Omega_m': 0.6104768795560938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,920 [classy] Computing new state
 2023-07-02 10:24:38,920 [classy] Setting parameters: {'Omega_m': 0.6104768795560938, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:38,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.61283987933217}
 2023-07-02 10:24:38,967 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:38,969 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.02376
 2023-07-02 10:24:38,969 [model] Computed derived parameters: {}
 2023-07-02 10:24:38,969 [model] Posterior to be computed for parameters {'Omega_m': 0.45827036257387266}
 2023-07-02 10:24:38,969 [prior] Evaluating prior at array([0.45827036])
 2023-07-02 10:24:38,969 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:38,969 [model] Got input parameters: {'Omega_m': 0.45827036257387266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,969 [classy] Got parameters {'Omega_m': 0.45827036257387266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:38,969 [classy] Computing new state
 2023-07-02 10:24:38,969 [classy] Setting parameters: {'Omega_m': 0.45827036257387266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.64361584242855}
 2023-07-02 10:24:39,016 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.946536
 2023-07-02 10:24:39,018 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,018 [mcmc] New sample, #295:
   Omega_m:0.4835061
 2023-07-02 10:24:39,018 [model] Posterior to be computed for parameters {'Omega_m': 0.48528512399685175}
 2023-07-02 10:24:39,018 [prior] Evaluating prior at array([0.48528512])
 2023-07-02 10:24:39,018 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,018 [model] Got input parameters: {'Omega_m': 0.48528512399685175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,019 [classy] Got parameters {'Omega_m': 0.48528512399685175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,019 [classy] Computing new state
 2023-07-02 10:24:39,019 [classy] Setting parameters: {'Omega_m': 0.48528512399685175, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,066 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.43730898027638}
 2023-07-02 10:24:39,066 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,068 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.2628
 2023-07-02 10:24:39,068 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,068 [mcmc] New sample, #296:
   Omega_m:0.4582704
 2023-07-02 10:24:39,068 [model] Posterior to be computed for parameters {'Omega_m': 0.4057883187822118}
 2023-07-02 10:24:39,068 [prior] Evaluating prior at array([0.40578832])
 2023-07-02 10:24:39,068 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,068 [model] Got input parameters: {'Omega_m': 0.4057883187822118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,068 [classy] Got parameters {'Omega_m': 0.4057883187822118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,068 [classy] Computing new state
 2023-07-02 10:24:39,069 [classy] Setting parameters: {'Omega_m': 0.4057883187822118, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.32058809492378}
 2023-07-02 10:24:39,116 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.431374
 2023-07-02 10:24:39,118 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,118 [mcmc] New sample, #297:
   Omega_m:0.4852851
 2023-07-02 10:24:39,118 [model] Posterior to be computed for parameters {'Omega_m': 0.16604242385534054}
 2023-07-02 10:24:39,118 [prior] Evaluating prior at array([0.16604242])
 2023-07-02 10:24:39,118 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,118 [model] Got input parameters: {'Omega_m': 0.16604242385534054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,118 [classy] Got parameters {'Omega_m': 0.16604242385534054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,118 [classy] Computing new state
 2023-07-02 10:24:39,118 [classy] Setting parameters: {'Omega_m': 0.16604242385534054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,165 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.79284201993966}
 2023-07-02 10:24:39,165 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,167 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.0208
 2023-07-02 10:24:39,167 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,167 [model] Posterior to be computed for parameters {'Omega_m': 0.5593957097953548}
 2023-07-02 10:24:39,167 [prior] Evaluating prior at array([0.55939571])
 2023-07-02 10:24:39,167 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,167 [model] Got input parameters: {'Omega_m': 0.5593957097953548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,167 [classy] Got parameters {'Omega_m': 0.5593957097953548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,167 [classy] Computing new state
 2023-07-02 10:24:39,167 [classy] Setting parameters: {'Omega_m': 0.5593957097953548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.96607877520823}
 2023-07-02 10:24:39,216 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,218 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.25851
 2023-07-02 10:24:39,218 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,218 [model] Posterior to be computed for parameters {'Omega_m': 0.7583577408816342}
 2023-07-02 10:24:39,218 [prior] Evaluating prior at array([0.75835774])
 2023-07-02 10:24:39,218 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,218 [model] Got input parameters: {'Omega_m': 0.7583577408816342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,218 [classy] Got parameters {'Omega_m': 0.7583577408816342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,218 [classy] Computing new state
 2023-07-02 10:24:39,218 [classy] Setting parameters: {'Omega_m': 0.7583577408816342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.36514974173697}
 2023-07-02 10:24:39,263 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,265 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.44089
 2023-07-02 10:24:39,265 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,265 [model] Posterior to be computed for parameters {'Omega_m': 0.6782615181304047}
 2023-07-02 10:24:39,265 [prior] Evaluating prior at array([0.67826152])
 2023-07-02 10:24:39,265 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,265 [model] Got input parameters: {'Omega_m': 0.6782615181304047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,265 [classy] Got parameters {'Omega_m': 0.6782615181304047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,265 [classy] Computing new state
 2023-07-02 10:24:39,265 [classy] Setting parameters: {'Omega_m': 0.6782615181304047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.59278847923802}
 2023-07-02 10:24:39,312 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.10411
 2023-07-02 10:24:39,314 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,314 [model] Posterior to be computed for parameters {'Omega_m': 0.6705787031509105}
 2023-07-02 10:24:39,314 [prior] Evaluating prior at array([0.6705787])
 2023-07-02 10:24:39,314 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,314 [model] Got input parameters: {'Omega_m': 0.6705787031509105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,314 [classy] Got parameters {'Omega_m': 0.6705787031509105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,314 [classy] Computing new state
 2023-07-02 10:24:39,314 [classy] Setting parameters: {'Omega_m': 0.6705787031509105, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,361 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.02638772536578}
 2023-07-02 10:24:39,361 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,363 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.9788
 2023-07-02 10:24:39,363 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,363 [mcmc] New sample, #298:
   Omega_m:0.4057883
 2023-07-02 10:24:39,363 [model] Posterior to be computed for parameters {'Omega_m': 0.4858340744164399}
 2023-07-02 10:24:39,363 [prior] Evaluating prior at array([0.48583407])
 2023-07-02 10:24:39,363 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,363 [model] Got input parameters: {'Omega_m': 0.4858340744164399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,363 [classy] Got parameters {'Omega_m': 0.4858340744164399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,363 [classy] Computing new state
 2023-07-02 10:24:39,363 [classy] Setting parameters: {'Omega_m': 0.4858340744164399, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,412 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.3937533647381}
 2023-07-02 10:24:39,412 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,414 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.26953
 2023-07-02 10:24:39,414 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,414 [mcmc] New sample, #299:
   Omega_m:0.6705787
 2023-07-02 10:24:39,414 [model] Posterior to be computed for parameters {'Omega_m': 0.2531899447351358}
 2023-07-02 10:24:39,414 [prior] Evaluating prior at array([0.25318994])
 2023-07-02 10:24:39,414 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,414 [model] Got input parameters: {'Omega_m': 0.2531899447351358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,414 [classy] Got parameters {'Omega_m': 0.2531899447351358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,414 [classy] Computing new state
 2023-07-02 10:24:39,414 [classy] Setting parameters: {'Omega_m': 0.2531899447351358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,462 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.0629567179264}
 2023-07-02 10:24:39,462 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,464 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.252371
 2023-07-02 10:24:39,464 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,464 [mcmc] New sample, #300:
   Omega_m:0.4858341
 2023-07-02 10:24:39,464 [model] Posterior to be computed for parameters {'Omega_m': 0.4099408498356112}
 2023-07-02 10:24:39,464 [prior] Evaluating prior at array([0.40994085])
 2023-07-02 10:24:39,465 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,465 [model] Got input parameters: {'Omega_m': 0.4099408498356112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,465 [classy] Got parameters {'Omega_m': 0.4099408498356112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,465 [classy] Computing new state
 2023-07-02 10:24:39,465 [classy] Setting parameters: {'Omega_m': 0.4099408498356112, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,512 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.92981421293112}
 2023-07-02 10:24:39,512 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,514 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.466512
 2023-07-02 10:24:39,514 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,514 [mcmc] New sample, #301:
   Omega_m:0.2531899
 2023-07-02 10:24:39,514 [model] Posterior to be computed for parameters {'Omega_m': 0.5328267218175338}
 2023-07-02 10:24:39,515 [prior] Evaluating prior at array([0.53282672])
 2023-07-02 10:24:39,515 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,515 [model] Got input parameters: {'Omega_m': 0.5328267218175338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,515 [classy] Got parameters {'Omega_m': 0.5328267218175338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,515 [classy] Computing new state
 2023-07-02 10:24:39,515 [classy] Setting parameters: {'Omega_m': 0.5328267218175338, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,563 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.83782411719453}
 2023-07-02 10:24:39,563 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,564 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.88326
 2023-07-02 10:24:39,564 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,565 [model] Posterior to be computed for parameters {'Omega_m': 1.55811726978832}
 2023-07-02 10:24:39,565 [prior] Evaluating prior at array([1.55811727])
 2023-07-02 10:24:39,565 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:39,565 [model] Posterior to be computed for parameters {'Omega_m': 0.6937925627855914}
 2023-07-02 10:24:39,565 [prior] Evaluating prior at array([0.69379256])
 2023-07-02 10:24:39,565 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,565 [model] Got input parameters: {'Omega_m': 0.6937925627855914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,565 [classy] Got parameters {'Omega_m': 0.6937925627855914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,565 [classy] Computing new state
 2023-07-02 10:24:39,565 [classy] Setting parameters: {'Omega_m': 0.6937925627855914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.73214297289047}
 2023-07-02 10:24:39,617 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,619 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.35924
 2023-07-02 10:24:39,619 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,619 [model] Posterior to be computed for parameters {'Omega_m': 0.3621397397118498}
 2023-07-02 10:24:39,619 [prior] Evaluating prior at array([0.36213974])
 2023-07-02 10:24:39,619 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,619 [model] Got input parameters: {'Omega_m': 0.3621397397118498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,619 [classy] Got parameters {'Omega_m': 0.3621397397118498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,619 [classy] Computing new state
 2023-07-02 10:24:39,619 [classy] Setting parameters: {'Omega_m': 0.3621397397118498, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.67419633070068}
 2023-07-02 10:24:39,673 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,675 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.134571
 2023-07-02 10:24:39,675 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,675 [mcmc] New sample, #302:
   Omega_m:0.4099408
 2023-07-02 10:24:39,676 [model] Posterior to be computed for parameters {'Omega_m': 0.47847143593505936}
 2023-07-02 10:24:39,676 [prior] Evaluating prior at array([0.47847144])
 2023-07-02 10:24:39,676 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,676 [model] Got input parameters: {'Omega_m': 0.47847143593505936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,676 [classy] Got parameters {'Omega_m': 0.47847143593505936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,676 [classy] Computing new state
 2023-07-02 10:24:39,676 [classy] Setting parameters: {'Omega_m': 0.47847143593505936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.98205413082408}
 2023-07-02 10:24:39,737 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,739 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.18025
 2023-07-02 10:24:39,740 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,740 [model] Posterior to be computed for parameters {'Omega_m': 0.6864431494684358}
 2023-07-02 10:24:39,740 [prior] Evaluating prior at array([0.68644315])
 2023-07-02 10:24:39,740 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,740 [model] Got input parameters: {'Omega_m': 0.6864431494684358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,740 [classy] Got parameters {'Omega_m': 0.6864431494684358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,740 [classy] Computing new state
 2023-07-02 10:24:39,740 [classy] Setting parameters: {'Omega_m': 0.6864431494684358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,804 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.13677637096387}
 2023-07-02 10:24:39,804 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,807 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.23823
 2023-07-02 10:24:39,807 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,807 [model] Posterior to be computed for parameters {'Omega_m': 0.7014947726716416}
 2023-07-02 10:24:39,807 [prior] Evaluating prior at array([0.70149477])
 2023-07-02 10:24:39,807 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,807 [model] Got input parameters: {'Omega_m': 0.7014947726716416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,807 [classy] Got parameters {'Omega_m': 0.7014947726716416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,807 [classy] Computing new state
 2023-07-02 10:24:39,807 [classy] Setting parameters: {'Omega_m': 0.7014947726716416, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,852 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.31299381869772}
 2023-07-02 10:24:39,852 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,854 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.48661
 2023-07-02 10:24:39,854 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,854 [model] Posterior to be computed for parameters {'Omega_m': 0.2562494637555342}
 2023-07-02 10:24:39,854 [prior] Evaluating prior at array([0.25624946])
 2023-07-02 10:24:39,854 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,854 [model] Got input parameters: {'Omega_m': 0.2562494637555342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,854 [classy] Got parameters {'Omega_m': 0.2562494637555342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,854 [classy] Computing new state
 2023-07-02 10:24:39,854 [classy] Setting parameters: {'Omega_m': 0.2562494637555342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.6241258821991}
 2023-07-02 10:24:39,901 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.22508
 2023-07-02 10:24:39,903 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,903 [mcmc] New sample, #303:
   Omega_m:0.3621397
 2023-07-02 10:24:39,903 [model] Posterior to be computed for parameters {'Omega_m': 0.3059597854037749}
 2023-07-02 10:24:39,903 [prior] Evaluating prior at array([0.30595979])
 2023-07-02 10:24:39,903 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,903 [model] Got input parameters: {'Omega_m': 0.3059597854037749, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,903 [classy] Got parameters {'Omega_m': 0.3059597854037749, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,903 [classy] Computing new state
 2023-07-02 10:24:39,903 [classy] Setting parameters: {'Omega_m': 0.3059597854037749, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.05252228167572}
 2023-07-02 10:24:39,948 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00285562
 2023-07-02 10:24:39,951 [model] Computed derived parameters: {}
 2023-07-02 10:24:39,951 [mcmc] New sample, #304:
   Omega_m:0.2562495
 2023-07-02 10:24:39,952 [model] Posterior to be computed for parameters {'Omega_m': -0.38169801093279976}
 2023-07-02 10:24:39,952 [prior] Evaluating prior at array([-0.38169801])
 2023-07-02 10:24:39,952 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:39,952 [model] Posterior to be computed for parameters {'Omega_m': 0.18361833517733994}
 2023-07-02 10:24:39,952 [prior] Evaluating prior at array([0.18361834])
 2023-07-02 10:24:39,952 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:39,952 [model] Got input parameters: {'Omega_m': 0.18361833517733994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,952 [classy] Got parameters {'Omega_m': 0.18361833517733994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:39,952 [classy] Computing new state
 2023-07-02 10:24:39,952 [classy] Setting parameters: {'Omega_m': 0.18361833517733994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:39,997 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.4160000485529}
 2023-07-02 10:24:39,997 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:39,999 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.47365
 2023-07-02 10:24:39,999 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,000 [model] Posterior to be computed for parameters {'Omega_m': 0.30746987369883133}
 2023-07-02 10:24:40,000 [prior] Evaluating prior at array([0.30746987])
 2023-07-02 10:24:40,000 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,000 [model] Got input parameters: {'Omega_m': 0.30746987369883133, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,000 [classy] Got parameters {'Omega_m': 0.30746987369883133, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,000 [classy] Computing new state
 2023-07-02 10:24:40,000 [classy] Setting parameters: {'Omega_m': 0.30746987369883133, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,046 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86779885979414}
 2023-07-02 10:24:40,046 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00176361
 2023-07-02 10:24:40,048 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,048 [mcmc] New sample, #305:
   Omega_m:0.3059598
 2023-07-02 10:24:40,048 [model] Posterior to be computed for parameters {'Omega_m': 0.2755324105622118}
 2023-07-02 10:24:40,048 [prior] Evaluating prior at array([0.27553241])
 2023-07-02 10:24:40,048 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,048 [model] Got input parameters: {'Omega_m': 0.2755324105622118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,048 [classy] Got parameters {'Omega_m': 0.2755324105622118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,048 [classy] Computing new state
 2023-07-02 10:24:40,049 [classy] Setting parameters: {'Omega_m': 0.2755324105622118, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.95526318462245}
 2023-07-02 10:24:40,096 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0923099
 2023-07-02 10:24:40,098 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,098 [mcmc] New sample, #306:
   Omega_m:0.3074699
 2023-07-02 10:24:40,098 [model] Posterior to be computed for parameters {'Omega_m': -0.21604564226216094}
 2023-07-02 10:24:40,098 [prior] Evaluating prior at array([-0.21604564])
 2023-07-02 10:24:40,098 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,099 [model] Posterior to be computed for parameters {'Omega_m': 0.1200033593418075}
 2023-07-02 10:24:40,099 [prior] Evaluating prior at array([0.12000336])
 2023-07-02 10:24:40,099 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,099 [model] Got input parameters: {'Omega_m': 0.1200033593418075, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,099 [classy] Got parameters {'Omega_m': 0.1200033593418075, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,099 [classy] Computing new state
 2023-07-02 10:24:40,099 [classy] Setting parameters: {'Omega_m': 0.1200033593418075, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.98255244615848}
 2023-07-02 10:24:40,146 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.15055
 2023-07-02 10:24:40,148 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,148 [model] Posterior to be computed for parameters {'Omega_m': 0.0982095829799198}
 2023-07-02 10:24:40,148 [prior] Evaluating prior at array([0.09820958])
 2023-07-02 10:24:40,148 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,148 [model] Posterior to be computed for parameters {'Omega_m': 0.445265092707658}
 2023-07-02 10:24:40,148 [prior] Evaluating prior at array([0.44526509])
 2023-07-02 10:24:40,148 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,148 [model] Got input parameters: {'Omega_m': 0.445265092707658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,148 [classy] Got parameters {'Omega_m': 0.445265092707658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,148 [classy] Computing new state
 2023-07-02 10:24:40,148 [classy] Setting parameters: {'Omega_m': 0.445265092707658, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,196 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.75204142069379}
 2023-07-02 10:24:40,196 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,198 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.805576
 2023-07-02 10:24:40,198 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,198 [mcmc] New sample, #307:
   Omega_m:0.2755324
 2023-07-02 10:24:40,198 [model] Posterior to be computed for parameters {'Omega_m': 0.331024982230116}
 2023-07-02 10:24:40,198 [prior] Evaluating prior at array([0.33102498])
 2023-07-02 10:24:40,199 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,199 [model] Got input parameters: {'Omega_m': 0.331024982230116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,199 [classy] Got parameters {'Omega_m': 0.331024982230116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,199 [classy] Computing new state
 2023-07-02 10:24:40,199 [classy] Setting parameters: {'Omega_m': 0.331024982230116, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.08612020953476}
 2023-07-02 10:24:40,246 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0203483
 2023-07-02 10:24:40,248 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,248 [mcmc] New sample, #308:
   Omega_m:0.4452651
 2023-07-02 10:24:40,248 [model] Posterior to be computed for parameters {'Omega_m': 0.451448662841972}
 2023-07-02 10:24:40,248 [prior] Evaluating prior at array([0.45144866])
 2023-07-02 10:24:40,248 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,248 [model] Got input parameters: {'Omega_m': 0.451448662841972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,248 [classy] Got parameters {'Omega_m': 0.451448662841972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,248 [classy] Computing new state
 2023-07-02 10:24:40,248 [classy] Setting parameters: {'Omega_m': 0.451448662841972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.2211282049}
 2023-07-02 10:24:40,295 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.871608
 2023-07-02 10:24:40,297 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,297 [model] Posterior to be computed for parameters {'Omega_m': 0.467586821969445}
 2023-07-02 10:24:40,297 [prior] Evaluating prior at array([0.46758682])
 2023-07-02 10:24:40,297 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,297 [model] Got input parameters: {'Omega_m': 0.467586821969445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,297 [classy] Got parameters {'Omega_m': 0.467586821969445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,297 [classy] Computing new state
 2023-07-02 10:24:40,297 [classy] Setting parameters: {'Omega_m': 0.467586821969445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8685137703851}
 2023-07-02 10:24:40,357 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,360 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05219
 2023-07-02 10:24:40,360 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,360 [mcmc] New sample, #309:
   Omega_m:0.331025
 2023-07-02 10:24:40,361 [model] Posterior to be computed for parameters {'Omega_m': -0.17501906774647458}
 2023-07-02 10:24:40,361 [prior] Evaluating prior at array([-0.17501907])
 2023-07-02 10:24:40,361 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,361 [model] Posterior to be computed for parameters {'Omega_m': 1.0428516599455153}
 2023-07-02 10:24:40,361 [prior] Evaluating prior at array([1.04285166])
 2023-07-02 10:24:40,361 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,361 [model] Posterior to be computed for parameters {'Omega_m': 0.567210580560753}
 2023-07-02 10:24:40,361 [prior] Evaluating prior at array([0.56721058])
 2023-07-02 10:24:40,361 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,361 [model] Got input parameters: {'Omega_m': 0.567210580560753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,362 [classy] Got parameters {'Omega_m': 0.567210580560753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,362 [classy] Computing new state
 2023-07-02 10:24:40,362 [classy] Setting parameters: {'Omega_m': 0.567210580560753, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.43290208616033}
 2023-07-02 10:24:40,439 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,442 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.37214
 2023-07-02 10:24:40,442 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,442 [mcmc] New sample, #310:
   Omega_m:0.4675868
 2023-07-02 10:24:40,442 [model] Posterior to be computed for parameters {'Omega_m': 0.922418774013628}
 2023-07-02 10:24:40,442 [prior] Evaluating prior at array([0.92241877])
 2023-07-02 10:24:40,442 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,442 [model] Got input parameters: {'Omega_m': 0.922418774013628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,442 [classy] Got parameters {'Omega_m': 0.922418774013628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,442 [classy] Computing new state
 2023-07-02 10:24:40,442 [classy] Setting parameters: {'Omega_m': 0.922418774013628, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,514 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.06250172264066}
 2023-07-02 10:24:40,514 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,516 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.26704
 2023-07-02 10:24:40,517 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,517 [model] Posterior to be computed for parameters {'Omega_m': 0.7363846589674309}
 2023-07-02 10:24:40,517 [prior] Evaluating prior at array([0.73638466])
 2023-07-02 10:24:40,517 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,517 [model] Got input parameters: {'Omega_m': 0.7363846589674309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,517 [classy] Got parameters {'Omega_m': 0.7363846589674309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,517 [classy] Computing new state
 2023-07-02 10:24:40,517 [classy] Setting parameters: {'Omega_m': 0.7363846589674309, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,563 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.4747815905536}
 2023-07-02 10:24:40,563 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,564 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.06953
 2023-07-02 10:24:40,564 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,565 [model] Posterior to be computed for parameters {'Omega_m': 0.1606649939992048}
 2023-07-02 10:24:40,565 [prior] Evaluating prior at array([0.16066499])
 2023-07-02 10:24:40,565 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,565 [model] Got input parameters: {'Omega_m': 0.1606649939992048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,565 [classy] Got parameters {'Omega_m': 0.1606649939992048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,565 [classy] Computing new state
 2023-07-02 10:24:40,565 [classy] Setting parameters: {'Omega_m': 0.1606649939992048, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.87658302347833}
 2023-07-02 10:24:40,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.21353
 2023-07-02 10:24:40,614 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,614 [mcmc] New sample, #311:
   Omega_m:0.5672106
 2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.6189699658488845}
 2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.61896997])
 2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.02835722378142355}
 2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.02835722])
 2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.04433577722682486}
 2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.04433578])
 2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.20862102119561377}
 2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.20862102])
 2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': 0.3971408758050733}
 2023-07-02 10:24:40,614 [prior] Evaluating prior at array([0.39714088])
 2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,615 [model] Got input parameters: {'Omega_m': 0.3971408758050733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,615 [classy] Got parameters {'Omega_m': 0.3971408758050733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,615 [classy] Computing new state
 2023-07-02 10:24:40,615 [classy] Setting parameters: {'Omega_m': 0.3971408758050733, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.1467783404195}
 2023-07-02 10:24:40,660 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.361742
 2023-07-02 10:24:40,662 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,663 [mcmc] New sample, #312:
   Omega_m:0.160665
 2023-07-02 10:24:40,663 [model] Posterior to be computed for parameters {'Omega_m': 0.24512936960184933}
 2023-07-02 10:24:40,663 [prior] Evaluating prior at array([0.24512937])
 2023-07-02 10:24:40,663 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,663 [model] Got input parameters: {'Omega_m': 0.24512936960184933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,663 [classy] Got parameters {'Omega_m': 0.24512936960184933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,663 [classy] Computing new state
 2023-07-02 10:24:40,663 [classy] Setting parameters: {'Omega_m': 0.24512936960184933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,709 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.24039065470444}
 2023-07-02 10:24:40,709 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,710 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.333117
 2023-07-02 10:24:40,711 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,711 [mcmc] New sample, #313:
   Omega_m:0.3971409
 2023-07-02 10:24:40,711 [model] Posterior to be computed for parameters {'Omega_m': 0.8949045461365108}
 2023-07-02 10:24:40,711 [prior] Evaluating prior at array([0.89490455])
 2023-07-02 10:24:40,711 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,711 [model] Got input parameters: {'Omega_m': 0.8949045461365108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,711 [classy] Got parameters {'Omega_m': 0.8949045461365108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,711 [classy] Computing new state
 2023-07-02 10:24:40,711 [classy] Setting parameters: {'Omega_m': 0.8949045461365108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.18054249600104}
 2023-07-02 10:24:40,756 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.78995
 2023-07-02 10:24:40,758 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,758 [model] Posterior to be computed for parameters {'Omega_m': 0.21592451960562065}
 2023-07-02 10:24:40,758 [prior] Evaluating prior at array([0.21592452])
 2023-07-02 10:24:40,758 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,758 [model] Got input parameters: {'Omega_m': 0.21592451960562065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,758 [classy] Got parameters {'Omega_m': 0.21592451960562065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,758 [classy] Computing new state
 2023-07-02 10:24:40,758 [classy] Setting parameters: {'Omega_m': 0.21592451960562065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,804 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.7881469150433}
 2023-07-02 10:24:40,804 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.74628
 2023-07-02 10:24:40,806 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,807 [model] Posterior to be computed for parameters {'Omega_m': -0.08285909407276681}
 2023-07-02 10:24:40,807 [prior] Evaluating prior at array([-0.08285909])
 2023-07-02 10:24:40,807 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,807 [model] Posterior to be computed for parameters {'Omega_m': 0.10162962923318036}
 2023-07-02 10:24:40,807 [prior] Evaluating prior at array([0.10162963])
 2023-07-02 10:24:40,807 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,807 [model] Got input parameters: {'Omega_m': 0.10162962923318036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,807 [classy] Got parameters {'Omega_m': 0.10162962923318036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,807 [classy] Computing new state
 2023-07-02 10:24:40,807 [classy] Setting parameters: {'Omega_m': 0.10162962923318036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 184.733553473902}
 2023-07-02 10:24:40,853 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,855 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.37788
 2023-07-02 10:24:40,855 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,855 [model] Posterior to be computed for parameters {'Omega_m': 0.29174086979727687}
 2023-07-02 10:24:40,855 [prior] Evaluating prior at array([0.29174087])
 2023-07-02 10:24:40,855 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,855 [model] Got input parameters: {'Omega_m': 0.29174086979727687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,855 [classy] Got parameters {'Omega_m': 0.29174086979727687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,855 [classy] Computing new state
 2023-07-02 10:24:40,856 [classy] Setting parameters: {'Omega_m': 0.29174086979727687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,902 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.83226334963538}
 2023-07-02 10:24:40,902 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0280144
 2023-07-02 10:24:40,903 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,904 [mcmc] New sample, #314:
   Omega_m:0.2451294
 2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': -0.11836021496707455}
 2023-07-02 10:24:40,904 [prior] Evaluating prior at array([-0.11836021])
 2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': 0.03883621754101313}
 2023-07-02 10:24:40,904 [prior] Evaluating prior at array([0.03883622])
 2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': 0.0676623855364892}
 2023-07-02 10:24:40,904 [prior] Evaluating prior at array([0.06766239])
 2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': -0.15589147019995037}
 2023-07-02 10:24:40,904 [prior] Evaluating prior at array([-0.15589147])
 2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,905 [model] Posterior to be computed for parameters {'Omega_m': 0.26381175231380855}
 2023-07-02 10:24:40,905 [prior] Evaluating prior at array([0.26381175])
 2023-07-02 10:24:40,905 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,905 [model] Got input parameters: {'Omega_m': 0.26381175231380855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,905 [classy] Got parameters {'Omega_m': 0.26381175231380855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,905 [classy] Computing new state
 2023-07-02 10:24:40,905 [classy] Setting parameters: {'Omega_m': 0.26381175231380855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:40,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.55795405981857}
 2023-07-02 10:24:40,956 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:40,959 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.165173
 2023-07-02 10:24:40,959 [model] Computed derived parameters: {}
 2023-07-02 10:24:40,959 [mcmc] New sample, #315:
   Omega_m:0.2917409
 2023-07-02 10:24:40,959 [model] Posterior to be computed for parameters {'Omega_m': 0.062372495751917834}
 2023-07-02 10:24:40,959 [prior] Evaluating prior at array([0.0623725])
 2023-07-02 10:24:40,959 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:40,960 [model] Posterior to be computed for parameters {'Omega_m': 0.1865817377094908}
 2023-07-02 10:24:40,960 [prior] Evaluating prior at array([0.18658174])
 2023-07-02 10:24:40,960 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:40,960 [model] Got input parameters: {'Omega_m': 0.1865817377094908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,960 [classy] Got parameters {'Omega_m': 0.1865817377094908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:40,960 [classy] Computing new state
 2023-07-02 10:24:40,960 [classy] Setting parameters: {'Omega_m': 0.1865817377094908, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.87006268004328}
 2023-07-02 10:24:41,022 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.39289
 2023-07-02 10:24:41,024 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,024 [model] Posterior to be computed for parameters {'Omega_m': 0.15476450403549796}
 2023-07-02 10:24:41,024 [prior] Evaluating prior at array([0.1547645])
 2023-07-02 10:24:41,024 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,024 [model] Got input parameters: {'Omega_m': 0.15476450403549796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,024 [classy] Got parameters {'Omega_m': 0.15476450403549796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,024 [classy] Computing new state
 2023-07-02 10:24:41,024 [classy] Setting parameters: {'Omega_m': 0.15476450403549796, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,071 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.09515566520267}
 2023-07-02 10:24:41,071 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,073 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.44005
 2023-07-02 10:24:41,073 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,073 [model] Posterior to be computed for parameters {'Omega_m': 0.18369946149853744}
 2023-07-02 10:24:41,073 [prior] Evaluating prior at array([0.18369946])
 2023-07-02 10:24:41,073 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,074 [model] Got input parameters: {'Omega_m': 0.18369946149853744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,074 [classy] Got parameters {'Omega_m': 0.18369946149853744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,074 [classy] Computing new state
 2023-07-02 10:24:41,074 [classy] Setting parameters: {'Omega_m': 0.18369946149853744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.40096744961411}
 2023-07-02 10:24:41,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.4714
 2023-07-02 10:24:41,149 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,149 [mcmc] New sample, #316:
   Omega_m:0.2638118
 2023-07-02 10:24:41,150 [model] Posterior to be computed for parameters {'Omega_m': -0.19924607467629551}
 2023-07-02 10:24:41,150 [prior] Evaluating prior at array([-0.19924607])
 2023-07-02 10:24:41,150 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,150 [model] Posterior to be computed for parameters {'Omega_m': 0.19656628729433154}
 2023-07-02 10:24:41,150 [prior] Evaluating prior at array([0.19656629])
 2023-07-02 10:24:41,150 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,150 [model] Got input parameters: {'Omega_m': 0.19656628729433154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,150 [classy] Got parameters {'Omega_m': 0.19656628729433154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,150 [classy] Computing new state
 2023-07-02 10:24:41,150 [classy] Setting parameters: {'Omega_m': 0.19656628729433154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,224 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.0767304131304}
 2023-07-02 10:24:41,224 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,226 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14288
 2023-07-02 10:24:41,226 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,227 [mcmc] New sample, #317:
   Omega_m:0.1836995
 2023-07-02 10:24:41,227 [model] Posterior to be computed for parameters {'Omega_m': -0.4809132868107351}
 2023-07-02 10:24:41,227 [prior] Evaluating prior at array([-0.48091329])
 2023-07-02 10:24:41,227 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,227 [model] Posterior to be computed for parameters {'Omega_m': 0.2576564773441015}
 2023-07-02 10:24:41,227 [prior] Evaluating prior at array([0.25765648])
 2023-07-02 10:24:41,227 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,227 [model] Got input parameters: {'Omega_m': 0.2576564773441015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,227 [classy] Got parameters {'Omega_m': 0.2576564773441015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,227 [classy] Computing new state
 2023-07-02 10:24:41,227 [classy] Setting parameters: {'Omega_m': 0.2576564773441015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.42377133575974}
 2023-07-02 10:24:41,284 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,286 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.213129
 2023-07-02 10:24:41,286 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,286 [mcmc] New sample, #318:
   Omega_m:0.1965663
 2023-07-02 10:24:41,286 [model] Posterior to be computed for parameters {'Omega_m': 0.2720018851978205}
 2023-07-02 10:24:41,286 [prior] Evaluating prior at array([0.27200189])
 2023-07-02 10:24:41,287 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,287 [model] Got input parameters: {'Omega_m': 0.2720018851978205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,287 [classy] Got parameters {'Omega_m': 0.2720018851978205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,287 [classy] Computing new state
 2023-07-02 10:24:41,287 [classy] Setting parameters: {'Omega_m': 0.2720018851978205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.43182680144588}
 2023-07-02 10:24:41,334 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,336 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111805
 2023-07-02 10:24:41,336 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,336 [mcmc] New sample, #319:
   Omega_m:0.2576565
 2023-07-02 10:24:41,336 [model] Posterior to be computed for parameters {'Omega_m': 0.2714610695293828}
 2023-07-02 10:24:41,336 [prior] Evaluating prior at array([0.27146107])
 2023-07-02 10:24:41,336 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,336 [model] Got input parameters: {'Omega_m': 0.2714610695293828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,336 [classy] Got parameters {'Omega_m': 0.2714610695293828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,336 [classy] Computing new state
 2023-07-02 10:24:41,336 [classy] Setting parameters: {'Omega_m': 0.2714610695293828, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.50530061516912}
 2023-07-02 10:24:41,384 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.114974
 2023-07-02 10:24:41,386 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,386 [mcmc] New sample, #320:
   Omega_m:0.2720019
 2023-07-02 10:24:41,386 [mcmc] Learn + convergence test @ 320 samples accepted.
 2023-07-02 10:24:41,386 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:41,392 [mcmc]  - Acceptance rate: 0.449
 2023-07-02 10:24:41,392 [mcmc]  - Condition number = 1
 2023-07-02 10:24:41,392 [mcmc]  - Eigenvalues = array([0.03899667])
 2023-07-02 10:24:41,392 [mcmc]  - Convergence of means: R-1 = 0.038997 after 256 accepted steps
 2023-07-02 10:24:41,393 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:41,393 [mcmc] array([[0.01232444]])
 2023-07-02 10:24:41,403 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:41,403 [model] Posterior to be computed for parameters {'Omega_m': 0.659893301851026}
 2023-07-02 10:24:41,403 [prior] Evaluating prior at array([0.6598933])
 2023-07-02 10:24:41,403 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,403 [model] Got input parameters: {'Omega_m': 0.659893301851026, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,403 [classy] Got parameters {'Omega_m': 0.659893301851026, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,403 [classy] Computing new state
 2023-07-02 10:24:41,403 [classy] Setting parameters: {'Omega_m': 0.659893301851026, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.63837735329697}
 2023-07-02 10:24:41,450 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,451 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.8056
 2023-07-02 10:24:41,452 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,452 [model] Posterior to be computed for parameters {'Omega_m': 0.12003370033669022}
 2023-07-02 10:24:41,452 [prior] Evaluating prior at array([0.1200337])
 2023-07-02 10:24:41,452 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,452 [model] Got input parameters: {'Omega_m': 0.12003370033669022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,452 [classy] Got parameters {'Omega_m': 0.12003370033669022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,452 [classy] Computing new state
 2023-07-02 10:24:41,452 [classy] Setting parameters: {'Omega_m': 0.12003370033669022, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,499 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.97507439586272}
 2023-07-02 10:24:41,499 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,501 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.14873
 2023-07-02 10:24:41,501 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,501 [model] Posterior to be computed for parameters {'Omega_m': 0.23485902472261655}
 2023-07-02 10:24:41,501 [prior] Evaluating prior at array([0.23485902])
 2023-07-02 10:24:41,501 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,501 [model] Got input parameters: {'Omega_m': 0.23485902472261655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,501 [classy] Got parameters {'Omega_m': 0.23485902472261655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,501 [classy] Computing new state
 2023-07-02 10:24:41,501 [classy] Setting parameters: {'Omega_m': 0.23485902472261655, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,548 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.78747411015152}
 2023-07-02 10:24:41,549 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,550 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.455745
 2023-07-02 10:24:41,550 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,550 [mcmc] New sample, #321:
   Omega_m:0.2714611
 2023-07-02 10:24:41,551 [model] Posterior to be computed for parameters {'Omega_m': 0.502925003606336}
 2023-07-02 10:24:41,551 [prior] Evaluating prior at array([0.502925])
 2023-07-02 10:24:41,551 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,551 [model] Got input parameters: {'Omega_m': 0.502925003606336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,551 [classy] Got parameters {'Omega_m': 0.502925003606336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,551 [classy] Computing new state
 2023-07-02 10:24:41,551 [classy] Setting parameters: {'Omega_m': 0.502925003606336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.0618220870738}
 2023-07-02 10:24:41,600 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,602 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.48441
 2023-07-02 10:24:41,602 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,602 [mcmc] New sample, #322:
   Omega_m:0.234859
 2023-07-02 10:24:41,602 [model] Posterior to be computed for parameters {'Omega_m': -0.22981471614532067}
 2023-07-02 10:24:41,602 [prior] Evaluating prior at array([-0.22981472])
 2023-07-02 10:24:41,602 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,602 [model] Posterior to be computed for parameters {'Omega_m': 0.5625522219332272}
 2023-07-02 10:24:41,602 [prior] Evaluating prior at array([0.56255222])
 2023-07-02 10:24:41,602 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,602 [model] Got input parameters: {'Omega_m': 0.5625522219332272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,602 [classy] Got parameters {'Omega_m': 0.5625522219332272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,602 [classy] Computing new state
 2023-07-02 10:24:41,602 [classy] Setting parameters: {'Omega_m': 0.5625522219332272, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.74980142396824}
 2023-07-02 10:24:41,658 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,659 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.30424
 2023-07-02 10:24:41,660 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,660 [mcmc] New sample, #323:
   Omega_m:0.502925
 2023-07-02 10:24:41,660 [model] Posterior to be computed for parameters {'Omega_m': 1.0815829483668415}
 2023-07-02 10:24:41,660 [prior] Evaluating prior at array([1.08158295])
 2023-07-02 10:24:41,660 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,660 [model] Posterior to be computed for parameters {'Omega_m': 0.039265173032374756}
 2023-07-02 10:24:41,660 [prior] Evaluating prior at array([0.03926517])
 2023-07-02 10:24:41,660 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,660 [model] Posterior to be computed for parameters {'Omega_m': 0.85095382281302}
 2023-07-02 10:24:41,660 [prior] Evaluating prior at array([0.85095382])
 2023-07-02 10:24:41,660 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,660 [model] Got input parameters: {'Omega_m': 0.85095382281302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,660 [classy] Got parameters {'Omega_m': 0.85095382281302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,660 [classy] Computing new state
 2023-07-02 10:24:41,660 [classy] Setting parameters: {'Omega_m': 0.85095382281302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.04935049444734}
 2023-07-02 10:24:41,708 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,710 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.02902
 2023-07-02 10:24:41,710 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,710 [model] Posterior to be computed for parameters {'Omega_m': -0.2596255748052363}
 2023-07-02 10:24:41,710 [prior] Evaluating prior at array([-0.25962557])
 2023-07-02 10:24:41,710 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,710 [model] Posterior to be computed for parameters {'Omega_m': 0.41983545186371785}
 2023-07-02 10:24:41,710 [prior] Evaluating prior at array([0.41983545])
 2023-07-02 10:24:41,710 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,711 [model] Got input parameters: {'Omega_m': 0.41983545186371785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,711 [classy] Got parameters {'Omega_m': 0.41983545186371785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,711 [classy] Computing new state
 2023-07-02 10:24:41,711 [classy] Setting parameters: {'Omega_m': 0.41983545186371785, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.01378602502828}
 2023-07-02 10:24:41,759 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.554467
 2023-07-02 10:24:41,760 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,760 [mcmc] New sample, #324:
   Omega_m:0.5625522
 2023-07-02 10:24:41,760 [model] Posterior to be computed for parameters {'Omega_m': 1.3413127131380616}
 2023-07-02 10:24:41,761 [prior] Evaluating prior at array([1.34131271])
 2023-07-02 10:24:41,761 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,761 [model] Posterior to be computed for parameters {'Omega_m': 0.2133296723061989}
 2023-07-02 10:24:41,761 [prior] Evaluating prior at array([0.21332967])
 2023-07-02 10:24:41,761 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,761 [model] Got input parameters: {'Omega_m': 0.2133296723061989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,761 [classy] Got parameters {'Omega_m': 0.2133296723061989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,761 [classy] Computing new state
 2023-07-02 10:24:41,761 [classy] Setting parameters: {'Omega_m': 0.2133296723061989, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 161.21539951461514}
 2023-07-02 10:24:41,809 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.793227
 2023-07-02 10:24:41,811 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,811 [mcmc] New sample, #325:
   Omega_m:0.4198355
 2023-07-02 10:24:41,811 [model] Posterior to be computed for parameters {'Omega_m': 0.7406859858846916}
 2023-07-02 10:24:41,811 [prior] Evaluating prior at array([0.74068599])
 2023-07-02 10:24:41,811 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,811 [model] Got input parameters: {'Omega_m': 0.7406859858846916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,811 [classy] Got parameters {'Omega_m': 0.7406859858846916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,811 [classy] Computing new state
 2023-07-02 10:24:41,811 [classy] Setting parameters: {'Omega_m': 0.7406859858846916, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.2547403285463}
 2023-07-02 10:24:41,858 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.142
 2023-07-02 10:24:41,860 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,860 [model] Posterior to be computed for parameters {'Omega_m': -0.23294378682238262}
 2023-07-02 10:24:41,860 [prior] Evaluating prior at array([-0.23294379])
 2023-07-02 10:24:41,860 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:41,860 [model] Posterior to be computed for parameters {'Omega_m': 0.1363389763377238}
 2023-07-02 10:24:41,860 [prior] Evaluating prior at array([0.13633898])
 2023-07-02 10:24:41,860 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,860 [model] Got input parameters: {'Omega_m': 0.1363389763377238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,861 [classy] Got parameters {'Omega_m': 0.1363389763377238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,861 [classy] Computing new state
 2023-07-02 10:24:41,861 [classy] Setting parameters: {'Omega_m': 0.1363389763377238, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,907 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.11461380527712}
 2023-07-02 10:24:41,907 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,909 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.25956
 2023-07-02 10:24:41,909 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,909 [model] Posterior to be computed for parameters {'Omega_m': 0.2771853565994251}
 2023-07-02 10:24:41,909 [prior] Evaluating prior at array([0.27718536])
 2023-07-02 10:24:41,909 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,909 [model] Got input parameters: {'Omega_m': 0.2771853565994251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,909 [classy] Got parameters {'Omega_m': 0.2771853565994251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,909 [classy] Computing new state
 2023-07-02 10:24:41,909 [classy] Setting parameters: {'Omega_m': 0.2771853565994251, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:41,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.7339272146062}
 2023-07-02 10:24:41,956 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:41,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0838835
 2023-07-02 10:24:41,958 [model] Computed derived parameters: {}
 2023-07-02 10:24:41,958 [mcmc] New sample, #326:
   Omega_m:0.2133297
 2023-07-02 10:24:41,958 [model] Posterior to be computed for parameters {'Omega_m': 0.40344838407467504}
 2023-07-02 10:24:41,958 [prior] Evaluating prior at array([0.40344838])
 2023-07-02 10:24:41,958 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:41,958 [model] Got input parameters: {'Omega_m': 0.40344838407467504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,958 [classy] Got parameters {'Omega_m': 0.40344838407467504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:41,958 [classy] Computing new state
 2023-07-02 10:24:41,959 [classy] Setting parameters: {'Omega_m': 0.40344838407467504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.5424875303604}
 2023-07-02 10:24:42,006 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,008 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.412051
 2023-07-02 10:24:42,008 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,008 [model] Posterior to be computed for parameters {'Omega_m': 0.4830273517219622}
 2023-07-02 10:24:42,008 [prior] Evaluating prior at array([0.48302735])
 2023-07-02 10:24:42,008 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,008 [model] Got input parameters: {'Omega_m': 0.4830273517219622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,008 [classy] Got parameters {'Omega_m': 0.4830273517219622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,009 [classy] Computing new state
 2023-07-02 10:24:42,009 [classy] Setting parameters: {'Omega_m': 0.4830273517219622, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.6169699300859}
 2023-07-02 10:24:42,060 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.23525
 2023-07-02 10:24:42,062 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,062 [model] Posterior to be computed for parameters {'Omega_m': 0.29692556175969914}
 2023-07-02 10:24:42,062 [prior] Evaluating prior at array([0.29692556])
 2023-07-02 10:24:42,062 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,062 [model] Got input parameters: {'Omega_m': 0.29692556175969914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,062 [classy] Got parameters {'Omega_m': 0.29692556175969914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,062 [classy] Computing new state
 2023-07-02 10:24:42,062 [classy] Setting parameters: {'Omega_m': 0.29692556175969914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,111 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1746903964477}
 2023-07-02 10:24:42,111 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,113 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.015641
 2023-07-02 10:24:42,113 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,113 [mcmc] New sample, #327:
   Omega_m:0.2771854
 2023-07-02 10:24:42,113 [model] Posterior to be computed for parameters {'Omega_m': 0.14384592363078158}
 2023-07-02 10:24:42,114 [prior] Evaluating prior at array([0.14384592])
 2023-07-02 10:24:42,114 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,114 [model] Got input parameters: {'Omega_m': 0.14384592363078158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,114 [classy] Got parameters {'Omega_m': 0.14384592363078158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,114 [classy] Computing new state
 2023-07-02 10:24:42,114 [classy] Setting parameters: {'Omega_m': 0.14384592363078158, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,162 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.43598937014045}
 2023-07-02 10:24:42,162 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,163 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.90394
 2023-07-02 10:24:42,164 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,164 [model] Posterior to be computed for parameters {'Omega_m': 0.3735843911966811}
 2023-07-02 10:24:42,164 [prior] Evaluating prior at array([0.37358439])
 2023-07-02 10:24:42,164 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,164 [model] Got input parameters: {'Omega_m': 0.3735843911966811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,164 [classy] Got parameters {'Omega_m': 0.3735843911966811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,164 [classy] Computing new state
 2023-07-02 10:24:42,164 [classy] Setting parameters: {'Omega_m': 0.3735843911966811, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,212 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.48689482797027}
 2023-07-02 10:24:42,212 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,214 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.198477
 2023-07-02 10:24:42,214 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,214 [mcmc] New sample, #328:
   Omega_m:0.2969256
 2023-07-02 10:24:42,214 [model] Posterior to be computed for parameters {'Omega_m': 0.32427887495765406}
 2023-07-02 10:24:42,214 [prior] Evaluating prior at array([0.32427887])
 2023-07-02 10:24:42,214 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,215 [model] Got input parameters: {'Omega_m': 0.32427887495765406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,215 [classy] Got parameters {'Omega_m': 0.32427887495765406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,215 [classy] Computing new state
 2023-07-02 10:24:42,215 [classy] Setting parameters: {'Omega_m': 0.32427887495765406, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8642169437191}
 2023-07-02 10:24:42,262 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,264 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00848877
 2023-07-02 10:24:42,264 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,264 [mcmc] New sample, #329:
   Omega_m:0.3735844
 2023-07-02 10:24:42,264 [model] Posterior to be computed for parameters {'Omega_m': -0.1693620989199789}
 2023-07-02 10:24:42,264 [prior] Evaluating prior at array([-0.1693621])
 2023-07-02 10:24:42,264 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:42,264 [model] Posterior to be computed for parameters {'Omega_m': 0.6025590133705816}
 2023-07-02 10:24:42,264 [prior] Evaluating prior at array([0.60255901])
 2023-07-02 10:24:42,264 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,264 [model] Got input parameters: {'Omega_m': 0.6025590133705816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,264 [classy] Got parameters {'Omega_m': 0.6025590133705816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,264 [classy] Computing new state
 2023-07-02 10:24:42,264 [classy] Setting parameters: {'Omega_m': 0.6025590133705816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.1129746221802}
 2023-07-02 10:24:42,312 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.90192
 2023-07-02 10:24:42,314 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,314 [model] Posterior to be computed for parameters {'Omega_m': 0.24415077334977903}
 2023-07-02 10:24:42,314 [prior] Evaluating prior at array([0.24415077])
 2023-07-02 10:24:42,314 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,314 [model] Got input parameters: {'Omega_m': 0.24415077334977903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,314 [classy] Got parameters {'Omega_m': 0.24415077334977903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,314 [classy] Computing new state
 2023-07-02 10:24:42,314 [classy] Setting parameters: {'Omega_m': 0.24415077334977903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,361 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.385509020039}
 2023-07-02 10:24:42,361 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,363 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.343825
 2023-07-02 10:24:42,363 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,363 [model] Posterior to be computed for parameters {'Omega_m': 0.3671402793651287}
 2023-07-02 10:24:42,364 [prior] Evaluating prior at array([0.36714028])
 2023-07-02 10:24:42,364 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,364 [model] Got input parameters: {'Omega_m': 0.3671402793651287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,364 [classy] Got parameters {'Omega_m': 0.3671402793651287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,364 [classy] Computing new state
 2023-07-02 10:24:42,364 [classy] Setting parameters: {'Omega_m': 0.3671402793651287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.15120918862218}
 2023-07-02 10:24:42,411 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,412 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.161163
 2023-07-02 10:24:42,413 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,413 [mcmc] New sample, #330:
   Omega_m:0.3242789
 2023-07-02 10:24:42,413 [model] Posterior to be computed for parameters {'Omega_m': 0.48740955476867676}
 2023-07-02 10:24:42,413 [prior] Evaluating prior at array([0.48740955])
 2023-07-02 10:24:42,413 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,413 [model] Got input parameters: {'Omega_m': 0.48740955476867676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,413 [classy] Got parameters {'Omega_m': 0.48740955476867676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,413 [classy] Computing new state
 2023-07-02 10:24:42,413 [classy] Setting parameters: {'Omega_m': 0.48740955476867676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.26902055142034}
 2023-07-02 10:24:42,461 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.2889
 2023-07-02 10:24:42,462 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,463 [model] Posterior to be computed for parameters {'Omega_m': 0.26249511098601025}
 2023-07-02 10:24:42,463 [prior] Evaluating prior at array([0.26249511])
 2023-07-02 10:24:42,463 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,463 [model] Got input parameters: {'Omega_m': 0.26249511098601025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,463 [classy] Got parameters {'Omega_m': 0.26249511098601025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,463 [classy] Computing new state
 2023-07-02 10:24:42,463 [classy] Setting parameters: {'Omega_m': 0.26249511098601025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.74172245436006}
 2023-07-02 10:24:42,511 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17485
 2023-07-02 10:24:42,512 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,513 [mcmc] New sample, #331:
   Omega_m:0.3671403
 2023-07-02 10:24:42,513 [model] Posterior to be computed for parameters {'Omega_m': 0.1585531552195668}
 2023-07-02 10:24:42,513 [prior] Evaluating prior at array([0.15855316])
 2023-07-02 10:24:42,513 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,513 [model] Got input parameters: {'Omega_m': 0.1585531552195668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,513 [classy] Got parameters {'Omega_m': 0.1585531552195668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,513 [classy] Computing new state
 2023-07-02 10:24:42,513 [classy] Setting parameters: {'Omega_m': 0.1585531552195668, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.3091312302472}
 2023-07-02 10:24:42,560 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,562 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.29276
 2023-07-02 10:24:42,562 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,562 [model] Posterior to be computed for parameters {'Omega_m': 0.4485543892027447}
 2023-07-02 10:24:42,562 [prior] Evaluating prior at array([0.44855439])
 2023-07-02 10:24:42,562 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,562 [model] Got input parameters: {'Omega_m': 0.4485543892027447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,562 [classy] Got parameters {'Omega_m': 0.4485543892027447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,562 [classy] Computing new state
 2023-07-02 10:24:42,562 [classy] Setting parameters: {'Omega_m': 0.4485543892027447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,609 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.46873812264752}
 2023-07-02 10:24:42,609 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,611 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.840473
 2023-07-02 10:24:42,611 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,611 [mcmc] New sample, #332:
   Omega_m:0.2624951
 2023-07-02 10:24:42,611 [model] Posterior to be computed for parameters {'Omega_m': 0.44373808913166485}
 2023-07-02 10:24:42,612 [prior] Evaluating prior at array([0.44373809])
 2023-07-02 10:24:42,612 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,612 [model] Got input parameters: {'Omega_m': 0.44373808913166485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,612 [classy] Got parameters {'Omega_m': 0.44373808913166485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,612 [classy] Computing new state
 2023-07-02 10:24:42,612 [classy] Setting parameters: {'Omega_m': 0.44373808913166485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.884257770616}
 2023-07-02 10:24:42,677 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,679 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.789555
 2023-07-02 10:24:42,679 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,680 [mcmc] New sample, #333:
   Omega_m:0.4485544
 2023-07-02 10:24:42,680 [model] Posterior to be computed for parameters {'Omega_m': -0.20669705696165291}
 2023-07-02 10:24:42,680 [prior] Evaluating prior at array([-0.20669706])
 2023-07-02 10:24:42,680 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:42,680 [model] Posterior to be computed for parameters {'Omega_m': 0.346880755918653}
 2023-07-02 10:24:42,680 [prior] Evaluating prior at array([0.34688076])
 2023-07-02 10:24:42,680 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,680 [model] Got input parameters: {'Omega_m': 0.346880755918653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,680 [classy] Got parameters {'Omega_m': 0.346880755918653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,680 [classy] Computing new state
 2023-07-02 10:24:42,680 [classy] Setting parameters: {'Omega_m': 0.346880755918653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,732 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.31242321195887}
 2023-07-02 10:24:42,733 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,734 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0669829
 2023-07-02 10:24:42,734 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,734 [mcmc] New sample, #334:
   Omega_m:0.4437381
 2023-07-02 10:24:42,735 [model] Posterior to be computed for parameters {'Omega_m': 0.07184849199864013}
 2023-07-02 10:24:42,735 [prior] Evaluating prior at array([0.07184849])
 2023-07-02 10:24:42,735 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:42,735 [model] Posterior to be computed for parameters {'Omega_m': 0.8718486197867703}
 2023-07-02 10:24:42,735 [prior] Evaluating prior at array([0.87184862])
 2023-07-02 10:24:42,735 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,735 [model] Got input parameters: {'Omega_m': 0.8718486197867703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,735 [classy] Got parameters {'Omega_m': 0.8718486197867703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,735 [classy] Computing new state
 2023-07-02 10:24:42,735 [classy] Setting parameters: {'Omega_m': 0.8718486197867703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,781 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.14770221577228}
 2023-07-02 10:24:42,781 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,783 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.39049
 2023-07-02 10:24:42,783 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,783 [model] Posterior to be computed for parameters {'Omega_m': 0.1513696866716494}
 2023-07-02 10:24:42,783 [prior] Evaluating prior at array([0.15136969])
 2023-07-02 10:24:42,783 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,783 [model] Got input parameters: {'Omega_m': 0.1513696866716494, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,784 [classy] Got parameters {'Omega_m': 0.1513696866716494, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,784 [classy] Computing new state
 2023-07-02 10:24:42,784 [classy] Setting parameters: {'Omega_m': 0.1513696866716494, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,831 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.81067875952124}
 2023-07-02 10:24:42,831 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.57785
 2023-07-02 10:24:42,833 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,833 [model] Posterior to be computed for parameters {'Omega_m': 0.14264891957824588}
 2023-07-02 10:24:42,833 [prior] Evaluating prior at array([0.14264892])
 2023-07-02 10:24:42,833 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,833 [model] Got input parameters: {'Omega_m': 0.14264891957824588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,833 [classy] Got parameters {'Omega_m': 0.14264891957824588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,833 [classy] Computing new state
 2023-07-02 10:24:42,833 [classy] Setting parameters: {'Omega_m': 0.14264891957824588, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.69973183741268}
 2023-07-02 10:24:42,881 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,883 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.95855
 2023-07-02 10:24:42,883 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,883 [model] Posterior to be computed for parameters {'Omega_m': 0.26085620089073785}
 2023-07-02 10:24:42,883 [prior] Evaluating prior at array([0.2608562])
 2023-07-02 10:24:42,883 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,883 [model] Got input parameters: {'Omega_m': 0.26085620089073785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,883 [classy] Got parameters {'Omega_m': 0.26085620089073785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,883 [classy] Computing new state
 2023-07-02 10:24:42,883 [classy] Setting parameters: {'Omega_m': 0.26085620089073785, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9715480413894}
 2023-07-02 10:24:42,932 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.187333
 2023-07-02 10:24:42,934 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,934 [mcmc] New sample, #335:
   Omega_m:0.3468808
 2023-07-02 10:24:42,934 [model] Posterior to be computed for parameters {'Omega_m': 0.4652357747195963}
 2023-07-02 10:24:42,935 [prior] Evaluating prior at array([0.46523577])
 2023-07-02 10:24:42,935 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,935 [model] Got input parameters: {'Omega_m': 0.4652357747195963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,935 [classy] Got parameters {'Omega_m': 0.4652357747195963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,935 [classy] Computing new state
 2023-07-02 10:24:42,935 [classy] Setting parameters: {'Omega_m': 0.4652357747195963, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:42,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.0626677857063}
 2023-07-02 10:24:42,981 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:42,983 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.02517
 2023-07-02 10:24:42,983 [model] Computed derived parameters: {}
 2023-07-02 10:24:42,983 [mcmc] New sample, #336:
   Omega_m:0.2608562
 2023-07-02 10:24:42,983 [model] Posterior to be computed for parameters {'Omega_m': 0.5052803590097305}
 2023-07-02 10:24:42,983 [prior] Evaluating prior at array([0.50528036])
 2023-07-02 10:24:42,983 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:42,983 [model] Got input parameters: {'Omega_m': 0.5052803590097305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,983 [classy] Got parameters {'Omega_m': 0.5052803590097305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:42,983 [classy] Computing new state
 2023-07-02 10:24:42,983 [classy] Setting parameters: {'Omega_m': 0.5052803590097305, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.88183902488632}
 2023-07-02 10:24:43,035 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,037 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.51481
 2023-07-02 10:24:43,037 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,037 [model] Posterior to be computed for parameters {'Omega_m': 0.45911757138097076}
 2023-07-02 10:24:43,037 [prior] Evaluating prior at array([0.45911757])
 2023-07-02 10:24:43,037 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,037 [model] Got input parameters: {'Omega_m': 0.45911757138097076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,037 [classy] Got parameters {'Omega_m': 0.45911757138097076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,037 [classy] Computing new state
 2023-07-02 10:24:43,037 [classy] Setting parameters: {'Omega_m': 0.45911757138097076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.57249468984796}
 2023-07-02 10:24:43,083 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,085 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.955985
 2023-07-02 10:24:43,085 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,085 [mcmc] New sample, #337:
   Omega_m:0.4652358
 2023-07-02 10:24:43,085 [model] Posterior to be computed for parameters {'Omega_m': 0.14670921660758607}
 2023-07-02 10:24:43,085 [prior] Evaluating prior at array([0.14670922])
 2023-07-02 10:24:43,085 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,085 [model] Got input parameters: {'Omega_m': 0.14670921660758607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,085 [classy] Got parameters {'Omega_m': 0.14670921660758607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,085 [classy] Computing new state
 2023-07-02 10:24:43,085 [classy] Setting parameters: {'Omega_m': 0.14670921660758607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.81092347338438}
 2023-07-02 10:24:43,132 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.77639
 2023-07-02 10:24:43,133 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,133 [model] Posterior to be computed for parameters {'Omega_m': 0.5585755368452686}
 2023-07-02 10:24:43,133 [prior] Evaluating prior at array([0.55857554])
 2023-07-02 10:24:43,134 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,134 [model] Got input parameters: {'Omega_m': 0.5585755368452686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,134 [classy] Got parameters {'Omega_m': 0.5585755368452686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,134 [classy] Computing new state
 2023-07-02 10:24:43,134 [classy] Setting parameters: {'Omega_m': 0.5585755368452686, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.02247993634876}
 2023-07-02 10:24:43,180 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,182 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.24666
 2023-07-02 10:24:43,182 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,182 [model] Posterior to be computed for parameters {'Omega_m': 0.19244306846874792}
 2023-07-02 10:24:43,182 [prior] Evaluating prior at array([0.19244307])
 2023-07-02 10:24:43,182 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,182 [model] Got input parameters: {'Omega_m': 0.19244306846874792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,182 [classy] Got parameters {'Omega_m': 0.19244306846874792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,182 [classy] Computing new state
 2023-07-02 10:24:43,182 [classy] Setting parameters: {'Omega_m': 0.19244306846874792, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.80887754914818}
 2023-07-02 10:24:43,229 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.24211
 2023-07-02 10:24:43,230 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,230 [model] Posterior to be computed for parameters {'Omega_m': 0.4277140357589607}
 2023-07-02 10:24:43,230 [prior] Evaluating prior at array([0.42771404])
 2023-07-02 10:24:43,231 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,231 [model] Got input parameters: {'Omega_m': 0.4277140357589607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,231 [classy] Got parameters {'Omega_m': 0.4277140357589607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,231 [classy] Computing new state
 2023-07-02 10:24:43,231 [classy] Setting parameters: {'Omega_m': 0.4277140357589607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.29915024059824}
 2023-07-02 10:24:43,281 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,283 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.62856
 2023-07-02 10:24:43,284 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,284 [mcmc] New sample, #338:
   Omega_m:0.4591176
 2023-07-02 10:24:43,284 [model] Posterior to be computed for parameters {'Omega_m': 0.5604789901828179}
 2023-07-02 10:24:43,284 [prior] Evaluating prior at array([0.56047899])
 2023-07-02 10:24:43,284 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,284 [model] Got input parameters: {'Omega_m': 0.5604789901828179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,284 [classy] Got parameters {'Omega_m': 0.5604789901828179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,284 [classy] Computing new state
 2023-07-02 10:24:43,284 [classy] Setting parameters: {'Omega_m': 0.5604789901828179, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.89171456117029}
 2023-07-02 10:24:43,354 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,357 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.27418
 2023-07-02 10:24:43,357 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,357 [model] Posterior to be computed for parameters {'Omega_m': 1.0258895395646146}
 2023-07-02 10:24:43,357 [prior] Evaluating prior at array([1.02588954])
 2023-07-02 10:24:43,357 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,357 [model] Posterior to be computed for parameters {'Omega_m': -0.2952585729695062}
 2023-07-02 10:24:43,357 [prior] Evaluating prior at array([-0.29525857])
 2023-07-02 10:24:43,358 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,358 [model] Posterior to be computed for parameters {'Omega_m': 0.3919191848475967}
 2023-07-02 10:24:43,358 [prior] Evaluating prior at array([0.39191918])
 2023-07-02 10:24:43,358 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,358 [model] Got input parameters: {'Omega_m': 0.3919191848475967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,358 [classy] Got parameters {'Omega_m': 0.3919191848475967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,358 [classy] Computing new state
 2023-07-02 10:24:43,358 [classy] Setting parameters: {'Omega_m': 0.3919191848475967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,416 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.65396112785308}
 2023-07-02 10:24:43,416 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,418 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.322116
 2023-07-02 10:24:43,418 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,418 [mcmc] New sample, #339:
   Omega_m:0.427714
 2023-07-02 10:24:43,419 [model] Posterior to be computed for parameters {'Omega_m': 0.2313428560768509}
 2023-07-02 10:24:43,419 [prior] Evaluating prior at array([0.23134286])
 2023-07-02 10:24:43,419 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,419 [model] Got input parameters: {'Omega_m': 0.2313428560768509, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,419 [classy] Got parameters {'Omega_m': 0.2313428560768509, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,419 [classy] Computing new state
 2023-07-02 10:24:43,419 [classy] Setting parameters: {'Omega_m': 0.2313428560768509, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,467 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.32973111199684}
 2023-07-02 10:24:43,467 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,470 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.50313
 2023-07-02 10:24:43,470 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,470 [mcmc] New sample, #340:
   Omega_m:0.3919192
 2023-07-02 10:24:43,470 [model] Posterior to be computed for parameters {'Omega_m': 0.08563871528441033}
 2023-07-02 10:24:43,470 [prior] Evaluating prior at array([0.08563872])
 2023-07-02 10:24:43,470 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,470 [model] Posterior to be computed for parameters {'Omega_m': 0.014361644866009188}
 2023-07-02 10:24:43,470 [prior] Evaluating prior at array([0.01436164])
 2023-07-02 10:24:43,471 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,471 [model] Posterior to be computed for parameters {'Omega_m': 0.5163885394599578}
 2023-07-02 10:24:43,471 [prior] Evaluating prior at array([0.51638854])
 2023-07-02 10:24:43,471 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,471 [model] Got input parameters: {'Omega_m': 0.5163885394599578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,471 [classy] Got parameters {'Omega_m': 0.5163885394599578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,471 [classy] Computing new state
 2023-07-02 10:24:43,471 [classy] Setting parameters: {'Omega_m': 0.5163885394599578, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,516 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.04429148533478}
 2023-07-02 10:24:43,516 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,518 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.66062
 2023-07-02 10:24:43,519 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,519 [mcmc] New sample, #341:
   Omega_m:0.2313429
 2023-07-02 10:24:43,519 [model] Posterior to be computed for parameters {'Omega_m': 0.25594015048362767}
 2023-07-02 10:24:43,519 [prior] Evaluating prior at array([0.25594015])
 2023-07-02 10:24:43,519 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,519 [model] Got input parameters: {'Omega_m': 0.25594015048362767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,519 [classy] Got parameters {'Omega_m': 0.25594015048362767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,519 [classy] Computing new state
 2023-07-02 10:24:43,520 [classy] Setting parameters: {'Omega_m': 0.25594015048362767, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.66829498730712}
 2023-07-02 10:24:43,566 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,567 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.227758
 2023-07-02 10:24:43,568 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,568 [mcmc] New sample, #342:
   Omega_m:0.5163885
 2023-07-02 10:24:43,568 [model] Posterior to be computed for parameters {'Omega_m': 0.22264926960659917}
 2023-07-02 10:24:43,568 [prior] Evaluating prior at array([0.22264927])
 2023-07-02 10:24:43,568 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,568 [model] Got input parameters: {'Omega_m': 0.22264926960659917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,568 [classy] Got parameters {'Omega_m': 0.22264926960659917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,568 [classy] Computing new state
 2023-07-02 10:24:43,568 [classy] Setting parameters: {'Omega_m': 0.22264926960659917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.69933398372078}
 2023-07-02 10:24:43,615 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.632894
 2023-07-02 10:24:43,616 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,616 [mcmc] New sample, #343:
   Omega_m:0.2559402
 2023-07-02 10:24:43,616 [model] Posterior to be computed for parameters {'Omega_m': 0.2549609215988391}
 2023-07-02 10:24:43,617 [prior] Evaluating prior at array([0.25496092])
 2023-07-02 10:24:43,617 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,617 [model] Got input parameters: {'Omega_m': 0.2549609215988391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,617 [classy] Got parameters {'Omega_m': 0.2549609215988391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,617 [classy] Computing new state
 2023-07-02 10:24:43,617 [classy] Setting parameters: {'Omega_m': 0.2549609215988391, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.80841037309568}
 2023-07-02 10:24:43,663 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.236355
 2023-07-02 10:24:43,665 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,665 [mcmc] New sample, #344:
   Omega_m:0.2226493
 2023-07-02 10:24:43,665 [model] Posterior to be computed for parameters {'Omega_m': -0.5367928599403415}
 2023-07-02 10:24:43,665 [prior] Evaluating prior at array([-0.53679286])
 2023-07-02 10:24:43,665 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,665 [model] Posterior to be computed for parameters {'Omega_m': 0.04525645269292344}
 2023-07-02 10:24:43,665 [prior] Evaluating prior at array([0.04525645])
 2023-07-02 10:24:43,665 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,665 [model] Posterior to be computed for parameters {'Omega_m': 0.42214874368410904}
 2023-07-02 10:24:43,665 [prior] Evaluating prior at array([0.42214874])
 2023-07-02 10:24:43,665 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,665 [model] Got input parameters: {'Omega_m': 0.42214874368410904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,665 [classy] Got parameters {'Omega_m': 0.42214874368410904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,665 [classy] Computing new state
 2023-07-02 10:24:43,665 [classy] Setting parameters: {'Omega_m': 0.42214874368410904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.80261168440575}
 2023-07-02 10:24:43,712 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,714 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.575861
 2023-07-02 10:24:43,714 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,714 [mcmc] New sample, #345:
   Omega_m:0.2549609
 2023-07-02 10:24:43,714 [model] Posterior to be computed for parameters {'Omega_m': 0.7859970612437794}
 2023-07-02 10:24:43,714 [prior] Evaluating prior at array([0.78599706])
 2023-07-02 10:24:43,714 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,714 [model] Got input parameters: {'Omega_m': 0.7859970612437794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,714 [classy] Got parameters {'Omega_m': 0.7859970612437794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,714 [classy] Computing new state
 2023-07-02 10:24:43,714 [classy] Setting parameters: {'Omega_m': 0.7859970612437794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,765 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.01841101222831}
 2023-07-02 10:24:43,766 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.91166
 2023-07-02 10:24:43,770 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,770 [model] Posterior to be computed for parameters {'Omega_m': 0.8531588240877295}
 2023-07-02 10:24:43,770 [prior] Evaluating prior at array([0.85315882])
 2023-07-02 10:24:43,770 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,770 [model] Got input parameters: {'Omega_m': 0.8531588240877295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,770 [classy] Got parameters {'Omega_m': 0.8531588240877295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,770 [classy] Computing new state
 2023-07-02 10:24:43,770 [classy] Setting parameters: {'Omega_m': 0.8531588240877295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.95303468646857}
 2023-07-02 10:24:43,827 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,829 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.06713
 2023-07-02 10:24:43,829 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,829 [model] Posterior to be computed for parameters {'Omega_m': 0.08378386579509162}
 2023-07-02 10:24:43,829 [prior] Evaluating prior at array([0.08378387])
 2023-07-02 10:24:43,830 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:43,830 [model] Posterior to be computed for parameters {'Omega_m': 0.10975719061785266}
 2023-07-02 10:24:43,830 [prior] Evaluating prior at array([0.10975719])
 2023-07-02 10:24:43,830 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,830 [model] Got input parameters: {'Omega_m': 0.10975719061785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,830 [classy] Got parameters {'Omega_m': 0.10975719061785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,830 [classy] Computing new state
 2023-07-02 10:24:43,830 [classy] Setting parameters: {'Omega_m': 0.10975719061785266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.57525948776947}
 2023-07-02 10:24:43,881 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,883 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.80247
 2023-07-02 10:24:43,883 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,884 [model] Posterior to be computed for parameters {'Omega_m': 0.9857292676817642}
 2023-07-02 10:24:43,884 [prior] Evaluating prior at array([0.98572927])
 2023-07-02 10:24:43,884 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,884 [model] Got input parameters: {'Omega_m': 0.9857292676817642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,884 [classy] Got parameters {'Omega_m': 0.9857292676817642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,884 [classy] Computing new state
 2023-07-02 10:24:43,884 [classy] Setting parameters: {'Omega_m': 0.9857292676817642, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.627609636173}
 2023-07-02 10:24:43,932 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.36409
 2023-07-02 10:24:43,934 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,934 [model] Posterior to be computed for parameters {'Omega_m': 0.1319142983723855}
 2023-07-02 10:24:43,934 [prior] Evaluating prior at array([0.1319143])
 2023-07-02 10:24:43,935 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,935 [model] Got input parameters: {'Omega_m': 0.1319142983723855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,935 [classy] Got parameters {'Omega_m': 0.1319142983723855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,935 [classy] Computing new state
 2023-07-02 10:24:43,935 [classy] Setting parameters: {'Omega_m': 0.1319142983723855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:43,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 177.1321458402311}
 2023-07-02 10:24:43,981 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:43,983 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.48434
 2023-07-02 10:24:43,983 [model] Computed derived parameters: {}
 2023-07-02 10:24:43,983 [model] Posterior to be computed for parameters {'Omega_m': 0.27032583919259134}
 2023-07-02 10:24:43,983 [prior] Evaluating prior at array([0.27032584])
 2023-07-02 10:24:43,983 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:43,983 [model] Got input parameters: {'Omega_m': 0.27032583919259134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,983 [classy] Got parameters {'Omega_m': 0.27032583919259134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:43,983 [classy] Computing new state
 2023-07-02 10:24:43,983 [classy] Setting parameters: {'Omega_m': 0.27032583919259134, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.65993466576168}
 2023-07-02 10:24:44,031 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,032 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.121789
 2023-07-02 10:24:44,032 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,032 [mcmc] New sample, #346:
   Omega_m:0.4221487
 2023-07-02 10:24:44,033 [model] Posterior to be computed for parameters {'Omega_m': 0.2802083109042294}
 2023-07-02 10:24:44,033 [prior] Evaluating prior at array([0.28020831])
 2023-07-02 10:24:44,033 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,033 [model] Got input parameters: {'Omega_m': 0.2802083109042294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,033 [classy] Got parameters {'Omega_m': 0.2802083109042294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,033 [classy] Computing new state
 2023-07-02 10:24:44,033 [classy] Setting parameters: {'Omega_m': 0.2802083109042294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3320317736816}
 2023-07-02 10:24:44,079 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,081 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0696039
 2023-07-02 10:24:44,081 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,081 [mcmc] New sample, #347:
   Omega_m:0.2703258
 2023-07-02 10:24:44,082 [model] Posterior to be computed for parameters {'Omega_m': 0.5100726103355833}
 2023-07-02 10:24:44,082 [prior] Evaluating prior at array([0.51007261])
 2023-07-02 10:24:44,082 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,082 [model] Got input parameters: {'Omega_m': 0.5100726103355833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,082 [classy] Got parameters {'Omega_m': 0.5100726103355833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,082 [classy] Computing new state
 2023-07-02 10:24:44,082 [classy] Setting parameters: {'Omega_m': 0.5100726103355833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.51823021835528}
 2023-07-02 10:24:44,130 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,132 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.57724
 2023-07-02 10:24:44,132 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,132 [model] Posterior to be computed for parameters {'Omega_m': 0.3427387587367304}
 2023-07-02 10:24:44,132 [prior] Evaluating prior at array([0.34273876])
 2023-07-02 10:24:44,132 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,132 [model] Got input parameters: {'Omega_m': 0.3427387587367304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,132 [classy] Got parameters {'Omega_m': 0.3427387587367304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,132 [classy] Computing new state
 2023-07-02 10:24:44,132 [classy] Setting parameters: {'Omega_m': 0.3427387587367304, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,179 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.76852611962065}
 2023-07-02 10:24:44,179 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,181 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.052372
 2023-07-02 10:24:44,181 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,181 [mcmc] New sample, #348:
   Omega_m:0.2802083
 2023-07-02 10:24:44,181 [model] Posterior to be computed for parameters {'Omega_m': 0.8127495723151039}
 2023-07-02 10:24:44,181 [prior] Evaluating prior at array([0.81274957])
 2023-07-02 10:24:44,181 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,181 [model] Got input parameters: {'Omega_m': 0.8127495723151039, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,181 [classy] Got parameters {'Omega_m': 0.8127495723151039, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,181 [classy] Computing new state
 2023-07-02 10:24:44,181 [classy] Setting parameters: {'Omega_m': 0.8127495723151039, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.76373064153115}
 2023-07-02 10:24:44,228 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.37035
 2023-07-02 10:24:44,230 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,230 [model] Posterior to be computed for parameters {'Omega_m': 0.6905751989782409}
 2023-07-02 10:24:44,230 [prior] Evaluating prior at array([0.6905752])
 2023-07-02 10:24:44,230 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,230 [model] Got input parameters: {'Omega_m': 0.6905751989782409, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,231 [classy] Got parameters {'Omega_m': 0.6905751989782409, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,231 [classy] Computing new state
 2023-07-02 10:24:44,231 [classy] Setting parameters: {'Omega_m': 0.6905751989782409, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,277 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.90871220796458}
 2023-07-02 10:24:44,277 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.3062
 2023-07-02 10:24:44,279 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,279 [model] Posterior to be computed for parameters {'Omega_m': -0.010868163143254672}
 2023-07-02 10:24:44,279 [prior] Evaluating prior at array([-0.01086816])
 2023-07-02 10:24:44,279 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:44,279 [model] Posterior to be computed for parameters {'Omega_m': 0.5158900310035739}
 2023-07-02 10:24:44,279 [prior] Evaluating prior at array([0.51589003])
 2023-07-02 10:24:44,279 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,279 [model] Got input parameters: {'Omega_m': 0.5158900310035739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,279 [classy] Got parameters {'Omega_m': 0.5158900310035739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,279 [classy] Computing new state
 2023-07-02 10:24:44,279 [classy] Setting parameters: {'Omega_m': 0.5158900310035739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,326 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.0814860662557}
 2023-07-02 10:24:44,326 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,328 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.654
 2023-07-02 10:24:44,328 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,328 [mcmc] New sample, #349:
   Omega_m:0.3427388
 2023-07-02 10:24:44,328 [model] Posterior to be computed for parameters {'Omega_m': 0.633032507668241}
 2023-07-02 10:24:44,328 [prior] Evaluating prior at array([0.63303251])
 2023-07-02 10:24:44,328 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,328 [model] Got input parameters: {'Omega_m': 0.633032507668241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,328 [classy] Got parameters {'Omega_m': 0.633032507668241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,328 [classy] Computing new state
 2023-07-02 10:24:44,328 [classy] Setting parameters: {'Omega_m': 0.633032507668241, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,375 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.22468677171638}
 2023-07-02 10:24:44,375 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,377 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.37636
 2023-07-02 10:24:44,377 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,377 [model] Posterior to be computed for parameters {'Omega_m': 0.5351123470039459}
 2023-07-02 10:24:44,377 [prior] Evaluating prior at array([0.53511235])
 2023-07-02 10:24:44,378 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,378 [model] Got input parameters: {'Omega_m': 0.5351123470039459, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,378 [classy] Got parameters {'Omega_m': 0.5351123470039459, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,378 [classy] Computing new state
 2023-07-02 10:24:44,378 [classy] Setting parameters: {'Omega_m': 0.5351123470039459, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,424 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.67308895188961}
 2023-07-02 10:24:44,424 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,426 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.91482
 2023-07-02 10:24:44,426 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,426 [mcmc] New sample, #350:
   Omega_m:0.51589
 2023-07-02 10:24:44,427 [model] Posterior to be computed for parameters {'Omega_m': 0.593840642476892}
 2023-07-02 10:24:44,427 [prior] Evaluating prior at array([0.59384064])
 2023-07-02 10:24:44,427 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,427 [model] Got input parameters: {'Omega_m': 0.593840642476892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,427 [classy] Got parameters {'Omega_m': 0.593840642476892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,427 [classy] Computing new state
 2023-07-02 10:24:44,427 [classy] Setting parameters: {'Omega_m': 0.593840642476892, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.67172950465041}
 2023-07-02 10:24:44,474 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.76901
 2023-07-02 10:24:44,476 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,476 [model] Posterior to be computed for parameters {'Omega_m': 0.8487991676140274}
 2023-07-02 10:24:44,476 [prior] Evaluating prior at array([0.84879917])
 2023-07-02 10:24:44,476 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,476 [model] Got input parameters: {'Omega_m': 0.8487991676140274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,476 [classy] Got parameters {'Omega_m': 0.8487991676140274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,476 [classy] Computing new state
 2023-07-02 10:24:44,476 [classy] Setting parameters: {'Omega_m': 0.8487991676140274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.14373464339094}
 2023-07-02 10:24:44,523 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.99178
 2023-07-02 10:24:44,525 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,525 [model] Posterior to be computed for parameters {'Omega_m': -0.039649836427738894}
 2023-07-02 10:24:44,525 [prior] Evaluating prior at array([-0.03964984])
 2023-07-02 10:24:44,525 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:44,525 [model] Posterior to be computed for parameters {'Omega_m': 0.5352412902503053}
 2023-07-02 10:24:44,525 [prior] Evaluating prior at array([0.53524129])
 2023-07-02 10:24:44,525 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,525 [model] Got input parameters: {'Omega_m': 0.5352412902503053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,525 [classy] Got parameters {'Omega_m': 0.5352412902503053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,525 [classy] Computing new state
 2023-07-02 10:24:44,526 [classy] Setting parameters: {'Omega_m': 0.5352412902503053, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.66381831345583}
 2023-07-02 10:24:44,574 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.9166
 2023-07-02 10:24:44,575 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,575 [mcmc] New sample, #351:
   Omega_m:0.5351123
 2023-07-02 10:24:44,576 [model] Posterior to be computed for parameters {'Omega_m': 0.6621716215042605}
 2023-07-02 10:24:44,576 [prior] Evaluating prior at array([0.66217162])
 2023-07-02 10:24:44,576 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,576 [model] Got input parameters: {'Omega_m': 0.6621716215042605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,576 [classy] Got parameters {'Omega_m': 0.6621716215042605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,576 [classy] Computing new state
 2023-07-02 10:24:44,576 [classy] Setting parameters: {'Omega_m': 0.6621716215042605, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,624 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.50700134686988}
 2023-07-02 10:24:44,624 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,625 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.84242
 2023-07-02 10:24:44,626 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,626 [model] Posterior to be computed for parameters {'Omega_m': 0.7879682746358245}
 2023-07-02 10:24:44,626 [prior] Evaluating prior at array([0.78796827])
 2023-07-02 10:24:44,626 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,626 [model] Got input parameters: {'Omega_m': 0.7879682746358245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,626 [classy] Got parameters {'Omega_m': 0.7879682746358245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,626 [classy] Computing new state
 2023-07-02 10:24:44,626 [classy] Setting parameters: {'Omega_m': 0.7879682746358245, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,675 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.92435925673924}
 2023-07-02 10:24:44,675 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,677 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.94537
 2023-07-02 10:24:44,677 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,677 [model] Posterior to be computed for parameters {'Omega_m': 0.8034765891747773}
 2023-07-02 10:24:44,677 [prior] Evaluating prior at array([0.80347659])
 2023-07-02 10:24:44,678 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,678 [model] Got input parameters: {'Omega_m': 0.8034765891747773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,678 [classy] Got parameters {'Omega_m': 0.8034765891747773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,678 [classy] Computing new state
 2023-07-02 10:24:44,678 [classy] Setting parameters: {'Omega_m': 0.8034765891747773, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.19339252737063}
 2023-07-02 10:24:44,726 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,727 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.21106
 2023-07-02 10:24:44,728 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,728 [mcmc] New sample, #352:
   Omega_m:0.5352413
 2023-07-02 10:24:44,728 [model] Posterior to be computed for parameters {'Omega_m': 0.5424985376793106}
 2023-07-02 10:24:44,728 [prior] Evaluating prior at array([0.54249854])
 2023-07-02 10:24:44,728 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,728 [model] Got input parameters: {'Omega_m': 0.5424985376793106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,728 [classy] Got parameters {'Omega_m': 0.5424985376793106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,728 [classy] Computing new state
 2023-07-02 10:24:44,728 [classy] Setting parameters: {'Omega_m': 0.5424985376793106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.14559277972083}
 2023-07-02 10:24:44,780 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.01778
 2023-07-02 10:24:44,781 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,781 [mcmc] New sample, #353:
   Omega_m:0.8034766
 2023-07-02 10:24:44,782 [model] Posterior to be computed for parameters {'Omega_m': 0.9765924049746053}
 2023-07-02 10:24:44,782 [prior] Evaluating prior at array([0.9765924])
 2023-07-02 10:24:44,782 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,782 [model] Got input parameters: {'Omega_m': 0.9765924049746053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,782 [classy] Got parameters {'Omega_m': 0.9765924049746053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,782 [classy] Computing new state
 2023-07-02 10:24:44,782 [classy] Setting parameters: {'Omega_m': 0.9765924049746053, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.96780801672365}
 2023-07-02 10:24:44,828 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.20597
 2023-07-02 10:24:44,830 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,830 [model] Posterior to be computed for parameters {'Omega_m': 0.500729709420488}
 2023-07-02 10:24:44,830 [prior] Evaluating prior at array([0.50072971])
 2023-07-02 10:24:44,830 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,830 [model] Got input parameters: {'Omega_m': 0.500729709420488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,830 [classy] Got parameters {'Omega_m': 0.500729709420488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,830 [classy] Computing new state
 2023-07-02 10:24:44,830 [classy] Setting parameters: {'Omega_m': 0.500729709420488, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.2303385722492}
 2023-07-02 10:24:44,879 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45624
 2023-07-02 10:24:44,881 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,881 [mcmc] New sample, #354:
   Omega_m:0.5424985
 2023-07-02 10:24:44,881 [model] Posterior to be computed for parameters {'Omega_m': 0.2890519350608233}
 2023-07-02 10:24:44,881 [prior] Evaluating prior at array([0.28905194])
 2023-07-02 10:24:44,881 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,881 [model] Got input parameters: {'Omega_m': 0.2890519350608233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,881 [classy] Got parameters {'Omega_m': 0.2890519350608233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,881 [classy] Computing new state
 2023-07-02 10:24:44,881 [classy] Setting parameters: {'Omega_m': 0.2890519350608233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.1772958027618}
 2023-07-02 10:24:44,928 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0359406
 2023-07-02 10:24:44,930 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,930 [mcmc] New sample, #355:
   Omega_m:0.5007297
 2023-07-02 10:24:44,930 [model] Posterior to be computed for parameters {'Omega_m': -0.010780879644781916}
 2023-07-02 10:24:44,930 [prior] Evaluating prior at array([-0.01078088])
 2023-07-02 10:24:44,930 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:44,930 [model] Posterior to be computed for parameters {'Omega_m': 0.05213690248323974}
 2023-07-02 10:24:44,930 [prior] Evaluating prior at array([0.0521369])
 2023-07-02 10:24:44,930 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:44,930 [model] Posterior to be computed for parameters {'Omega_m': 0.669256904499597}
 2023-07-02 10:24:44,930 [prior] Evaluating prior at array([0.6692569])
 2023-07-02 10:24:44,931 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,931 [model] Got input parameters: {'Omega_m': 0.669256904499597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,931 [classy] Got parameters {'Omega_m': 0.669256904499597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,931 [classy] Computing new state
 2023-07-02 10:24:44,931 [classy] Setting parameters: {'Omega_m': 0.669256904499597, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:44,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.10152242592675}
 2023-07-02 10:24:44,977 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:44,978 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.95731
 2023-07-02 10:24:44,979 [model] Computed derived parameters: {}
 2023-07-02 10:24:44,979 [model] Posterior to be computed for parameters {'Omega_m': 0.555618471759565}
 2023-07-02 10:24:44,979 [prior] Evaluating prior at array([0.55561847])
 2023-07-02 10:24:44,979 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:44,979 [model] Got input parameters: {'Omega_m': 0.555618471759565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,979 [classy] Got parameters {'Omega_m': 0.555618471759565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:44,979 [classy] Computing new state
 2023-07-02 10:24:44,979 [classy] Setting parameters: {'Omega_m': 0.555618471759565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,026 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.22653830654869}
 2023-07-02 10:24:45,026 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,028 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.20409
 2023-07-02 10:24:45,028 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,028 [model] Posterior to be computed for parameters {'Omega_m': -0.0021427189608299035}
 2023-07-02 10:24:45,028 [prior] Evaluating prior at array([-0.00214272])
 2023-07-02 10:24:45,028 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:45,028 [model] Posterior to be computed for parameters {'Omega_m': 0.7696399707263206}
 2023-07-02 10:24:45,028 [prior] Evaluating prior at array([0.76963997])
 2023-07-02 10:24:45,028 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,028 [model] Got input parameters: {'Omega_m': 0.7696399707263206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,028 [classy] Got parameters {'Omega_m': 0.7696399707263206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,028 [classy] Computing new state
 2023-07-02 10:24:45,028 [classy] Setting parameters: {'Omega_m': 0.7696399707263206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.80898357916952}
 2023-07-02 10:24:45,073 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.63263
 2023-07-02 10:24:45,075 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,075 [model] Posterior to be computed for parameters {'Omega_m': 0.43774918469304214}
 2023-07-02 10:24:45,075 [prior] Evaluating prior at array([0.43774918])
 2023-07-02 10:24:45,075 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,075 [model] Got input parameters: {'Omega_m': 0.43774918469304214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,075 [classy] Got parameters {'Omega_m': 0.43774918469304214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,075 [classy] Computing new state
 2023-07-02 10:24:45,075 [classy] Setting parameters: {'Omega_m': 0.43774918469304214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,122 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.40715448534678}
 2023-07-02 10:24:45,122 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,124 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.727831
 2023-07-02 10:24:45,124 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,124 [mcmc] New sample, #356:
   Omega_m:0.2890519
 2023-07-02 10:24:45,124 [model] Posterior to be computed for parameters {'Omega_m': 0.43892656897882126}
 2023-07-02 10:24:45,124 [prior] Evaluating prior at array([0.43892657])
 2023-07-02 10:24:45,124 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,124 [model] Got input parameters: {'Omega_m': 0.43892656897882126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,124 [classy] Got parameters {'Omega_m': 0.43892656897882126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,124 [classy] Computing new state
 2023-07-02 10:24:45,124 [classy] Setting parameters: {'Omega_m': 0.43892656897882126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.30379850852572}
 2023-07-02 10:24:45,170 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,172 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.739825
 2023-07-02 10:24:45,172 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,172 [mcmc] New sample, #357:
   Omega_m:0.4377492
 2023-07-02 10:24:45,172 [model] Posterior to be computed for parameters {'Omega_m': -0.18028925982478644}
 2023-07-02 10:24:45,172 [prior] Evaluating prior at array([-0.18028926])
 2023-07-02 10:24:45,172 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:45,172 [model] Posterior to be computed for parameters {'Omega_m': 0.8557982885876529}
 2023-07-02 10:24:45,172 [prior] Evaluating prior at array([0.85579829])
 2023-07-02 10:24:45,172 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,172 [model] Got input parameters: {'Omega_m': 0.8557982885876529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,172 [classy] Got parameters {'Omega_m': 0.8557982885876529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,172 [classy] Computing new state
 2023-07-02 10:24:45,172 [classy] Setting parameters: {'Omega_m': 0.8557982885876529, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.83810467499187}
 2023-07-02 10:24:45,218 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.11277
 2023-07-02 10:24:45,220 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,220 [model] Posterior to be computed for parameters {'Omega_m': 0.4414296910401034}
 2023-07-02 10:24:45,220 [prior] Evaluating prior at array([0.44142969])
 2023-07-02 10:24:45,220 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,220 [model] Got input parameters: {'Omega_m': 0.4414296910401034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,221 [classy] Got parameters {'Omega_m': 0.4414296910401034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,221 [classy] Computing new state
 2023-07-02 10:24:45,221 [classy] Setting parameters: {'Omega_m': 0.4414296910401034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.0849722180762}
 2023-07-02 10:24:45,266 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.765554
 2023-07-02 10:24:45,268 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,269 [mcmc] New sample, #358:
   Omega_m:0.4389266
 2023-07-02 10:24:45,269 [model] Posterior to be computed for parameters {'Omega_m': 0.90058341504644}
 2023-07-02 10:24:45,269 [prior] Evaluating prior at array([0.90058342])
 2023-07-02 10:24:45,269 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,269 [model] Got input parameters: {'Omega_m': 0.90058341504644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,269 [classy] Got parameters {'Omega_m': 0.90058341504644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,269 [classy] Computing new state
 2023-07-02 10:24:45,269 [classy] Setting parameters: {'Omega_m': 0.90058341504644, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.94662591533205}
 2023-07-02 10:24:45,316 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.8884
 2023-07-02 10:24:45,318 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,318 [model] Posterior to be computed for parameters {'Omega_m': 0.599568566639542}
 2023-07-02 10:24:45,318 [prior] Evaluating prior at array([0.59956857])
 2023-07-02 10:24:45,318 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,318 [model] Got input parameters: {'Omega_m': 0.599568566639542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,318 [classy] Got parameters {'Omega_m': 0.599568566639542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,318 [classy] Computing new state
 2023-07-02 10:24:45,318 [classy] Setting parameters: {'Omega_m': 0.599568566639542, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.30367591248512}
 2023-07-02 10:24:45,367 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.85617
 2023-07-02 10:24:45,368 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,369 [model] Posterior to be computed for parameters {'Omega_m': 0.5561954653678962}
 2023-07-02 10:24:45,369 [prior] Evaluating prior at array([0.55619547])
 2023-07-02 10:24:45,369 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,369 [model] Got input parameters: {'Omega_m': 0.5561954653678962, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,369 [classy] Got parameters {'Omega_m': 0.5561954653678962, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,369 [classy] Computing new state
 2023-07-02 10:24:45,369 [classy] Setting parameters: {'Omega_m': 0.5561954653678962, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.18663492667822}
 2023-07-02 10:24:45,419 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,421 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.21238
 2023-07-02 10:24:45,421 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,421 [model] Posterior to be computed for parameters {'Omega_m': 0.7314348829752193}
 2023-07-02 10:24:45,421 [prior] Evaluating prior at array([0.73143488])
 2023-07-02 10:24:45,421 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,421 [model] Got input parameters: {'Omega_m': 0.7314348829752193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,421 [classy] Got parameters {'Omega_m': 0.7314348829752193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,422 [classy] Computing new state
 2023-07-02 10:24:45,422 [classy] Setting parameters: {'Omega_m': 0.7314348829752193, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,468 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.72972836373765}
 2023-07-02 10:24:45,469 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,470 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.9863
 2023-07-02 10:24:45,470 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,471 [model] Posterior to be computed for parameters {'Omega_m': 0.39058575834802817}
 2023-07-02 10:24:45,471 [prior] Evaluating prior at array([0.39058576])
 2023-07-02 10:24:45,471 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,471 [model] Got input parameters: {'Omega_m': 0.39058575834802817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,471 [classy] Got parameters {'Omega_m': 0.39058575834802817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,471 [classy] Computing new state
 2023-07-02 10:24:45,471 [classy] Setting parameters: {'Omega_m': 0.39058575834802817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,519 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.78450988854124}
 2023-07-02 10:24:45,519 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.312298
 2023-07-02 10:24:45,521 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,521 [mcmc] New sample, #359:
   Omega_m:0.4414297
 2023-07-02 10:24:45,521 [model] Posterior to be computed for parameters {'Omega_m': 0.7074844631995114}
 2023-07-02 10:24:45,521 [prior] Evaluating prior at array([0.70748446])
 2023-07-02 10:24:45,522 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,522 [model] Got input parameters: {'Omega_m': 0.7074844631995114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,522 [classy] Got parameters {'Omega_m': 0.7074844631995114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,522 [classy] Computing new state
 2023-07-02 10:24:45,522 [classy] Setting parameters: {'Omega_m': 0.7074844631995114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.99044947367614}
 2023-07-02 10:24:45,570 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,572 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.58602
 2023-07-02 10:24:45,572 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,572 [model] Posterior to be computed for parameters {'Omega_m': 0.44207595533050464}
 2023-07-02 10:24:45,572 [prior] Evaluating prior at array([0.44207596])
 2023-07-02 10:24:45,572 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,572 [model] Got input parameters: {'Omega_m': 0.44207595533050464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,572 [classy] Got parameters {'Omega_m': 0.44207595533050464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,572 [classy] Computing new state
 2023-07-02 10:24:45,572 [classy] Setting parameters: {'Omega_m': 0.44207595533050464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,621 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.02867735407992}
 2023-07-02 10:24:45,621 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,623 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.772247
 2023-07-02 10:24:45,623 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,623 [mcmc] New sample, #360:
   Omega_m:0.3905858
 2023-07-02 10:24:45,623 [mcmc] Learn + convergence test @ 360 samples accepted.
 2023-07-02 10:24:45,624 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:45,630 [mcmc]  - Acceptance rate: 0.432
 2023-07-02 10:24:45,631 [mcmc]  - Condition number = 1
 2023-07-02 10:24:45,631 [mcmc]  - Eigenvalues = array([0.02178049])
 2023-07-02 10:24:45,631 [mcmc]  - Convergence of means: R-1 = 0.021780 after 288 accepted steps
 2023-07-02 10:24:45,631 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:45,631 [mcmc] array([[0.01227921]])
 2023-07-02 10:24:45,642 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:45,642 [model] Posterior to be computed for parameters {'Omega_m': 0.8435970413490674}
 2023-07-02 10:24:45,642 [prior] Evaluating prior at array([0.84359704])
 2023-07-02 10:24:45,642 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,642 [model] Got input parameters: {'Omega_m': 0.8435970413490674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,642 [classy] Got parameters {'Omega_m': 0.8435970413490674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,642 [classy] Computing new state
 2023-07-02 10:24:45,642 [classy] Setting parameters: {'Omega_m': 0.8435970413490674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,691 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.3727185737638}
 2023-07-02 10:24:45,691 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.90193
 2023-07-02 10:24:45,693 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,693 [model] Posterior to be computed for parameters {'Omega_m': 0.4064486755755495}
 2023-07-02 10:24:45,693 [prior] Evaluating prior at array([0.40644868])
 2023-07-02 10:24:45,693 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,693 [model] Got input parameters: {'Omega_m': 0.4064486755755495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,693 [classy] Got parameters {'Omega_m': 0.4064486755755495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,693 [classy] Computing new state
 2023-07-02 10:24:45,693 [classy] Setting parameters: {'Omega_m': 0.4064486755755495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.25818631690277}
 2023-07-02 10:24:45,739 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,742 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.43689
 2023-07-02 10:24:45,742 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,742 [mcmc] New sample, #361:
   Omega_m:0.442076
 2023-07-02 10:24:45,742 [model] Posterior to be computed for parameters {'Omega_m': 0.3542198243687988}
 2023-07-02 10:24:45,742 [prior] Evaluating prior at array([0.35421982])
 2023-07-02 10:24:45,742 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,742 [model] Got input parameters: {'Omega_m': 0.3542198243687988, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,742 [classy] Got parameters {'Omega_m': 0.3542198243687988, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,742 [classy] Computing new state
 2023-07-02 10:24:45,743 [classy] Setting parameters: {'Omega_m': 0.3542198243687988, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,789 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.516392738315}
 2023-07-02 10:24:45,790 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0968603
 2023-07-02 10:24:45,792 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,792 [mcmc] New sample, #362:
   Omega_m:0.4064487
 2023-07-02 10:24:45,793 [model] Posterior to be computed for parameters {'Omega_m': -0.825210572759129}
 2023-07-02 10:24:45,793 [prior] Evaluating prior at array([-0.82521057])
 2023-07-02 10:24:45,793 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:45,793 [model] Posterior to be computed for parameters {'Omega_m': 0.6301092151028064}
 2023-07-02 10:24:45,793 [prior] Evaluating prior at array([0.63010922])
 2023-07-02 10:24:45,793 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,793 [model] Got input parameters: {'Omega_m': 0.6301092151028064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,793 [classy] Got parameters {'Omega_m': 0.6301092151028064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,793 [classy] Computing new state
 2023-07-02 10:24:45,793 [classy] Setting parameters: {'Omega_m': 0.6301092151028064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.4016185920272}
 2023-07-02 10:24:45,840 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,843 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.33023
 2023-07-02 10:24:45,843 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,843 [model] Posterior to be computed for parameters {'Omega_m': 0.36541186440924106}
 2023-07-02 10:24:45,843 [prior] Evaluating prior at array([0.36541186])
 2023-07-02 10:24:45,843 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,843 [model] Got input parameters: {'Omega_m': 0.36541186440924106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,843 [classy] Got parameters {'Omega_m': 0.36541186440924106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,843 [classy] Computing new state
 2023-07-02 10:24:45,843 [classy] Setting parameters: {'Omega_m': 0.36541186440924106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.3312261925746}
 2023-07-02 10:24:45,891 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,894 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.151734
 2023-07-02 10:24:45,894 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,894 [mcmc] New sample, #363:
   Omega_m:0.3542198
 2023-07-02 10:24:45,894 [model] Posterior to be computed for parameters {'Omega_m': 0.31810889303016626}
 2023-07-02 10:24:45,894 [prior] Evaluating prior at array([0.31810889])
 2023-07-02 10:24:45,894 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,894 [model] Got input parameters: {'Omega_m': 0.31810889303016626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,894 [classy] Got parameters {'Omega_m': 0.31810889303016626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,894 [classy] Computing new state
 2023-07-02 10:24:45,894 [classy] Setting parameters: {'Omega_m': 0.31810889303016626, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,942 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.58866582691934}
 2023-07-02 10:24:45,942 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,944 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00211558
 2023-07-02 10:24:45,945 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,945 [mcmc] New sample, #364:
   Omega_m:0.3654119
 2023-07-02 10:24:45,945 [model] Posterior to be computed for parameters {'Omega_m': 0.3858272350607616}
 2023-07-02 10:24:45,945 [prior] Evaluating prior at array([0.38582724])
 2023-07-02 10:24:45,945 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,945 [model] Got input parameters: {'Omega_m': 0.3858272350607616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,945 [classy] Got parameters {'Omega_m': 0.3858272350607616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,945 [classy] Computing new state
 2023-07-02 10:24:45,945 [classy] Setting parameters: {'Omega_m': 0.3858272350607616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:45,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.2538704097351}
 2023-07-02 10:24:45,993 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:45,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.278284
 2023-07-02 10:24:45,995 [model] Computed derived parameters: {}
 2023-07-02 10:24:45,995 [mcmc] New sample, #365:
   Omega_m:0.3181089
 2023-07-02 10:24:45,995 [model] Posterior to be computed for parameters {'Omega_m': 0.23990994328428356}
 2023-07-02 10:24:45,995 [prior] Evaluating prior at array([0.23990994])
 2023-07-02 10:24:45,995 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:45,995 [model] Got input parameters: {'Omega_m': 0.23990994328428356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,995 [classy] Got parameters {'Omega_m': 0.23990994328428356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:45,996 [classy] Computing new state
 2023-07-02 10:24:45,996 [classy] Setting parameters: {'Omega_m': 0.23990994328428356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.01991793320798}
 2023-07-02 10:24:46,044 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,045 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.392574
 2023-07-02 10:24:46,046 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,046 [mcmc] New sample, #366:
   Omega_m:0.3858272
 2023-07-02 10:24:46,046 [model] Posterior to be computed for parameters {'Omega_m': -0.06002103424233951}
 2023-07-02 10:24:46,046 [prior] Evaluating prior at array([-0.06002103])
 2023-07-02 10:24:46,046 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:46,046 [model] Posterior to be computed for parameters {'Omega_m': 0.19074137997623872}
 2023-07-02 10:24:46,046 [prior] Evaluating prior at array([0.19074138])
 2023-07-02 10:24:46,046 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,046 [model] Got input parameters: {'Omega_m': 0.19074137997623872, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,046 [classy] Got parameters {'Omega_m': 0.19074137997623872, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,046 [classy] Computing new state
 2023-07-02 10:24:46,046 [classy] Setting parameters: {'Omega_m': 0.19074137997623872, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,095 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.11446630524884}
 2023-07-02 10:24:46,095 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,097 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.28469
 2023-07-02 10:24:46,097 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,097 [model] Posterior to be computed for parameters {'Omega_m': -0.6661765573925307}
 2023-07-02 10:24:46,097 [prior] Evaluating prior at array([-0.66617656])
 2023-07-02 10:24:46,097 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:46,097 [model] Posterior to be computed for parameters {'Omega_m': -0.42227852613169975}
 2023-07-02 10:24:46,098 [prior] Evaluating prior at array([-0.42227853])
 2023-07-02 10:24:46,098 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:46,098 [model] Posterior to be computed for parameters {'Omega_m': 0.3236637659425725}
 2023-07-02 10:24:46,098 [prior] Evaluating prior at array([0.32366377])
 2023-07-02 10:24:46,098 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,098 [model] Got input parameters: {'Omega_m': 0.3236637659425725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,098 [classy] Got parameters {'Omega_m': 0.3236637659425725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,098 [classy] Computing new state
 2023-07-02 10:24:46,098 [classy] Setting parameters: {'Omega_m': 0.3236637659425725, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9358856363259}
 2023-07-02 10:24:46,146 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00765812
 2023-07-02 10:24:46,148 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,148 [mcmc] New sample, #367:
   Omega_m:0.2399099
 2023-07-02 10:24:46,148 [model] Posterior to be computed for parameters {'Omega_m': -0.053288318087928666}
 2023-07-02 10:24:46,148 [prior] Evaluating prior at array([-0.05328832])
 2023-07-02 10:24:46,148 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:46,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3625688242758681}
 2023-07-02 10:24:46,148 [prior] Evaluating prior at array([0.36256882])
 2023-07-02 10:24:46,148 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,148 [model] Got input parameters: {'Omega_m': 0.3625688242758681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,148 [classy] Got parameters {'Omega_m': 0.3625688242758681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,148 [classy] Computing new state
 2023-07-02 10:24:46,149 [classy] Setting parameters: {'Omega_m': 0.3625688242758681, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.6290574700278}
 2023-07-02 10:24:46,197 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,199 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.13677
 2023-07-02 10:24:46,199 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,199 [mcmc] New sample, #368:
   Omega_m:0.3236638
 2023-07-02 10:24:46,199 [model] Posterior to be computed for parameters {'Omega_m': 0.7279382574665947}
 2023-07-02 10:24:46,200 [prior] Evaluating prior at array([0.72793826])
 2023-07-02 10:24:46,200 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,200 [model] Got input parameters: {'Omega_m': 0.7279382574665947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,200 [classy] Got parameters {'Omega_m': 0.7279382574665947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,200 [classy] Computing new state
 2023-07-02 10:24:46,200 [classy] Setting parameters: {'Omega_m': 0.7279382574665947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.91095653141669}
 2023-07-02 10:24:46,248 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.92761
 2023-07-02 10:24:46,250 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,251 [model] Posterior to be computed for parameters {'Omega_m': 0.5291711558914336}
 2023-07-02 10:24:46,251 [prior] Evaluating prior at array([0.52917116])
 2023-07-02 10:24:46,251 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,251 [model] Got input parameters: {'Omega_m': 0.5291711558914336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,251 [classy] Got parameters {'Omega_m': 0.5291711558914336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,251 [classy] Computing new state
 2023-07-02 10:24:46,251 [classy] Setting parameters: {'Omega_m': 0.5291711558914336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,300 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.10279554865743}
 2023-07-02 10:24:46,300 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,302 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.83308
 2023-07-02 10:24:46,302 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,302 [mcmc] New sample, #369:
   Omega_m:0.3625688
 2023-07-02 10:24:46,302 [model] Posterior to be computed for parameters {'Omega_m': 0.513741759927027}
 2023-07-02 10:24:46,302 [prior] Evaluating prior at array([0.51374176])
 2023-07-02 10:24:46,303 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,303 [model] Got input parameters: {'Omega_m': 0.513741759927027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,303 [classy] Got parameters {'Omega_m': 0.513741759927027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,303 [classy] Computing new state
 2023-07-02 10:24:46,303 [classy] Setting parameters: {'Omega_m': 0.513741759927027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,348 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.24218302279536}
 2023-07-02 10:24:46,348 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,351 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.62553
 2023-07-02 10:24:46,351 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,351 [mcmc] New sample, #370:
   Omega_m:0.5291712
 2023-07-02 10:24:46,351 [model] Posterior to be computed for parameters {'Omega_m': 0.3273789263356756}
 2023-07-02 10:24:46,351 [prior] Evaluating prior at array([0.32737893])
 2023-07-02 10:24:46,351 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,352 [model] Got input parameters: {'Omega_m': 0.3273789263356756, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,352 [classy] Got parameters {'Omega_m': 0.3273789263356756, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,352 [classy] Computing new state
 2023-07-02 10:24:46,352 [classy] Setting parameters: {'Omega_m': 0.3273789263356756, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50485987672872}
 2023-07-02 10:24:46,403 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,406 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0133186
 2023-07-02 10:24:46,406 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,406 [mcmc] New sample, #371:
   Omega_m:0.5137418
 2023-07-02 10:24:46,406 [model] Posterior to be computed for parameters {'Omega_m': 0.46274783822488363}
 2023-07-02 10:24:46,406 [prior] Evaluating prior at array([0.46274784])
 2023-07-02 10:24:46,406 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,406 [model] Got input parameters: {'Omega_m': 0.46274783822488363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,406 [classy] Got parameters {'Omega_m': 0.46274783822488363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,406 [classy] Computing new state
 2023-07-02 10:24:46,407 [classy] Setting parameters: {'Omega_m': 0.46274783822488363, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.26918809551628}
 2023-07-02 10:24:46,456 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,458 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.99684
 2023-07-02 10:24:46,458 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,458 [model] Posterior to be computed for parameters {'Omega_m': 0.7870876928577524}
 2023-07-02 10:24:46,458 [prior] Evaluating prior at array([0.78708769])
 2023-07-02 10:24:46,458 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,458 [model] Got input parameters: {'Omega_m': 0.7870876928577524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,458 [classy] Got parameters {'Omega_m': 0.7870876928577524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,458 [classy] Computing new state
 2023-07-02 10:24:46,458 [classy] Setting parameters: {'Omega_m': 0.7870876928577524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.96634165199276}
 2023-07-02 10:24:46,506 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,508 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.93031
 2023-07-02 10:24:46,508 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,508 [model] Posterior to be computed for parameters {'Omega_m': -0.1134078998319436}
 2023-07-02 10:24:46,508 [prior] Evaluating prior at array([-0.1134079])
 2023-07-02 10:24:46,508 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:46,508 [model] Posterior to be computed for parameters {'Omega_m': 0.29685351775962004}
 2023-07-02 10:24:46,508 [prior] Evaluating prior at array([0.29685352])
 2023-07-02 10:24:46,508 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,508 [model] Got input parameters: {'Omega_m': 0.29685351775962004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,508 [classy] Got parameters {'Omega_m': 0.29685351775962004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,508 [classy] Computing new state
 2023-07-02 10:24:46,508 [classy] Setting parameters: {'Omega_m': 0.29685351775962004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.18375893023773}
 2023-07-02 10:24:46,557 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,559 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0157872
 2023-07-02 10:24:46,559 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,559 [mcmc] New sample, #372:
   Omega_m:0.3273789
 2023-07-02 10:24:46,559 [model] Posterior to be computed for parameters {'Omega_m': 0.19825351859332874}
 2023-07-02 10:24:46,559 [prior] Evaluating prior at array([0.19825352])
 2023-07-02 10:24:46,559 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,559 [model] Got input parameters: {'Omega_m': 0.19825351859332874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,560 [classy] Got parameters {'Omega_m': 0.19825351859332874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,560 [classy] Computing new state
 2023-07-02 10:24:46,560 [classy] Setting parameters: {'Omega_m': 0.19825351859332874, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,607 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.7804993267242}
 2023-07-02 10:24:46,607 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.10386
 2023-07-02 10:24:46,609 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,609 [model] Posterior to be computed for parameters {'Omega_m': 0.49574491218329597}
 2023-07-02 10:24:46,609 [prior] Evaluating prior at array([0.49574491])
 2023-07-02 10:24:46,609 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,609 [model] Got input parameters: {'Omega_m': 0.49574491218329597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,609 [classy] Got parameters {'Omega_m': 0.49574491218329597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,609 [classy] Computing new state
 2023-07-02 10:24:46,609 [classy] Setting parameters: {'Omega_m': 0.49574491218329597, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,656 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.61574886231938}
 2023-07-02 10:24:46,656 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,658 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.39288
 2023-07-02 10:24:46,658 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,658 [model] Posterior to be computed for parameters {'Omega_m': 0.36113974782840286}
 2023-07-02 10:24:46,658 [prior] Evaluating prior at array([0.36113975])
 2023-07-02 10:24:46,659 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,659 [model] Got input parameters: {'Omega_m': 0.36113974782840286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,659 [classy] Got parameters {'Omega_m': 0.36113974782840286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,659 [classy] Computing new state
 2023-07-02 10:24:46,659 [classy] Setting parameters: {'Omega_m': 0.36113974782840286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,706 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.77958037711784}
 2023-07-02 10:24:46,706 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,708 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.129508
 2023-07-02 10:24:46,708 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,708 [mcmc] New sample, #373:
   Omega_m:0.2968535
 2023-07-02 10:24:46,708 [model] Posterior to be computed for parameters {'Omega_m': 0.7078616666284414}
 2023-07-02 10:24:46,708 [prior] Evaluating prior at array([0.70786167])
 2023-07-02 10:24:46,708 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,708 [model] Got input parameters: {'Omega_m': 0.7078616666284414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,709 [classy] Got parameters {'Omega_m': 0.7078616666284414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,709 [classy] Computing new state
 2023-07-02 10:24:46,709 [classy] Setting parameters: {'Omega_m': 0.7078616666284414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.9702379771254}
 2023-07-02 10:24:46,754 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.59229
 2023-07-02 10:24:46,756 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,756 [model] Posterior to be computed for parameters {'Omega_m': 0.44567217453858965}
 2023-07-02 10:24:46,756 [prior] Evaluating prior at array([0.44567217])
 2023-07-02 10:24:46,756 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,756 [model] Got input parameters: {'Omega_m': 0.44567217453858965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,756 [classy] Got parameters {'Omega_m': 0.44567217453858965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,757 [classy] Computing new state
 2023-07-02 10:24:46,757 [classy] Setting parameters: {'Omega_m': 0.44567217453858965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.7168709517539}
 2023-07-02 10:24:46,803 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,805 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.809866
 2023-07-02 10:24:46,805 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,805 [model] Posterior to be computed for parameters {'Omega_m': 0.8070386978968211}
 2023-07-02 10:24:46,805 [prior] Evaluating prior at array([0.8070387])
 2023-07-02 10:24:46,805 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,805 [model] Got input parameters: {'Omega_m': 0.8070386978968211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,805 [classy] Got parameters {'Omega_m': 0.8070386978968211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,805 [classy] Computing new state
 2023-07-02 10:24:46,805 [classy] Setting parameters: {'Omega_m': 0.8070386978968211, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.02770122093526}
 2023-07-02 10:24:46,851 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,853 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.27221
 2023-07-02 10:24:46,853 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,853 [model] Posterior to be computed for parameters {'Omega_m': 0.49356300379523177}
 2023-07-02 10:24:46,853 [prior] Evaluating prior at array([0.493563])
 2023-07-02 10:24:46,853 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,853 [model] Got input parameters: {'Omega_m': 0.49356300379523177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,853 [classy] Got parameters {'Omega_m': 0.49356300379523177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,853 [classy] Computing new state
 2023-07-02 10:24:46,853 [classy] Setting parameters: {'Omega_m': 0.49356300379523177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.78566909774568}
 2023-07-02 10:24:46,900 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.36543
 2023-07-02 10:24:46,902 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,902 [mcmc] New sample, #374:
   Omega_m:0.3611397
 2023-07-02 10:24:46,903 [model] Posterior to be computed for parameters {'Omega_m': 0.3533511950696836}
 2023-07-02 10:24:46,903 [prior] Evaluating prior at array([0.3533512])
 2023-07-02 10:24:46,903 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,903 [model] Got input parameters: {'Omega_m': 0.3533511950696836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,903 [classy] Got parameters {'Omega_m': 0.3533511950696836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,903 [classy] Computing new state
 2023-07-02 10:24:46,903 [classy] Setting parameters: {'Omega_m': 0.3533511950696836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:46,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.60981628767135}
 2023-07-02 10:24:46,950 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:46,952 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0930644
 2023-07-02 10:24:46,952 [model] Computed derived parameters: {}
 2023-07-02 10:24:46,952 [mcmc] New sample, #375:
   Omega_m:0.493563
 2023-07-02 10:24:46,952 [model] Posterior to be computed for parameters {'Omega_m': 0.48853501364072716}
 2023-07-02 10:24:46,952 [prior] Evaluating prior at array([0.48853501])
 2023-07-02 10:24:46,953 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:46,953 [model] Got input parameters: {'Omega_m': 0.48853501364072716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,953 [classy] Got parameters {'Omega_m': 0.48853501364072716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:46,953 [classy] Computing new state
 2023-07-02 10:24:46,953 [classy] Setting parameters: {'Omega_m': 0.48853501364072716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,000 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.18016375046466}
 2023-07-02 10:24:47,001 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.30279
 2023-07-02 10:24:47,003 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,003 [model] Posterior to be computed for parameters {'Omega_m': 0.24802296155161552}
 2023-07-02 10:24:47,003 [prior] Evaluating prior at array([0.24802296])
 2023-07-02 10:24:47,003 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,003 [model] Got input parameters: {'Omega_m': 0.24802296155161552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,003 [classy] Got parameters {'Omega_m': 0.24802296155161552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,003 [classy] Computing new state
 2023-07-02 10:24:47,003 [classy] Setting parameters: {'Omega_m': 0.24802296155161552, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.81409607927193}
 2023-07-02 10:24:47,054 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,056 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.30262
 2023-07-02 10:24:47,056 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,056 [model] Posterior to be computed for parameters {'Omega_m': 0.4685508887790934}
 2023-07-02 10:24:47,056 [prior] Evaluating prior at array([0.46855089])
 2023-07-02 10:24:47,057 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,057 [model] Got input parameters: {'Omega_m': 0.4685508887790934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,057 [classy] Got parameters {'Omega_m': 0.4685508887790934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,057 [classy] Computing new state
 2023-07-02 10:24:47,057 [classy] Setting parameters: {'Omega_m': 0.4685508887790934, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.7891743339365}
 2023-07-02 10:24:47,104 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,106 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.06334
 2023-07-02 10:24:47,106 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,106 [model] Posterior to be computed for parameters {'Omega_m': 0.2900957373277737}
 2023-07-02 10:24:47,106 [prior] Evaluating prior at array([0.29009574])
 2023-07-02 10:24:47,106 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,106 [model] Got input parameters: {'Omega_m': 0.2900957373277737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,106 [classy] Got parameters {'Omega_m': 0.2900957373277737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,106 [classy] Computing new state
 2023-07-02 10:24:47,106 [classy] Setting parameters: {'Omega_m': 0.2900957373277737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.04303273934713}
 2023-07-02 10:24:47,153 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0327393
 2023-07-02 10:24:47,155 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,155 [mcmc] New sample, #376:
   Omega_m:0.3533512
 2023-07-02 10:24:47,155 [model] Posterior to be computed for parameters {'Omega_m': 0.29086613306917863}
 2023-07-02 10:24:47,155 [prior] Evaluating prior at array([0.29086613])
 2023-07-02 10:24:47,155 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,155 [model] Got input parameters: {'Omega_m': 0.29086613306917863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,155 [classy] Got parameters {'Omega_m': 0.29086613306917863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,155 [classy] Computing new state
 2023-07-02 10:24:47,155 [classy] Setting parameters: {'Omega_m': 0.29086613306917863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.94420415465325}
 2023-07-02 10:24:47,202 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,204 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0304781
 2023-07-02 10:24:47,204 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,204 [mcmc] New sample, #377:
   Omega_m:0.2900957
 2023-07-02 10:24:47,204 [model] Posterior to be computed for parameters {'Omega_m': 0.16643799559835912}
 2023-07-02 10:24:47,204 [prior] Evaluating prior at array([0.166438])
 2023-07-02 10:24:47,204 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,204 [model] Got input parameters: {'Omega_m': 0.16643799559835912, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,204 [classy] Got parameters {'Omega_m': 0.16643799559835912, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,204 [classy] Computing new state
 2023-07-02 10:24:47,204 [classy] Setting parameters: {'Omega_m': 0.16643799559835912, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.7140955961042}
 2023-07-02 10:24:47,251 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00712
 2023-07-02 10:24:47,253 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,253 [model] Posterior to be computed for parameters {'Omega_m': 0.019484940426982178}
 2023-07-02 10:24:47,253 [prior] Evaluating prior at array([0.01948494])
 2023-07-02 10:24:47,253 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:47,253 [model] Posterior to be computed for parameters {'Omega_m': 0.29936881835201934}
 2023-07-02 10:24:47,253 [prior] Evaluating prior at array([0.29936882])
 2023-07-02 10:24:47,253 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,253 [model] Got input parameters: {'Omega_m': 0.29936881835201934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,253 [classy] Got parameters {'Omega_m': 0.29936881835201934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,253 [classy] Computing new state
 2023-07-02 10:24:47,253 [classy] Setting parameters: {'Omega_m': 0.29936881835201934, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,300 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8682649386721}
 2023-07-02 10:24:47,300 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,302 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111041
 2023-07-02 10:24:47,302 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,302 [mcmc] New sample, #378:
   Omega_m:0.2908661
 2023-07-02 10:24:47,302 [model] Posterior to be computed for parameters {'Omega_m': 0.10610276849223887}
 2023-07-02 10:24:47,302 [prior] Evaluating prior at array([0.10610277])
 2023-07-02 10:24:47,302 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,302 [model] Got input parameters: {'Omega_m': 0.10610276849223887, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,303 [classy] Got parameters {'Omega_m': 0.10610276849223887, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,303 [classy] Computing new state
 2023-07-02 10:24:47,303 [classy] Setting parameters: {'Omega_m': 0.10610276849223887, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,350 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.53410145110618}
 2023-07-02 10:24:47,350 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,352 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.05448
 2023-07-02 10:24:47,352 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,352 [model] Posterior to be computed for parameters {'Omega_m': -0.04894469503475479}
 2023-07-02 10:24:47,352 [prior] Evaluating prior at array([-0.0489447])
 2023-07-02 10:24:47,352 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:47,352 [model] Posterior to be computed for parameters {'Omega_m': 0.3589213280872786}
 2023-07-02 10:24:47,352 [prior] Evaluating prior at array([0.35892133])
 2023-07-02 10:24:47,352 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,352 [model] Got input parameters: {'Omega_m': 0.3589213280872786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,352 [classy] Got parameters {'Omega_m': 0.3589213280872786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,352 [classy] Computing new state
 2023-07-02 10:24:47,352 [classy] Setting parameters: {'Omega_m': 0.3589213280872786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.01435276346368}
 2023-07-02 10:24:47,399 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.118583
 2023-07-02 10:24:47,401 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,401 [mcmc] New sample, #379:
   Omega_m:0.2993688
 2023-07-02 10:24:47,401 [model] Posterior to be computed for parameters {'Omega_m': 0.23314310403140961}
 2023-07-02 10:24:47,401 [prior] Evaluating prior at array([0.2331431])
 2023-07-02 10:24:47,401 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,401 [model] Got input parameters: {'Omega_m': 0.23314310403140961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,401 [classy] Got parameters {'Omega_m': 0.23314310403140961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,401 [classy] Computing new state
 2023-07-02 10:24:47,401 [classy] Setting parameters: {'Omega_m': 0.23314310403140961, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,447 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.05126272450426}
 2023-07-02 10:24:47,447 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,449 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.478511
 2023-07-02 10:24:47,449 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,449 [mcmc] New sample, #380:
   Omega_m:0.3589213
 2023-07-02 10:24:47,449 [model] Posterior to be computed for parameters {'Omega_m': 0.1594760680290367}
 2023-07-02 10:24:47,449 [prior] Evaluating prior at array([0.15947607])
 2023-07-02 10:24:47,449 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,449 [model] Got input parameters: {'Omega_m': 0.1594760680290367, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,449 [classy] Got parameters {'Omega_m': 0.1594760680290367, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,449 [classy] Computing new state
 2023-07-02 10:24:47,449 [classy] Setting parameters: {'Omega_m': 0.1594760680290367, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.1196155937437}
 2023-07-02 10:24:47,495 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,497 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.25789
 2023-07-02 10:24:47,497 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,497 [model] Posterior to be computed for parameters {'Omega_m': 0.29087528165249904}
 2023-07-02 10:24:47,497 [prior] Evaluating prior at array([0.29087528])
 2023-07-02 10:24:47,497 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,497 [model] Got input parameters: {'Omega_m': 0.29087528165249904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,497 [classy] Got parameters {'Omega_m': 0.29087528165249904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,497 [classy] Computing new state
 2023-07-02 10:24:47,497 [classy] Setting parameters: {'Omega_m': 0.29087528165249904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.94302977693494}
 2023-07-02 10:24:47,544 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0304516
 2023-07-02 10:24:47,546 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,546 [mcmc] New sample, #381:
   Omega_m:0.2331431
 2023-07-02 10:24:47,546 [model] Posterior to be computed for parameters {'Omega_m': 0.3586233326772683}
 2023-07-02 10:24:47,546 [prior] Evaluating prior at array([0.35862333])
 2023-07-02 10:24:47,546 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,546 [model] Got input parameters: {'Omega_m': 0.3586233326772683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,546 [classy] Got parameters {'Omega_m': 0.3586233326772683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,546 [classy] Computing new state
 2023-07-02 10:24:47,546 [classy] Setting parameters: {'Omega_m': 0.3586233326772683, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,593 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.04599362070954}
 2023-07-02 10:24:47,593 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,595 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.117148
 2023-07-02 10:24:47,595 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,595 [mcmc] New sample, #382:
   Omega_m:0.2908753
 2023-07-02 10:24:47,595 [model] Posterior to be computed for parameters {'Omega_m': 0.4357743522455158}
 2023-07-02 10:24:47,595 [prior] Evaluating prior at array([0.43577435])
 2023-07-02 10:24:47,595 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,595 [model] Got input parameters: {'Omega_m': 0.4357743522455158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,596 [classy] Got parameters {'Omega_m': 0.4357743522455158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,596 [classy] Computing new state
 2023-07-02 10:24:47,596 [classy] Setting parameters: {'Omega_m': 0.4357743522455158, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.58111385476712}
 2023-07-02 10:24:47,643 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.707876
 2023-07-02 10:24:47,645 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,645 [model] Posterior to be computed for parameters {'Omega_m': 0.18445325114990346}
 2023-07-02 10:24:47,645 [prior] Evaluating prior at array([0.18445325])
 2023-07-02 10:24:47,645 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,645 [model] Got input parameters: {'Omega_m': 0.18445325114990346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,645 [classy] Got parameters {'Omega_m': 0.18445325114990346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,645 [classy] Computing new state
 2023-07-02 10:24:47,645 [classy] Setting parameters: {'Omega_m': 0.18445325114990346, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.26151766317363}
 2023-07-02 10:24:47,692 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,694 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45058
 2023-07-02 10:24:47,694 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,694 [mcmc] New sample, #383:
   Omega_m:0.3586233
 2023-07-02 10:24:47,694 [model] Posterior to be computed for parameters {'Omega_m': 0.10190578484306648}
 2023-07-02 10:24:47,694 [prior] Evaluating prior at array([0.10190578])
 2023-07-02 10:24:47,694 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,694 [model] Got input parameters: {'Omega_m': 0.10190578484306648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,694 [classy] Got parameters {'Omega_m': 0.10190578484306648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,694 [classy] Computing new state
 2023-07-02 10:24:47,694 [classy] Setting parameters: {'Omega_m': 0.10190578484306648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 184.65866008830082}
 2023-07-02 10:24:47,741 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,743 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.35742
 2023-07-02 10:24:47,743 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,743 [model] Posterior to be computed for parameters {'Omega_m': -0.014892118732253323}
 2023-07-02 10:24:47,743 [prior] Evaluating prior at array([-0.01489212])
 2023-07-02 10:24:47,744 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:47,744 [model] Posterior to be computed for parameters {'Omega_m': 0.3027699542997853}
 2023-07-02 10:24:47,744 [prior] Evaluating prior at array([0.30276995])
 2023-07-02 10:24:47,744 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,744 [model] Got input parameters: {'Omega_m': 0.3027699542997853, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,744 [classy] Got parameters {'Omega_m': 0.3027699542997853, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,744 [classy] Computing new state
 2023-07-02 10:24:47,744 [classy] Setting parameters: {'Omega_m': 0.3027699542997853, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.44536602041893}
 2023-07-02 10:24:47,791 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,793 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0061316
 2023-07-02 10:24:47,793 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,793 [mcmc] New sample, #384:
   Omega_m:0.1844533
 2023-07-02 10:24:47,793 [model] Posterior to be computed for parameters {'Omega_m': 0.5221497456283342}
 2023-07-02 10:24:47,793 [prior] Evaluating prior at array([0.52214975])
 2023-07-02 10:24:47,793 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,793 [model] Got input parameters: {'Omega_m': 0.5221497456283342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,793 [classy] Got parameters {'Omega_m': 0.5221497456283342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,793 [classy] Computing new state
 2023-07-02 10:24:47,793 [classy] Setting parameters: {'Omega_m': 0.5221497456283342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.61706684688846}
 2023-07-02 10:24:47,841 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.73775
 2023-07-02 10:24:47,842 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,843 [model] Posterior to be computed for parameters {'Omega_m': 0.27016429433800965}
 2023-07-02 10:24:47,843 [prior] Evaluating prior at array([0.27016429])
 2023-07-02 10:24:47,843 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,843 [model] Got input parameters: {'Omega_m': 0.27016429433800965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,843 [classy] Got parameters {'Omega_m': 0.27016429433800965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,843 [classy] Computing new state
 2023-07-02 10:24:47,843 [classy] Setting parameters: {'Omega_m': 0.27016429433800965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,889 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.6819830276757}
 2023-07-02 10:24:47,889 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,891 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.122776
 2023-07-02 10:24:47,891 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,891 [mcmc] New sample, #385:
   Omega_m:0.30277
 2023-07-02 10:24:47,891 [model] Posterior to be computed for parameters {'Omega_m': -0.047168943017101006}
 2023-07-02 10:24:47,891 [prior] Evaluating prior at array([-0.04716894])
 2023-07-02 10:24:47,891 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:47,892 [model] Posterior to be computed for parameters {'Omega_m': 0.5418758249274245}
 2023-07-02 10:24:47,892 [prior] Evaluating prior at array([0.54187582])
 2023-07-02 10:24:47,892 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,892 [model] Got input parameters: {'Omega_m': 0.5418758249274245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,892 [classy] Got parameters {'Omega_m': 0.5418758249274245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,892 [classy] Computing new state
 2023-07-02 10:24:47,892 [classy] Setting parameters: {'Omega_m': 0.5418758249274245, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,940 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.18978289073908}
 2023-07-02 10:24:47,940 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00904
 2023-07-02 10:24:47,941 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,942 [model] Posterior to be computed for parameters {'Omega_m': 0.38469457092988335}
 2023-07-02 10:24:47,942 [prior] Evaluating prior at array([0.38469457])
 2023-07-02 10:24:47,942 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,942 [model] Got input parameters: {'Omega_m': 0.38469457092988335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,942 [classy] Got parameters {'Omega_m': 0.38469457092988335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,942 [classy] Computing new state
 2023-07-02 10:24:47,942 [classy] Setting parameters: {'Omega_m': 0.38469457092988335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:47,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.36639399621245}
 2023-07-02 10:24:47,989 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:47,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.270429
 2023-07-02 10:24:47,990 [model] Computed derived parameters: {}
 2023-07-02 10:24:47,990 [mcmc] New sample, #386:
   Omega_m:0.2701643
 2023-07-02 10:24:47,990 [model] Posterior to be computed for parameters {'Omega_m': 0.6330271362405097}
 2023-07-02 10:24:47,991 [prior] Evaluating prior at array([0.63302714])
 2023-07-02 10:24:47,991 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:47,991 [model] Got input parameters: {'Omega_m': 0.6330271362405097, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,991 [classy] Got parameters {'Omega_m': 0.6330271362405097, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:47,991 [classy] Computing new state
 2023-07-02 10:24:47,991 [classy] Setting parameters: {'Omega_m': 0.6330271362405097, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.22501072059242}
 2023-07-02 10:24:48,038 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.37627
 2023-07-02 10:24:48,039 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,039 [model] Posterior to be computed for parameters {'Omega_m': 0.4557561577607229}
 2023-07-02 10:24:48,039 [prior] Evaluating prior at array([0.45575616])
 2023-07-02 10:24:48,040 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,040 [model] Got input parameters: {'Omega_m': 0.4557561577607229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,040 [classy] Got parameters {'Omega_m': 0.4557561577607229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,040 [classy] Computing new state
 2023-07-02 10:24:48,040 [classy] Setting parameters: {'Omega_m': 0.4557561577607229, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.85547616605194}
 2023-07-02 10:24:48,087 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.918672
 2023-07-02 10:24:48,089 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,089 [mcmc] New sample, #387:
   Omega_m:0.3846946
 2023-07-02 10:24:48,089 [model] Posterior to be computed for parameters {'Omega_m': 0.5469857827901178}
 2023-07-02 10:24:48,089 [prior] Evaluating prior at array([0.54698578])
 2023-07-02 10:24:48,089 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,089 [model] Got input parameters: {'Omega_m': 0.5469857827901178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,089 [classy] Got parameters {'Omega_m': 0.5469857827901178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,089 [classy] Computing new state
 2023-07-02 10:24:48,089 [classy] Setting parameters: {'Omega_m': 0.5469857827901178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.82869805368978}
 2023-07-02 10:24:48,137 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.08103
 2023-07-02 10:24:48,139 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,139 [model] Posterior to be computed for parameters {'Omega_m': 0.7040085374841394}
 2023-07-02 10:24:48,139 [prior] Evaluating prior at array([0.70400854])
 2023-07-02 10:24:48,139 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,139 [model] Got input parameters: {'Omega_m': 0.7040085374841394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,139 [classy] Got parameters {'Omega_m': 0.7040085374841394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,139 [classy] Computing new state
 2023-07-02 10:24:48,139 [classy] Setting parameters: {'Omega_m': 0.7040085374841394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,185 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.1772644949938}
 2023-07-02 10:24:48,185 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.52829
 2023-07-02 10:24:48,188 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,188 [model] Posterior to be computed for parameters {'Omega_m': 0.9312133826516412}
 2023-07-02 10:24:48,188 [prior] Evaluating prior at array([0.93121338])
 2023-07-02 10:24:48,188 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,188 [model] Got input parameters: {'Omega_m': 0.9312133826516412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,188 [classy] Got parameters {'Omega_m': 0.9312133826516412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,188 [classy] Computing new state
 2023-07-02 10:24:48,188 [classy] Setting parameters: {'Omega_m': 0.9312133826516412, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 105.71305946488376}
 2023-07-02 10:24:48,234 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.41957
 2023-07-02 10:24:48,237 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,237 [model] Posterior to be computed for parameters {'Omega_m': 0.6496109474993732}
 2023-07-02 10:24:48,237 [prior] Evaluating prior at array([0.64961095])
 2023-07-02 10:24:48,237 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,238 [model] Got input parameters: {'Omega_m': 0.6496109474993732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,238 [classy] Got parameters {'Omega_m': 0.6496109474993732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,238 [classy] Computing new state
 2023-07-02 10:24:48,238 [classy] Setting parameters: {'Omega_m': 0.6496109474993732, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.23735929186631}
 2023-07-02 10:24:48,284 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.64019
 2023-07-02 10:24:48,287 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,287 [model] Posterior to be computed for parameters {'Omega_m': 0.5467948292106004}
 2023-07-02 10:24:48,287 [prior] Evaluating prior at array([0.54679483])
 2023-07-02 10:24:48,287 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,287 [model] Got input parameters: {'Omega_m': 0.5467948292106004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,287 [classy] Got parameters {'Omega_m': 0.5467948292106004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,287 [classy] Computing new state
 2023-07-02 10:24:48,287 [classy] Setting parameters: {'Omega_m': 0.5467948292106004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.84212936529887}
 2023-07-02 10:24:48,334 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,337 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.07832
 2023-07-02 10:24:48,337 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,337 [model] Posterior to be computed for parameters {'Omega_m': 0.5310523264166135}
 2023-07-02 10:24:48,337 [prior] Evaluating prior at array([0.53105233])
 2023-07-02 10:24:48,337 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,337 [model] Got input parameters: {'Omega_m': 0.5310523264166135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,337 [classy] Got parameters {'Omega_m': 0.5310523264166135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,337 [classy] Computing new state
 2023-07-02 10:24:48,337 [classy] Setting parameters: {'Omega_m': 0.5310523264166135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.96620851441739}
 2023-07-02 10:24:48,384 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.85885
 2023-07-02 10:24:48,387 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,387 [mcmc] New sample, #388:
   Omega_m:0.4557562
 2023-07-02 10:24:48,387 [model] Posterior to be computed for parameters {'Omega_m': 0.7031421232719388}
 2023-07-02 10:24:48,387 [prior] Evaluating prior at array([0.70314212])
 2023-07-02 10:24:48,387 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,387 [model] Got input parameters: {'Omega_m': 0.7031421232719388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,388 [classy] Got parameters {'Omega_m': 0.7031421232719388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,388 [classy] Computing new state
 2023-07-02 10:24:48,388 [classy] Setting parameters: {'Omega_m': 0.7031421232719388, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.22398792518273}
 2023-07-02 10:24:48,433 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.51392
 2023-07-02 10:24:48,436 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,436 [model] Posterior to be computed for parameters {'Omega_m': -0.5380137777268591}
 2023-07-02 10:24:48,436 [prior] Evaluating prior at array([-0.53801378])
 2023-07-02 10:24:48,436 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:48,437 [model] Posterior to be computed for parameters {'Omega_m': 0.4783950117711401}
 2023-07-02 10:24:48,437 [prior] Evaluating prior at array([0.47839501])
 2023-07-02 10:24:48,437 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,437 [model] Got input parameters: {'Omega_m': 0.4783950117711401, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,437 [classy] Got parameters {'Omega_m': 0.4783950117711401, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,437 [classy] Computing new state
 2023-07-02 10:24:48,437 [classy] Setting parameters: {'Omega_m': 0.4783950117711401, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.98820605751007}
 2023-07-02 10:24:48,484 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,487 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.17934
 2023-07-02 10:24:48,487 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,487 [mcmc] New sample, #389:
   Omega_m:0.5310523
 2023-07-02 10:24:48,487 [model] Posterior to be computed for parameters {'Omega_m': 0.7454899986882226}
 2023-07-02 10:24:48,487 [prior] Evaluating prior at array([0.74549])
 2023-07-02 10:24:48,487 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,487 [model] Got input parameters: {'Omega_m': 0.7454899986882226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,487 [classy] Got parameters {'Omega_m': 0.7454899986882226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,487 [classy] Computing new state
 2023-07-02 10:24:48,487 [classy] Setting parameters: {'Omega_m': 0.7454899986882226, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,534 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.01062253454151}
 2023-07-02 10:24:48,534 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,537 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.22308
 2023-07-02 10:24:48,537 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,537 [model] Posterior to be computed for parameters {'Omega_m': 1.081436441863225}
 2023-07-02 10:24:48,537 [prior] Evaluating prior at array([1.08143644])
 2023-07-02 10:24:48,537 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:48,537 [model] Posterior to be computed for parameters {'Omega_m': 0.696663626285269}
 2023-07-02 10:24:48,537 [prior] Evaluating prior at array([0.69666363])
 2023-07-02 10:24:48,537 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,537 [model] Got input parameters: {'Omega_m': 0.696663626285269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,537 [classy] Got parameters {'Omega_m': 0.696663626285269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,537 [classy] Computing new state
 2023-07-02 10:24:48,537 [classy] Setting parameters: {'Omega_m': 0.696663626285269, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.57531985859782}
 2023-07-02 10:24:48,584 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,587 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.40665
 2023-07-02 10:24:48,587 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,587 [model] Posterior to be computed for parameters {'Omega_m': 0.27887498202671995}
 2023-07-02 10:24:48,587 [prior] Evaluating prior at array([0.27887498])
 2023-07-02 10:24:48,587 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,587 [model] Got input parameters: {'Omega_m': 0.27887498202671995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,587 [classy] Got parameters {'Omega_m': 0.27887498202671995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,587 [classy] Computing new state
 2023-07-02 10:24:48,587 [classy] Setting parameters: {'Omega_m': 0.27887498202671995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,634 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.50883676425246}
 2023-07-02 10:24:48,634 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,637 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0757235
 2023-07-02 10:24:48,637 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,637 [mcmc] New sample, #390:
   Omega_m:0.478395
 2023-07-02 10:24:48,637 [model] Posterior to be computed for parameters {'Omega_m': 0.2941860937882571}
 2023-07-02 10:24:48,637 [prior] Evaluating prior at array([0.29418609])
 2023-07-02 10:24:48,637 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,637 [model] Got input parameters: {'Omega_m': 0.2941860937882571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,637 [classy] Got parameters {'Omega_m': 0.2941860937882571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,637 [classy] Computing new state
 2023-07-02 10:24:48,637 [classy] Setting parameters: {'Omega_m': 0.2941860937882571, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.52088401724643}
 2023-07-02 10:24:48,684 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0217076
 2023-07-02 10:24:48,687 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,687 [mcmc] New sample, #391:
   Omega_m:0.278875
 2023-07-02 10:24:48,687 [model] Posterior to be computed for parameters {'Omega_m': 0.36798854525088553}
 2023-07-02 10:24:48,687 [prior] Evaluating prior at array([0.36798855])
 2023-07-02 10:24:48,687 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,687 [model] Got input parameters: {'Omega_m': 0.36798854525088553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,687 [classy] Got parameters {'Omega_m': 0.36798854525088553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,687 [classy] Computing new state
 2023-07-02 10:24:48,687 [classy] Setting parameters: {'Omega_m': 0.36798854525088553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.06314619278507}
 2023-07-02 10:24:48,734 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,737 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.165882
 2023-07-02 10:24:48,737 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,737 [model] Posterior to be computed for parameters {'Omega_m': 0.4545153353113559}
 2023-07-02 10:24:48,737 [prior] Evaluating prior at array([0.45451534])
 2023-07-02 10:24:48,737 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,737 [model] Got input parameters: {'Omega_m': 0.4545153353113559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,737 [classy] Got parameters {'Omega_m': 0.4545153353113559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,737 [classy] Computing new state
 2023-07-02 10:24:48,737 [classy] Setting parameters: {'Omega_m': 0.4545153353113559, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,783 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.96045809368576}
 2023-07-02 10:24:48,783 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,786 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.905027
 2023-07-02 10:24:48,786 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,787 [model] Posterior to be computed for parameters {'Omega_m': 0.2611661950495352}
 2023-07-02 10:24:48,787 [prior] Evaluating prior at array([0.2611662])
 2023-07-02 10:24:48,787 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,787 [model] Got input parameters: {'Omega_m': 0.2611661950495352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,787 [classy] Got parameters {'Omega_m': 0.2611661950495352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,787 [classy] Computing new state
 2023-07-02 10:24:48,787 [classy] Setting parameters: {'Omega_m': 0.2611661950495352, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.92798583384817}
 2023-07-02 10:24:48,833 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,836 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.184935
 2023-07-02 10:24:48,836 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,836 [mcmc] New sample, #392:
   Omega_m:0.2941861
 2023-07-02 10:24:48,837 [model] Posterior to be computed for parameters {'Omega_m': 0.32728529125526973}
 2023-07-02 10:24:48,837 [prior] Evaluating prior at array([0.32728529])
 2023-07-02 10:24:48,837 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,837 [model] Got input parameters: {'Omega_m': 0.32728529125526973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,837 [classy] Got parameters {'Omega_m': 0.32728529125526973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,837 [classy] Computing new state
 2023-07-02 10:24:48,837 [classy] Setting parameters: {'Omega_m': 0.32728529125526973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,885 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.51566818217103}
 2023-07-02 10:24:48,886 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,888 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131572
 2023-07-02 10:24:48,888 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,888 [mcmc] New sample, #393:
   Omega_m:0.2611662
 2023-07-02 10:24:48,888 [model] Posterior to be computed for parameters {'Omega_m': 0.7312041061605647}
 2023-07-02 10:24:48,888 [prior] Evaluating prior at array([0.73120411])
 2023-07-02 10:24:48,888 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,888 [model] Got input parameters: {'Omega_m': 0.7312041061605647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,889 [classy] Got parameters {'Omega_m': 0.7312041061605647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,889 [classy] Computing new state
 2023-07-02 10:24:48,889 [classy] Setting parameters: {'Omega_m': 0.7312041061605647, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.74165994241817}
 2023-07-02 10:24:48,936 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,938 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.98242
 2023-07-02 10:24:48,938 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,938 [model] Posterior to be computed for parameters {'Omega_m': -0.044729229513257696}
 2023-07-02 10:24:48,938 [prior] Evaluating prior at array([-0.04472923])
 2023-07-02 10:24:48,938 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:48,938 [model] Posterior to be computed for parameters {'Omega_m': 0.24009070711674252}
 2023-07-02 10:24:48,938 [prior] Evaluating prior at array([0.24009071])
 2023-07-02 10:24:48,938 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,939 [model] Got input parameters: {'Omega_m': 0.24009070711674252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,939 [classy] Got parameters {'Omega_m': 0.24009070711674252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,939 [classy] Computing new state
 2023-07-02 10:24:48,939 [classy] Setting parameters: {'Omega_m': 0.24009070711674252, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:48,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.99268791526384}
 2023-07-02 10:24:48,989 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:48,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.390416
 2023-07-02 10:24:48,991 [model] Computed derived parameters: {}
 2023-07-02 10:24:48,991 [mcmc] New sample, #394:
   Omega_m:0.3272853
 2023-07-02 10:24:48,991 [model] Posterior to be computed for parameters {'Omega_m': 0.6793341865097531}
 2023-07-02 10:24:48,991 [prior] Evaluating prior at array([0.67933419])
 2023-07-02 10:24:48,991 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:48,991 [model] Got input parameters: {'Omega_m': 0.6793341865097531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,991 [classy] Got parameters {'Omega_m': 0.6793341865097531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:48,991 [classy] Computing new state
 2023-07-02 10:24:48,991 [classy] Setting parameters: {'Omega_m': 0.6793341865097531, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.53266867246151}
 2023-07-02 10:24:49,037 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.12165
 2023-07-02 10:24:49,039 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,039 [model] Posterior to be computed for parameters {'Omega_m': -0.027327308202302003}
 2023-07-02 10:24:49,039 [prior] Evaluating prior at array([-0.02732731])
 2023-07-02 10:24:49,039 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:49,039 [model] Posterior to be computed for parameters {'Omega_m': 0.0330945783975482}
 2023-07-02 10:24:49,039 [prior] Evaluating prior at array([0.03309458])
 2023-07-02 10:24:49,040 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:49,040 [model] Posterior to be computed for parameters {'Omega_m': 0.5650737732058642}
 2023-07-02 10:24:49,040 [prior] Evaluating prior at array([0.56507377])
 2023-07-02 10:24:49,040 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,040 [model] Got input parameters: {'Omega_m': 0.5650737732058642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,040 [classy] Got parameters {'Omega_m': 0.5650737732058642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,040 [classy] Computing new state
 2023-07-02 10:24:49,040 [classy] Setting parameters: {'Omega_m': 0.5650737732058642, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.57792773550864}
 2023-07-02 10:24:49,087 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,088 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.34094
 2023-07-02 10:24:49,089 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,089 [mcmc] New sample, #395:
   Omega_m:0.2400907
 2023-07-02 10:24:49,089 [model] Posterior to be computed for parameters {'Omega_m': 0.46744491292460083}
 2023-07-02 10:24:49,089 [prior] Evaluating prior at array([0.46744491])
 2023-07-02 10:24:49,089 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,089 [model] Got input parameters: {'Omega_m': 0.46744491292460083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,089 [classy] Got parameters {'Omega_m': 0.46744491292460083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,089 [classy] Computing new state
 2023-07-02 10:24:49,089 [classy] Setting parameters: {'Omega_m': 0.46744491292460083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8802048494339}
 2023-07-02 10:24:49,137 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05055
 2023-07-02 10:24:49,139 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,139 [mcmc] New sample, #396:
   Omega_m:0.5650738
 2023-07-02 10:24:49,139 [model] Posterior to be computed for parameters {'Omega_m': 0.5846058438915025}
 2023-07-02 10:24:49,139 [prior] Evaluating prior at array([0.58460584])
 2023-07-02 10:24:49,139 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,139 [model] Got input parameters: {'Omega_m': 0.5846058438915025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,139 [classy] Got parameters {'Omega_m': 0.5846058438915025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,139 [classy] Computing new state
 2023-07-02 10:24:49,139 [classy] Setting parameters: {'Omega_m': 0.5846058438915025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.27297936945887}
 2023-07-02 10:24:49,187 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62978
 2023-07-02 10:24:49,188 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,189 [model] Posterior to be computed for parameters {'Omega_m': 0.21738675539582347}
 2023-07-02 10:24:49,189 [prior] Evaluating prior at array([0.21738676])
 2023-07-02 10:24:49,189 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,189 [model] Got input parameters: {'Omega_m': 0.21738675539582347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,189 [classy] Got parameters {'Omega_m': 0.21738675539582347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,189 [classy] Computing new state
 2023-07-02 10:24:49,189 [classy] Setting parameters: {'Omega_m': 0.21738675539582347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.54914640346664}
 2023-07-02 10:24:49,234 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,236 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.720619
 2023-07-02 10:24:49,236 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,236 [mcmc] New sample, #397:
   Omega_m:0.4674449
 2023-07-02 10:24:49,236 [model] Posterior to be computed for parameters {'Omega_m': 0.332379591583703}
 2023-07-02 10:24:49,236 [prior] Evaluating prior at array([0.33237959])
 2023-07-02 10:24:49,236 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,236 [model] Got input parameters: {'Omega_m': 0.332379591583703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,236 [classy] Got parameters {'Omega_m': 0.332379591583703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,236 [classy] Computing new state
 2023-07-02 10:24:49,236 [classy] Setting parameters: {'Omega_m': 0.332379591583703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.93161587286653}
 2023-07-02 10:24:49,284 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.023324
 2023-07-02 10:24:49,287 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,287 [mcmc] New sample, #398:
   Omega_m:0.2173868
 2023-07-02 10:24:49,287 [model] Posterior to be computed for parameters {'Omega_m': 0.5126746121058726}
 2023-07-02 10:24:49,287 [prior] Evaluating prior at array([0.51267461])
 2023-07-02 10:24:49,287 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,287 [model] Got input parameters: {'Omega_m': 0.5126746121058726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,287 [classy] Got parameters {'Omega_m': 0.5126746121058726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,287 [classy] Computing new state
 2023-07-02 10:24:49,287 [classy] Setting parameters: {'Omega_m': 0.5126746121058726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.32226001409953}
 2023-07-02 10:24:49,334 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,336 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.61144
 2023-07-02 10:24:49,336 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,336 [model] Posterior to be computed for parameters {'Omega_m': 0.46515782750976054}
 2023-07-02 10:24:49,336 [prior] Evaluating prior at array([0.46515783])
 2023-07-02 10:24:49,337 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,337 [model] Got input parameters: {'Omega_m': 0.46515782750976054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,337 [classy] Got parameters {'Omega_m': 0.46515782750976054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,337 [classy] Computing new state
 2023-07-02 10:24:49,337 [classy] Setting parameters: {'Omega_m': 0.46515782750976054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.0691208440315}
 2023-07-02 10:24:49,384 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,385 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.02428
 2023-07-02 10:24:49,385 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,386 [mcmc] New sample, #399:
   Omega_m:0.3323796
 2023-07-02 10:24:49,386 [model] Posterior to be computed for parameters {'Omega_m': 0.8646800805279174}
 2023-07-02 10:24:49,386 [prior] Evaluating prior at array([0.86468008])
 2023-07-02 10:24:49,386 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,386 [model] Got input parameters: {'Omega_m': 0.8646800805279174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,386 [classy] Got parameters {'Omega_m': 0.8646800805279174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,386 [classy] Computing new state
 2023-07-02 10:24:49,386 [classy] Setting parameters: {'Omega_m': 0.8646800805279174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.45427406585448}
 2023-07-02 10:24:49,432 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.26642
 2023-07-02 10:24:49,434 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,434 [model] Posterior to be computed for parameters {'Omega_m': 0.4616593268998967}
 2023-07-02 10:24:49,434 [prior] Evaluating prior at array([0.46165933])
 2023-07-02 10:24:49,434 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,434 [model] Got input parameters: {'Omega_m': 0.4616593268998967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,435 [classy] Got parameters {'Omega_m': 0.4616593268998967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,435 [classy] Computing new state
 2023-07-02 10:24:49,435 [classy] Setting parameters: {'Omega_m': 0.4616593268998967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.35988810911462}
 2023-07-02 10:24:49,481 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.984528
 2023-07-02 10:24:49,483 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,483 [mcmc] New sample, #400:
   Omega_m:0.4651578
 2023-07-02 10:24:49,483 [mcmc] Learn + convergence test @ 400 samples accepted.
 2023-07-02 10:24:49,483 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:49,488 [mcmc]  - Acceptance rate: 0.427
 2023-07-02 10:24:49,489 [mcmc]  - Condition number = 1
 2023-07-02 10:24:49,489 [mcmc]  - Eigenvalues = array([0.03276477])
 2023-07-02 10:24:49,489 [mcmc]  - Convergence of means: R-1 = 0.032765 after 320 accepted steps
 2023-07-02 10:24:49,489 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:49,489 [mcmc] array([[0.01200069]])
 2023-07-02 10:24:49,499 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:49,499 [model] Posterior to be computed for parameters {'Omega_m': 0.32676862470983375}
 2023-07-02 10:24:49,499 [prior] Evaluating prior at array([0.32676862])
 2023-07-02 10:24:49,499 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,500 [model] Got input parameters: {'Omega_m': 0.32676862470983375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,500 [classy] Got parameters {'Omega_m': 0.32676862470983375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,500 [classy] Computing new state
 2023-07-02 10:24:49,500 [classy] Setting parameters: {'Omega_m': 0.32676862470983375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57536458753657}
 2023-07-02 10:24:49,546 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,549 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0122835
 2023-07-02 10:24:49,549 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,549 [mcmc] New sample, #401:
   Omega_m:0.4616593
 2023-07-02 10:24:49,549 [model] Posterior to be computed for parameters {'Omega_m': 0.3427794086215481}
 2023-07-02 10:24:49,549 [prior] Evaluating prior at array([0.34277941])
 2023-07-02 10:24:49,549 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,549 [model] Got input parameters: {'Omega_m': 0.3427794086215481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,549 [classy] Got parameters {'Omega_m': 0.3427794086215481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,549 [classy] Computing new state
 2023-07-02 10:24:49,549 [classy] Setting parameters: {'Omega_m': 0.3427794086215481, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.76402837295277}
 2023-07-02 10:24:49,596 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,598 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0525071
 2023-07-02 10:24:49,598 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,599 [model] Posterior to be computed for parameters {'Omega_m': 0.10512836904135917}
 2023-07-02 10:24:49,599 [prior] Evaluating prior at array([0.10512837])
 2023-07-02 10:24:49,599 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,599 [model] Got input parameters: {'Omega_m': 0.10512836904135917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,599 [classy] Got parameters {'Omega_m': 0.10512836904135917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,599 [classy] Computing new state
 2023-07-02 10:24:49,599 [classy] Setting parameters: {'Omega_m': 0.10512836904135917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,649 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.79292737264674}
 2023-07-02 10:24:49,649 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.1235
 2023-07-02 10:24:49,652 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,652 [model] Posterior to be computed for parameters {'Omega_m': 0.5317220814329515}
 2023-07-02 10:24:49,652 [prior] Evaluating prior at array([0.53172208])
 2023-07-02 10:24:49,652 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,652 [model] Got input parameters: {'Omega_m': 0.5317220814329515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,652 [classy] Got parameters {'Omega_m': 0.5317220814329515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,652 [classy] Computing new state
 2023-07-02 10:24:49,652 [classy] Setting parameters: {'Omega_m': 0.5317220814329515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.9176976149968}
 2023-07-02 10:24:49,704 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.86806
 2023-07-02 10:24:49,706 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,706 [model] Posterior to be computed for parameters {'Omega_m': 0.19353301860060468}
 2023-07-02 10:24:49,706 [prior] Evaluating prior at array([0.19353302])
 2023-07-02 10:24:49,706 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,706 [model] Got input parameters: {'Omega_m': 0.19353301860060468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,706 [classy] Got parameters {'Omega_m': 0.19353301860060468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,706 [classy] Computing new state
 2023-07-02 10:24:49,706 [classy] Setting parameters: {'Omega_m': 0.19353301860060468, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,759 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.61419919364698}
 2023-07-02 10:24:49,759 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,761 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.21534
 2023-07-02 10:24:49,761 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,761 [model] Posterior to be computed for parameters {'Omega_m': 0.3430779851713183}
 2023-07-02 10:24:49,761 [prior] Evaluating prior at array([0.34307799])
 2023-07-02 10:24:49,761 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,761 [model] Got input parameters: {'Omega_m': 0.3430779851713183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,761 [classy] Got parameters {'Omega_m': 0.3430779851713183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,761 [classy] Computing new state
 2023-07-02 10:24:49,761 [classy] Setting parameters: {'Omega_m': 0.3430779851713183, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.7309806700128}
 2023-07-02 10:24:49,809 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0535061
 2023-07-02 10:24:49,811 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,811 [mcmc] New sample, #402:
   Omega_m:0.3267686
 2023-07-02 10:24:49,811 [model] Posterior to be computed for parameters {'Omega_m': 0.5899227145380558}
 2023-07-02 10:24:49,811 [prior] Evaluating prior at array([0.58992271])
 2023-07-02 10:24:49,811 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,811 [model] Got input parameters: {'Omega_m': 0.5899227145380558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,811 [classy] Got parameters {'Omega_m': 0.5899227145380558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,811 [classy] Computing new state
 2023-07-02 10:24:49,811 [classy] Setting parameters: {'Omega_m': 0.5899227145380558, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.92561510823374}
 2023-07-02 10:24:49,858 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.70974
 2023-07-02 10:24:49,860 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,860 [model] Posterior to be computed for parameters {'Omega_m': 0.48855354045875765}
 2023-07-02 10:24:49,860 [prior] Evaluating prior at array([0.48855354])
 2023-07-02 10:24:49,860 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,860 [model] Got input parameters: {'Omega_m': 0.48855354045875765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,860 [classy] Got parameters {'Omega_m': 0.48855354045875765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,860 [classy] Computing new state
 2023-07-02 10:24:49,860 [classy] Setting parameters: {'Omega_m': 0.48855354045875765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,907 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.1787013667199}
 2023-07-02 10:24:49,907 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,909 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.30302
 2023-07-02 10:24:49,909 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,909 [model] Posterior to be computed for parameters {'Omega_m': 0.34425707421128554}
 2023-07-02 10:24:49,909 [prior] Evaluating prior at array([0.34425707])
 2023-07-02 10:24:49,909 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,909 [model] Got input parameters: {'Omega_m': 0.34425707421128554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,910 [classy] Got parameters {'Omega_m': 0.34425707421128554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,910 [classy] Computing new state
 2023-07-02 10:24:49,910 [classy] Setting parameters: {'Omega_m': 0.34425707421128554, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:49,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.60074091632578}
 2023-07-02 10:24:49,956 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:49,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0575356
 2023-07-02 10:24:49,958 [model] Computed derived parameters: {}
 2023-07-02 10:24:49,958 [mcmc] New sample, #403:
   Omega_m:0.343078
 2023-07-02 10:24:49,958 [model] Posterior to be computed for parameters {'Omega_m': 0.836930120958044}
 2023-07-02 10:24:49,958 [prior] Evaluating prior at array([0.83693012])
 2023-07-02 10:24:49,958 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:49,959 [model] Got input parameters: {'Omega_m': 0.836930120958044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,959 [classy] Got parameters {'Omega_m': 0.836930120958044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:49,959 [classy] Computing new state
 2023-07-02 10:24:49,959 [classy] Setting parameters: {'Omega_m': 0.836930120958044, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.66848746897219}
 2023-07-02 10:24:50,005 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,007 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.78685
 2023-07-02 10:24:50,007 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,007 [model] Posterior to be computed for parameters {'Omega_m': 0.20576761183048878}
 2023-07-02 10:24:50,007 [prior] Evaluating prior at array([0.20576761])
 2023-07-02 10:24:50,007 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,007 [model] Got input parameters: {'Omega_m': 0.20576761183048878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,007 [classy] Got parameters {'Omega_m': 0.20576761183048878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,007 [classy] Computing new state
 2023-07-02 10:24:50,007 [classy] Setting parameters: {'Omega_m': 0.20576761183048878, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,058 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.48396704406545}
 2023-07-02 10:24:50,058 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.940712
 2023-07-02 10:24:50,059 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,060 [mcmc] New sample, #404:
   Omega_m:0.3442571
 2023-07-02 10:24:50,060 [model] Posterior to be computed for parameters {'Omega_m': 0.02918154655298144}
 2023-07-02 10:24:50,060 [prior] Evaluating prior at array([0.02918155])
 2023-07-02 10:24:50,060 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:50,060 [model] Posterior to be computed for parameters {'Omega_m': 0.6108762565689925}
 2023-07-02 10:24:50,060 [prior] Evaluating prior at array([0.61087626])
 2023-07-02 10:24:50,060 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,060 [model] Got input parameters: {'Omega_m': 0.6108762565689925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,060 [classy] Got parameters {'Omega_m': 0.6108762565689925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,060 [classy] Computing new state
 2023-07-02 10:24:50,060 [classy] Setting parameters: {'Omega_m': 0.6108762565689925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,110 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.58779075286111}
 2023-07-02 10:24:50,110 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.02993
 2023-07-02 10:24:50,111 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,112 [model] Posterior to be computed for parameters {'Omega_m': 0.17514637902339814}
 2023-07-02 10:24:50,112 [prior] Evaluating prior at array([0.17514638])
 2023-07-02 10:24:50,112 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,112 [model] Got input parameters: {'Omega_m': 0.17514637902339814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,112 [classy] Got parameters {'Omega_m': 0.17514637902339814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,112 [classy] Computing new state
 2023-07-02 10:24:50,112 [classy] Setting parameters: {'Omega_m': 0.17514637902339814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,159 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.01322003614166}
 2023-07-02 10:24:50,159 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,161 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.7223
 2023-07-02 10:24:50,161 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,161 [model] Posterior to be computed for parameters {'Omega_m': 0.11459836405881604}
 2023-07-02 10:24:50,162 [prior] Evaluating prior at array([0.11459836])
 2023-07-02 10:24:50,162 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,162 [model] Got input parameters: {'Omega_m': 0.11459836405881604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,162 [classy] Got parameters {'Omega_m': 0.11459836405881604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,162 [classy] Computing new state
 2023-07-02 10:24:50,162 [classy] Setting parameters: {'Omega_m': 0.11459836405881604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 181.333180885917}
 2023-07-02 10:24:50,208 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,210 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.48476
 2023-07-02 10:24:50,210 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,210 [model] Posterior to be computed for parameters {'Omega_m': 0.27337782827443013}
 2023-07-02 10:24:50,210 [prior] Evaluating prior at array([0.27337783])
 2023-07-02 10:24:50,210 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,211 [model] Got input parameters: {'Omega_m': 0.27337782827443013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,211 [classy] Got parameters {'Omega_m': 0.27337782827443013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,211 [classy] Computing new state
 2023-07-02 10:24:50,211 [classy] Setting parameters: {'Omega_m': 0.27337782827443013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.24546834018247}
 2023-07-02 10:24:50,257 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,259 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103962
 2023-07-02 10:24:50,259 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,259 [mcmc] New sample, #405:
   Omega_m:0.2057676
 2023-07-02 10:24:50,259 [model] Posterior to be computed for parameters {'Omega_m': 0.06543828708372013}
 2023-07-02 10:24:50,259 [prior] Evaluating prior at array([0.06543829])
 2023-07-02 10:24:50,259 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:50,259 [model] Posterior to be computed for parameters {'Omega_m': 0.20548040072543283}
 2023-07-02 10:24:50,259 [prior] Evaluating prior at array([0.2054804])
 2023-07-02 10:24:50,260 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,260 [model] Got input parameters: {'Omega_m': 0.20548040072543283, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,260 [classy] Got parameters {'Omega_m': 0.20548040072543283, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,260 [classy] Computing new state
 2023-07-02 10:24:50,260 [classy] Setting parameters: {'Omega_m': 0.20548040072543283, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.5328560491312}
 2023-07-02 10:24:50,307 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.946637
 2023-07-02 10:24:50,309 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,309 [model] Posterior to be computed for parameters {'Omega_m': 0.2856377556595243}
 2023-07-02 10:24:50,309 [prior] Evaluating prior at array([0.28563776])
 2023-07-02 10:24:50,309 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,309 [model] Got input parameters: {'Omega_m': 0.2856377556595243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,309 [classy] Got parameters {'Omega_m': 0.2856377556595243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,309 [classy] Computing new state
 2023-07-02 10:24:50,309 [classy] Setting parameters: {'Omega_m': 0.2856377556595243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.6194210467605}
 2023-07-02 10:24:50,357 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0475339
 2023-07-02 10:24:50,359 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,359 [mcmc] New sample, #406:
   Omega_m:0.2733778
 2023-07-02 10:24:50,359 [model] Posterior to be computed for parameters {'Omega_m': 0.11620963555030883}
 2023-07-02 10:24:50,359 [prior] Evaluating prior at array([0.11620964])
 2023-07-02 10:24:50,360 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,360 [model] Got input parameters: {'Omega_m': 0.11620963555030883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,360 [classy] Got parameters {'Omega_m': 0.11620963555030883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,360 [classy] Computing new state
 2023-07-02 10:24:50,360 [classy] Setting parameters: {'Omega_m': 0.11620963555030883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,410 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 180.92664751335647}
 2023-07-02 10:24:50,410 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,412 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.38293
 2023-07-02 10:24:50,412 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,412 [model] Posterior to be computed for parameters {'Omega_m': -0.12282832034375685}
 2023-07-02 10:24:50,412 [prior] Evaluating prior at array([-0.12282832])
 2023-07-02 10:24:50,413 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:50,413 [model] Posterior to be computed for parameters {'Omega_m': 0.6561637762467107}
 2023-07-02 10:24:50,413 [prior] Evaluating prior at array([0.65616378])
 2023-07-02 10:24:50,413 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,413 [model] Got input parameters: {'Omega_m': 0.6561637762467107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,413 [classy] Got parameters {'Omega_m': 0.6561637762467107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,413 [classy] Computing new state
 2023-07-02 10:24:50,413 [classy] Setting parameters: {'Omega_m': 0.6561637762467107, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.85448393076001}
 2023-07-02 10:24:50,464 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,466 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.74545
 2023-07-02 10:24:50,466 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,466 [model] Posterior to be computed for parameters {'Omega_m': 0.5860648575297149}
 2023-07-02 10:24:50,466 [prior] Evaluating prior at array([0.58606486])
 2023-07-02 10:24:50,467 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,467 [model] Got input parameters: {'Omega_m': 0.5860648575297149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,467 [classy] Got parameters {'Omega_m': 0.5860648575297149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,467 [classy] Computing new state
 2023-07-02 10:24:50,467 [classy] Setting parameters: {'Omega_m': 0.5860648575297149, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.1773244551881}
 2023-07-02 10:24:50,516 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,518 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.65168
 2023-07-02 10:24:50,519 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,519 [mcmc] New sample, #407:
   Omega_m:0.2856378
 2023-07-02 10:24:50,519 [model] Posterior to be computed for parameters {'Omega_m': 0.741787022984269}
 2023-07-02 10:24:50,519 [prior] Evaluating prior at array([0.74178702])
 2023-07-02 10:24:50,519 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,519 [model] Got input parameters: {'Omega_m': 0.741787022984269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,519 [classy] Got parameters {'Omega_m': 0.741787022984269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,519 [classy] Computing new state
 2023-07-02 10:24:50,519 [classy] Setting parameters: {'Omega_m': 0.741787022984269, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,565 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.19864184456952}
 2023-07-02 10:24:50,565 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,568 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.16057
 2023-07-02 10:24:50,568 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,568 [model] Posterior to be computed for parameters {'Omega_m': 0.6191618831458678}
 2023-07-02 10:24:50,569 [prior] Evaluating prior at array([0.61916188])
 2023-07-02 10:24:50,569 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,569 [model] Got input parameters: {'Omega_m': 0.6191618831458678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,569 [classy] Got parameters {'Omega_m': 0.6191618831458678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,569 [classy] Computing new state
 2023-07-02 10:24:50,569 [classy] Setting parameters: {'Omega_m': 0.6191618831458678, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.07202655109462}
 2023-07-02 10:24:50,618 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,620 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.1586
 2023-07-02 10:24:50,620 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,620 [model] Posterior to be computed for parameters {'Omega_m': 0.815521316179243}
 2023-07-02 10:24:50,620 [prior] Evaluating prior at array([0.81552132])
 2023-07-02 10:24:50,620 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,620 [model] Got input parameters: {'Omega_m': 0.815521316179243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,620 [classy] Got parameters {'Omega_m': 0.815521316179243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,620 [classy] Computing new state
 2023-07-02 10:24:50,620 [classy] Setting parameters: {'Omega_m': 0.815521316179243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,668 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.63635163027793}
 2023-07-02 10:24:50,669 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,670 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.41802
 2023-07-02 10:24:50,670 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,671 [model] Posterior to be computed for parameters {'Omega_m': 0.45823077352968233}
 2023-07-02 10:24:50,671 [prior] Evaluating prior at array([0.45823077])
 2023-07-02 10:24:50,671 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,671 [model] Got input parameters: {'Omega_m': 0.45823077352968233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,671 [classy] Got parameters {'Omega_m': 0.45823077352968233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,671 [classy] Computing new state
 2023-07-02 10:24:50,671 [classy] Setting parameters: {'Omega_m': 0.45823077352968233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.64694478746662}
 2023-07-02 10:24:50,720 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,722 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.946094
 2023-07-02 10:24:50,722 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,722 [mcmc] New sample, #408:
   Omega_m:0.5860649
 2023-07-02 10:24:50,722 [model] Posterior to be computed for parameters {'Omega_m': 0.8787783384084056}
 2023-07-02 10:24:50,722 [prior] Evaluating prior at array([0.87877834])
 2023-07-02 10:24:50,722 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,722 [model] Got input parameters: {'Omega_m': 0.8787783384084056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,722 [classy] Got parameters {'Omega_m': 0.8787783384084056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,722 [classy] Computing new state
 2023-07-02 10:24:50,722 [classy] Setting parameters: {'Omega_m': 0.8787783384084056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,770 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.85400903458876}
 2023-07-02 10:24:50,770 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,771 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.51051
 2023-07-02 10:24:50,771 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,772 [model] Posterior to be computed for parameters {'Omega_m': 0.5830156049981488}
 2023-07-02 10:24:50,772 [prior] Evaluating prior at array([0.5830156])
 2023-07-02 10:24:50,772 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,772 [model] Got input parameters: {'Omega_m': 0.5830156049981488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,772 [classy] Got parameters {'Omega_m': 0.5830156049981488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,772 [classy] Computing new state
 2023-07-02 10:24:50,772 [classy] Setting parameters: {'Omega_m': 0.5830156049981488, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,820 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.3775227686365}
 2023-07-02 10:24:50,820 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,822 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.60597
 2023-07-02 10:24:50,822 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,822 [model] Posterior to be computed for parameters {'Omega_m': 0.6848629463642}
 2023-07-02 10:24:50,822 [prior] Evaluating prior at array([0.68486295])
 2023-07-02 10:24:50,822 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,822 [model] Got input parameters: {'Omega_m': 0.6848629463642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,822 [classy] Got parameters {'Omega_m': 0.6848629463642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,822 [classy] Computing new state
 2023-07-02 10:24:50,822 [classy] Setting parameters: {'Omega_m': 0.6848629463642, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,870 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.22439275875857}
 2023-07-02 10:24:50,870 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,871 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.21228
 2023-07-02 10:24:50,871 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,872 [model] Posterior to be computed for parameters {'Omega_m': 0.47991352672268056}
 2023-07-02 10:24:50,872 [prior] Evaluating prior at array([0.47991353])
 2023-07-02 10:24:50,872 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,872 [model] Got input parameters: {'Omega_m': 0.47991352672268056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,872 [classy] Got parameters {'Omega_m': 0.47991352672268056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,872 [classy] Computing new state
 2023-07-02 10:24:50,872 [classy] Setting parameters: {'Omega_m': 0.47991352672268056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.8661198169364}
 2023-07-02 10:24:50,920 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,922 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.19757
 2023-07-02 10:24:50,922 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,922 [mcmc] New sample, #409:
   Omega_m:0.4582308
 2023-07-02 10:24:50,922 [model] Posterior to be computed for parameters {'Omega_m': 0.5127997041626268}
 2023-07-02 10:24:50,922 [prior] Evaluating prior at array([0.5127997])
 2023-07-02 10:24:50,922 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,922 [model] Got input parameters: {'Omega_m': 0.5127997041626268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,922 [classy] Got parameters {'Omega_m': 0.5127997041626268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,923 [classy] Computing new state
 2023-07-02 10:24:50,923 [classy] Setting parameters: {'Omega_m': 0.5127997041626268, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:50,970 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.3128650034056}
 2023-07-02 10:24:50,970 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:50,972 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.61309
 2023-07-02 10:24:50,972 [model] Computed derived parameters: {}
 2023-07-02 10:24:50,972 [model] Posterior to be computed for parameters {'Omega_m': 0.5797714435016257}
 2023-07-02 10:24:50,972 [prior] Evaluating prior at array([0.57977144])
 2023-07-02 10:24:50,972 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:50,972 [model] Got input parameters: {'Omega_m': 0.5797714435016257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,972 [classy] Got parameters {'Omega_m': 0.5797714435016257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:50,972 [classy] Computing new state
 2023-07-02 10:24:50,972 [classy] Setting parameters: {'Omega_m': 0.5797714435016257, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.5917187630541}
 2023-07-02 10:24:51,020 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,022 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.55755
 2023-07-02 10:24:51,022 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,022 [model] Posterior to be computed for parameters {'Omega_m': 0.21028387720293723}
 2023-07-02 10:24:51,022 [prior] Evaluating prior at array([0.21028388])
 2023-07-02 10:24:51,022 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,022 [model] Got input parameters: {'Omega_m': 0.21028387720293723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,022 [classy] Got parameters {'Omega_m': 0.21028387720293723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,022 [classy] Computing new state
 2023-07-02 10:24:51,022 [classy] Setting parameters: {'Omega_m': 0.21028387720293723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,069 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 161.72208141976742}
 2023-07-02 10:24:51,070 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,071 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.850685
 2023-07-02 10:24:51,071 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,071 [mcmc] New sample, #410:
   Omega_m:0.4799135
 2023-07-02 10:24:51,072 [model] Posterior to be computed for parameters {'Omega_m': 0.32375120716287425}
 2023-07-02 10:24:51,072 [prior] Evaluating prior at array([0.32375121])
 2023-07-02 10:24:51,072 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,072 [model] Got input parameters: {'Omega_m': 0.32375120716287425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,072 [classy] Got parameters {'Omega_m': 0.32375120716287425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,072 [classy] Computing new state
 2023-07-02 10:24:51,072 [classy] Setting parameters: {'Omega_m': 0.32375120716287425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,120 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92568870784214}
 2023-07-02 10:24:51,120 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,121 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00777363
 2023-07-02 10:24:51,122 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,122 [mcmc] New sample, #411:
   Omega_m:0.2102839
 2023-07-02 10:24:51,122 [model] Posterior to be computed for parameters {'Omega_m': 0.07919556872374156}
 2023-07-02 10:24:51,122 [prior] Evaluating prior at array([0.07919557])
 2023-07-02 10:24:51,122 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:51,122 [model] Posterior to be computed for parameters {'Omega_m': 0.5843471994423544}
 2023-07-02 10:24:51,122 [prior] Evaluating prior at array([0.5843472])
 2023-07-02 10:24:51,122 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,122 [model] Got input parameters: {'Omega_m': 0.5843471994423544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,122 [classy] Got parameters {'Omega_m': 0.5843471994423544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,122 [classy] Computing new state
 2023-07-02 10:24:51,122 [classy] Setting parameters: {'Omega_m': 0.5843471994423544, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.28996213032066}
 2023-07-02 10:24:51,171 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62591
 2023-07-02 10:24:51,173 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,173 [model] Posterior to be computed for parameters {'Omega_m': -0.023713783748902095}
 2023-07-02 10:24:51,173 [prior] Evaluating prior at array([-0.02371378])
 2023-07-02 10:24:51,173 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:51,173 [model] Posterior to be computed for parameters {'Omega_m': 0.23140780681585238}
 2023-07-02 10:24:51,173 [prior] Evaluating prior at array([0.23140781])
 2023-07-02 10:24:51,173 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,173 [model] Got input parameters: {'Omega_m': 0.23140780681585238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,173 [classy] Got parameters {'Omega_m': 0.23140780681585238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,173 [classy] Computing new state
 2023-07-02 10:24:51,173 [classy] Setting parameters: {'Omega_m': 0.23140780681585238, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.3196531874321}
 2023-07-02 10:24:51,223 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,224 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.502228
 2023-07-02 10:24:51,224 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,224 [mcmc] New sample, #412:
   Omega_m:0.3237512
 2023-07-02 10:24:51,224 [model] Posterior to be computed for parameters {'Omega_m': 0.22171335447387375}
 2023-07-02 10:24:51,225 [prior] Evaluating prior at array([0.22171335])
 2023-07-02 10:24:51,225 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,225 [model] Got input parameters: {'Omega_m': 0.22171335447387375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,225 [classy] Got parameters {'Omega_m': 0.22171335447387375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,225 [classy] Computing new state
 2023-07-02 10:24:51,225 [classy] Setting parameters: {'Omega_m': 0.22171335447387375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.8492933806491}
 2023-07-02 10:24:51,273 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.647974
 2023-07-02 10:24:51,275 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,275 [mcmc] New sample, #413:
   Omega_m:0.2314078
 2023-07-02 10:24:51,275 [model] Posterior to be computed for parameters {'Omega_m': 0.036911028921373046}
 2023-07-02 10:24:51,275 [prior] Evaluating prior at array([0.03691103])
 2023-07-02 10:24:51,275 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:51,275 [model] Posterior to be computed for parameters {'Omega_m': 0.4403621962358777}
 2023-07-02 10:24:51,275 [prior] Evaluating prior at array([0.4403622])
 2023-07-02 10:24:51,275 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,275 [model] Got input parameters: {'Omega_m': 0.4403621962358777, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,275 [classy] Got parameters {'Omega_m': 0.4403621962358777, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,275 [classy] Computing new state
 2023-07-02 10:24:51,275 [classy] Setting parameters: {'Omega_m': 0.4403621962358777, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.1781430129762}
 2023-07-02 10:24:51,324 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.754544
 2023-07-02 10:24:51,326 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,326 [mcmc] New sample, #414:
   Omega_m:0.2217134
 2023-07-02 10:24:51,326 [model] Posterior to be computed for parameters {'Omega_m': 0.508242296226595}
 2023-07-02 10:24:51,326 [prior] Evaluating prior at array([0.5082423])
 2023-07-02 10:24:51,326 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,326 [model] Got input parameters: {'Omega_m': 0.508242296226595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,326 [classy] Got parameters {'Omega_m': 0.508242296226595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,326 [classy] Computing new state
 2023-07-02 10:24:51,326 [classy] Setting parameters: {'Omega_m': 0.508242296226595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.65669616063835}
 2023-07-02 10:24:51,374 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,376 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.55331
 2023-07-02 10:24:51,376 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,376 [mcmc] New sample, #415:
   Omega_m:0.4403622
 2023-07-02 10:24:51,376 [model] Posterior to be computed for parameters {'Omega_m': 0.3614251845518407}
 2023-07-02 10:24:51,376 [prior] Evaluating prior at array([0.36142518])
 2023-07-02 10:24:51,376 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,376 [model] Got input parameters: {'Omega_m': 0.3614251845518407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,376 [classy] Got parameters {'Omega_m': 0.3614251845518407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,376 [classy] Computing new state
 2023-07-02 10:24:51,376 [classy] Setting parameters: {'Omega_m': 0.3614251845518407, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.7494722607087}
 2023-07-02 10:24:51,425 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,427 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.130944
 2023-07-02 10:24:51,427 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,427 [mcmc] New sample, #416:
   Omega_m:0.5082423
 2023-07-02 10:24:51,427 [model] Posterior to be computed for parameters {'Omega_m': 0.15001178474665575}
 2023-07-02 10:24:51,427 [prior] Evaluating prior at array([0.15001178])
 2023-07-02 10:24:51,427 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,427 [model] Got input parameters: {'Omega_m': 0.15001178474665575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,427 [classy] Got parameters {'Omega_m': 0.15001178474665575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,427 [classy] Computing new state
 2023-07-02 10:24:51,427 [classy] Setting parameters: {'Omega_m': 0.15001178474665575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,475 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.09995122394395}
 2023-07-02 10:24:51,475 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,477 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.63456
 2023-07-02 10:24:51,477 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,477 [model] Posterior to be computed for parameters {'Omega_m': 0.3443193306891126}
 2023-07-02 10:24:51,477 [prior] Evaluating prior at array([0.34431933])
 2023-07-02 10:24:51,477 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,477 [model] Got input parameters: {'Omega_m': 0.3443193306891126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,477 [classy] Got parameters {'Omega_m': 0.3443193306891126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,477 [classy] Computing new state
 2023-07-02 10:24:51,477 [classy] Setting parameters: {'Omega_m': 0.3443193306891126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,525 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.59387526439167}
 2023-07-02 10:24:51,525 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,527 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0577521
 2023-07-02 10:24:51,527 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,527 [mcmc] New sample, #417:
   Omega_m:0.3614252
 2023-07-02 10:24:51,527 [model] Posterior to be computed for parameters {'Omega_m': 0.87421690913155}
 2023-07-02 10:24:51,527 [prior] Evaluating prior at array([0.87421691])
 2023-07-02 10:24:51,527 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,527 [model] Got input parameters: {'Omega_m': 0.87421690913155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,527 [classy] Got parameters {'Omega_m': 0.87421690913155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,528 [classy] Computing new state
 2023-07-02 10:24:51,528 [classy] Setting parameters: {'Omega_m': 0.87421690913155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.04703666505206}
 2023-07-02 10:24:51,575 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.4315
 2023-07-02 10:24:51,577 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,577 [model] Posterior to be computed for parameters {'Omega_m': 0.2806338643456273}
 2023-07-02 10:24:51,577 [prior] Evaluating prior at array([0.28063386])
 2023-07-02 10:24:51,577 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,577 [model] Got input parameters: {'Omega_m': 0.2806338643456273, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,577 [classy] Got parameters {'Omega_m': 0.2806338643456273, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,577 [classy] Computing new state
 2023-07-02 10:24:51,578 [classy] Setting parameters: {'Omega_m': 0.2806338643456273, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.27575194931487}
 2023-07-02 10:24:51,625 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0677095
 2023-07-02 10:24:51,627 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,627 [mcmc] New sample, #418:
   Omega_m:0.3443193
 2023-07-02 10:24:51,627 [model] Posterior to be computed for parameters {'Omega_m': 0.32923797554627726}
 2023-07-02 10:24:51,627 [prior] Evaluating prior at array([0.32923798])
 2023-07-02 10:24:51,627 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,627 [model] Got input parameters: {'Omega_m': 0.32923797554627726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,627 [classy] Got parameters {'Omega_m': 0.32923797554627726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,627 [classy] Computing new state
 2023-07-02 10:24:51,627 [classy] Setting parameters: {'Omega_m': 0.32923797554627726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29081874657084}
 2023-07-02 10:24:51,676 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0167233
 2023-07-02 10:24:51,678 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,678 [mcmc] New sample, #419:
   Omega_m:0.2806339
 2023-07-02 10:24:51,678 [model] Posterior to be computed for parameters {'Omega_m': 0.6025795779497076}
 2023-07-02 10:24:51,678 [prior] Evaluating prior at array([0.60257958])
 2023-07-02 10:24:51,678 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,678 [model] Got input parameters: {'Omega_m': 0.6025795779497076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,678 [classy] Got parameters {'Omega_m': 0.6025795779497076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,678 [classy] Computing new state
 2023-07-02 10:24:51,678 [classy] Setting parameters: {'Omega_m': 0.6025795779497076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.11166858673302}
 2023-07-02 10:24:51,727 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,730 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.90223
 2023-07-02 10:24:51,730 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,730 [model] Posterior to be computed for parameters {'Omega_m': 0.2023026033897107}
 2023-07-02 10:24:51,730 [prior] Evaluating prior at array([0.2023026])
 2023-07-02 10:24:51,730 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,730 [model] Got input parameters: {'Omega_m': 0.2023026033897107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,730 [classy] Got parameters {'Omega_m': 0.2023026033897107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,730 [classy] Computing new state
 2023-07-02 10:24:51,730 [classy] Setting parameters: {'Omega_m': 0.2023026033897107, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.07729046721232}
 2023-07-02 10:24:51,777 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.01383
 2023-07-02 10:24:51,780 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,780 [mcmc] New sample, #420:
   Omega_m:0.329238
 2023-07-02 10:24:51,780 [model] Posterior to be computed for parameters {'Omega_m': 0.5419348073468846}
 2023-07-02 10:24:51,780 [prior] Evaluating prior at array([0.54193481])
 2023-07-02 10:24:51,780 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,780 [model] Got input parameters: {'Omega_m': 0.5419348073468846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,780 [classy] Got parameters {'Omega_m': 0.5419348073468846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,780 [classy] Computing new state
 2023-07-02 10:24:51,780 [classy] Setting parameters: {'Omega_m': 0.5419348073468846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.18559373674135}
 2023-07-02 10:24:51,828 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00987
 2023-07-02 10:24:51,830 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,830 [model] Posterior to be computed for parameters {'Omega_m': 0.5066237293406393}
 2023-07-02 10:24:51,830 [prior] Evaluating prior at array([0.50662373])
 2023-07-02 10:24:51,830 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,830 [model] Got input parameters: {'Omega_m': 0.5066237293406393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,830 [classy] Got parameters {'Omega_m': 0.5066237293406393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,830 [classy] Computing new state
 2023-07-02 10:24:51,830 [classy] Setting parameters: {'Omega_m': 0.5066237293406393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.77956314268334}
 2023-07-02 10:24:51,878 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.53224
 2023-07-02 10:24:51,880 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,880 [mcmc] New sample, #421:
   Omega_m:0.2023026
 2023-07-02 10:24:51,880 [model] Posterior to be computed for parameters {'Omega_m': 1.197500045254602}
 2023-07-02 10:24:51,880 [prior] Evaluating prior at array([1.19750005])
 2023-07-02 10:24:51,880 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:51,880 [model] Posterior to be computed for parameters {'Omega_m': 0.4699972885092816}
 2023-07-02 10:24:51,880 [prior] Evaluating prior at array([0.46999729])
 2023-07-02 10:24:51,880 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,881 [model] Got input parameters: {'Omega_m': 0.4699972885092816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,881 [classy] Got parameters {'Omega_m': 0.4699972885092816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,881 [classy] Computing new state
 2023-07-02 10:24:51,881 [classy] Setting parameters: {'Omega_m': 0.4699972885092816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.67044549921172}
 2023-07-02 10:24:51,928 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.08013
 2023-07-02 10:24:51,930 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,931 [mcmc] New sample, #422:
   Omega_m:0.5066237
 2023-07-02 10:24:51,931 [model] Posterior to be computed for parameters {'Omega_m': 0.7694356774850792}
 2023-07-02 10:24:51,931 [prior] Evaluating prior at array([0.76943568])
 2023-07-02 10:24:51,931 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,931 [model] Got input parameters: {'Omega_m': 0.7694356774850792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,931 [classy] Got parameters {'Omega_m': 0.7694356774850792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,931 [classy] Computing new state
 2023-07-02 10:24:51,931 [classy] Setting parameters: {'Omega_m': 0.7694356774850792, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:51,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.81897686489529}
 2023-07-02 10:24:51,978 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:51,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.62915
 2023-07-02 10:24:51,980 [model] Computed derived parameters: {}
 2023-07-02 10:24:51,980 [model] Posterior to be computed for parameters {'Omega_m': 0.833578088297452}
 2023-07-02 10:24:51,980 [prior] Evaluating prior at array([0.83357809])
 2023-07-02 10:24:51,981 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:51,981 [model] Got input parameters: {'Omega_m': 0.833578088297452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,981 [classy] Got parameters {'Omega_m': 0.833578088297452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:51,981 [classy] Computing new state
 2023-07-02 10:24:51,981 [classy] Setting parameters: {'Omega_m': 0.833578088297452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,036 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.81820859135057}
 2023-07-02 10:24:52,036 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,038 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.72902
 2023-07-02 10:24:52,038 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,038 [model] Posterior to be computed for parameters {'Omega_m': 0.7839807322063569}
 2023-07-02 10:24:52,038 [prior] Evaluating prior at array([0.78398073])
 2023-07-02 10:24:52,038 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,038 [model] Got input parameters: {'Omega_m': 0.7839807322063569, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,038 [classy] Got parameters {'Omega_m': 0.7839807322063569, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,038 [classy] Computing new state
 2023-07-02 10:24:52,039 [classy] Setting parameters: {'Omega_m': 0.7839807322063569, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.11488315905197}
 2023-07-02 10:24:52,087 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.8772
 2023-07-02 10:24:52,089 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,089 [model] Posterior to be computed for parameters {'Omega_m': 0.4399397764328308}
 2023-07-02 10:24:52,089 [prior] Evaluating prior at array([0.43993978])
 2023-07-02 10:24:52,089 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,089 [model] Got input parameters: {'Omega_m': 0.4399397764328308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,089 [classy] Got parameters {'Omega_m': 0.4399397764328308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,089 [classy] Computing new state
 2023-07-02 10:24:52,089 [classy] Setting parameters: {'Omega_m': 0.4399397764328308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.21507472043444}
 2023-07-02 10:24:52,139 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,141 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.750202
 2023-07-02 10:24:52,141 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,141 [mcmc] New sample, #423:
   Omega_m:0.4699973
 2023-07-02 10:24:52,141 [model] Posterior to be computed for parameters {'Omega_m': 0.43529853234449734}
 2023-07-02 10:24:52,141 [prior] Evaluating prior at array([0.43529853])
 2023-07-02 10:24:52,141 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,141 [model] Got input parameters: {'Omega_m': 0.43529853234449734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,141 [classy] Got parameters {'Omega_m': 0.43529853234449734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,141 [classy] Computing new state
 2023-07-02 10:24:52,141 [classy] Setting parameters: {'Omega_m': 0.43529853234449734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,190 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.62314468456552}
 2023-07-02 10:24:52,190 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,192 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.703097
 2023-07-02 10:24:52,192 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,192 [mcmc] New sample, #424:
   Omega_m:0.4399398
 2023-07-02 10:24:52,192 [model] Posterior to be computed for parameters {'Omega_m': 0.42970801125083347}
 2023-07-02 10:24:52,192 [prior] Evaluating prior at array([0.42970801])
 2023-07-02 10:24:52,192 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,192 [model] Got input parameters: {'Omega_m': 0.42970801125083347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,192 [classy] Got parameters {'Omega_m': 0.42970801125083347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,192 [classy] Computing new state
 2023-07-02 10:24:52,193 [classy] Setting parameters: {'Omega_m': 0.42970801125083347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.1203113760143}
 2023-07-02 10:24:52,242 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,243 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.647856
 2023-07-02 10:24:52,243 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,243 [mcmc] New sample, #425:
   Omega_m:0.4352985
 2023-07-02 10:24:52,243 [model] Posterior to be computed for parameters {'Omega_m': 0.5874781931486645}
 2023-07-02 10:24:52,243 [prior] Evaluating prior at array([0.58747819])
 2023-07-02 10:24:52,244 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,244 [model] Got input parameters: {'Omega_m': 0.5874781931486645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,244 [classy] Got parameters {'Omega_m': 0.5874781931486645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,244 [classy] Computing new state
 2023-07-02 10:24:52,244 [classy] Setting parameters: {'Omega_m': 0.5874781931486645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.08490706643138}
 2023-07-02 10:24:52,292 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,294 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.67292
 2023-07-02 10:24:52,294 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,294 [mcmc] New sample, #426:
   Omega_m:0.429708
 2023-07-02 10:24:52,294 [model] Posterior to be computed for parameters {'Omega_m': 0.7731889371190399}
 2023-07-02 10:24:52,294 [prior] Evaluating prior at array([0.77318894])
 2023-07-02 10:24:52,295 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,295 [model] Got input parameters: {'Omega_m': 0.7731889371190399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,295 [classy] Got parameters {'Omega_m': 0.7731889371190399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,295 [classy] Computing new state
 2023-07-02 10:24:52,295 [classy] Setting parameters: {'Omega_m': 0.7731889371190399, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.63589192344611}
 2023-07-02 10:24:52,343 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.69307
 2023-07-02 10:24:52,345 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,345 [model] Posterior to be computed for parameters {'Omega_m': 1.3548471072314854}
 2023-07-02 10:24:52,345 [prior] Evaluating prior at array([1.35484711])
 2023-07-02 10:24:52,346 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:52,346 [model] Posterior to be computed for parameters {'Omega_m': 0.6800621098437819}
 2023-07-02 10:24:52,346 [prior] Evaluating prior at array([0.68006211])
 2023-07-02 10:24:52,346 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,346 [model] Got input parameters: {'Omega_m': 0.6800621098437819, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,346 [classy] Got parameters {'Omega_m': 0.6800621098437819, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,346 [classy] Computing new state
 2023-07-02 10:24:52,346 [classy] Setting parameters: {'Omega_m': 0.6800621098437819, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.49192764542691}
 2023-07-02 10:24:52,393 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,395 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.13357
 2023-07-02 10:24:52,395 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,395 [mcmc] New sample, #427:
   Omega_m:0.5874782
 2023-07-02 10:24:52,395 [model] Posterior to be computed for parameters {'Omega_m': 0.7073102493066185}
 2023-07-02 10:24:52,395 [prior] Evaluating prior at array([0.70731025])
 2023-07-02 10:24:52,395 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,395 [model] Got input parameters: {'Omega_m': 0.7073102493066185, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,395 [classy] Got parameters {'Omega_m': 0.7073102493066185, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,395 [classy] Computing new state
 2023-07-02 10:24:52,396 [classy] Setting parameters: {'Omega_m': 0.7073102493066185, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.99978828224823}
 2023-07-02 10:24:52,443 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.58312
 2023-07-02 10:24:52,445 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,445 [model] Posterior to be computed for parameters {'Omega_m': 0.4613570781872015}
 2023-07-02 10:24:52,445 [prior] Evaluating prior at array([0.46135708])
 2023-07-02 10:24:52,445 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,445 [model] Got input parameters: {'Omega_m': 0.4613570781872015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,445 [classy] Got parameters {'Omega_m': 0.4613570781872015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,445 [classy] Computing new state
 2023-07-02 10:24:52,445 [classy] Setting parameters: {'Omega_m': 0.4613570781872015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.3851071583867}
 2023-07-02 10:24:52,494 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.98112
 2023-07-02 10:24:52,496 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,496 [mcmc] New sample, #428:
   Omega_m:0.6800621
 2023-07-02 10:24:52,496 [model] Posterior to be computed for parameters {'Omega_m': 1.2965372910821473}
 2023-07-02 10:24:52,496 [prior] Evaluating prior at array([1.29653729])
 2023-07-02 10:24:52,496 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:52,496 [model] Posterior to be computed for parameters {'Omega_m': 0.433751590711657}
 2023-07-02 10:24:52,496 [prior] Evaluating prior at array([0.43375159])
 2023-07-02 10:24:52,497 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,497 [model] Got input parameters: {'Omega_m': 0.433751590711657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,497 [classy] Got parameters {'Omega_m': 0.433751590711657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,497 [classy] Computing new state
 2023-07-02 10:24:52,497 [classy] Setting parameters: {'Omega_m': 0.433751590711657, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.76009381562315}
 2023-07-02 10:24:52,545 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.687646
 2023-07-02 10:24:52,547 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,547 [mcmc] New sample, #429:
   Omega_m:0.4613571
 2023-07-02 10:24:52,547 [model] Posterior to be computed for parameters {'Omega_m': 0.6356044176458548}
 2023-07-02 10:24:52,547 [prior] Evaluating prior at array([0.63560442])
 2023-07-02 10:24:52,547 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,547 [model] Got input parameters: {'Omega_m': 0.6356044176458548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,547 [classy] Got parameters {'Omega_m': 0.6356044176458548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,547 [classy] Computing new state
 2023-07-02 10:24:52,547 [classy] Setting parameters: {'Omega_m': 0.6356044176458548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,593 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.06973189124147}
 2023-07-02 10:24:52,593 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,596 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.41704
 2023-07-02 10:24:52,596 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,596 [model] Posterior to be computed for parameters {'Omega_m': 0.22830072177813987}
 2023-07-02 10:24:52,596 [prior] Evaluating prior at array([0.22830072])
 2023-07-02 10:24:52,596 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,596 [model] Got input parameters: {'Omega_m': 0.22830072177813987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,596 [classy] Got parameters {'Omega_m': 0.22830072177813987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,596 [classy] Computing new state
 2023-07-02 10:24:52,596 [classy] Setting parameters: {'Omega_m': 0.22830072177813987, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,645 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.8042634028049}
 2023-07-02 10:24:52,645 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,647 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.54646
 2023-07-02 10:24:52,647 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,647 [mcmc] New sample, #430:
   Omega_m:0.4337516
 2023-07-02 10:24:52,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3304817502187113}
 2023-07-02 10:24:52,647 [prior] Evaluating prior at array([0.33048175])
 2023-07-02 10:24:52,647 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,647 [model] Got input parameters: {'Omega_m': 0.3304817502187113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,647 [classy] Got parameters {'Omega_m': 0.3304817502187113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,648 [classy] Computing new state
 2023-07-02 10:24:52,648 [classy] Setting parameters: {'Omega_m': 0.3304817502187113, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,694 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.14823956229984}
 2023-07-02 10:24:52,695 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0192101
 2023-07-02 10:24:52,697 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,697 [mcmc] New sample, #431:
   Omega_m:0.2283007
 2023-07-02 10:24:52,697 [model] Posterior to be computed for parameters {'Omega_m': 0.42739131906829947}
 2023-07-02 10:24:52,697 [prior] Evaluating prior at array([0.42739132])
 2023-07-02 10:24:52,697 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,697 [model] Got input parameters: {'Omega_m': 0.42739131906829947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,697 [classy] Got parameters {'Omega_m': 0.42739131906829947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,697 [classy] Computing new state
 2023-07-02 10:24:52,697 [classy] Setting parameters: {'Omega_m': 0.42739131906829947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.328169915425}
 2023-07-02 10:24:52,745 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,747 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.625457
 2023-07-02 10:24:52,747 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,747 [model] Posterior to be computed for parameters {'Omega_m': 0.17772578165008182}
 2023-07-02 10:24:52,747 [prior] Evaluating prior at array([0.17772578])
 2023-07-02 10:24:52,748 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,748 [model] Got input parameters: {'Omega_m': 0.17772578165008182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,748 [classy] Got parameters {'Omega_m': 0.17772578165008182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,748 [classy] Computing new state
 2023-07-02 10:24:52,748 [classy] Setting parameters: {'Omega_m': 0.17772578165008182, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.52110724393486}
 2023-07-02 10:24:52,795 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,797 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.64374
 2023-07-02 10:24:52,797 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,797 [mcmc] New sample, #432:
   Omega_m:0.3304818
 2023-07-02 10:24:52,797 [model] Posterior to be computed for parameters {'Omega_m': 0.10891982388073515}
 2023-07-02 10:24:52,797 [prior] Evaluating prior at array([0.10891982])
 2023-07-02 10:24:52,797 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,797 [model] Got input parameters: {'Omega_m': 0.10891982388073515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,797 [classy] Got parameters {'Omega_m': 0.10891982388073515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,798 [classy] Computing new state
 2023-07-02 10:24:52,798 [classy] Setting parameters: {'Omega_m': 0.10891982388073515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.79333169423265}
 2023-07-02 10:24:52,845 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.85927
 2023-07-02 10:24:52,847 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,847 [model] Posterior to be computed for parameters {'Omega_m': -0.12960109758764807}
 2023-07-02 10:24:52,847 [prior] Evaluating prior at array([-0.1296011])
 2023-07-02 10:24:52,848 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:52,848 [model] Posterior to be computed for parameters {'Omega_m': 0.16957209924293803}
 2023-07-02 10:24:52,848 [prior] Evaluating prior at array([0.1695721])
 2023-07-02 10:24:52,848 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,848 [model] Got input parameters: {'Omega_m': 0.16957209924293803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,848 [classy] Got parameters {'Omega_m': 0.16957209924293803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,848 [classy] Computing new state
 2023-07-02 10:24:52,848 [classy] Setting parameters: {'Omega_m': 0.16957209924293803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,896 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.09481584803484}
 2023-07-02 10:24:52,896 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.90104
 2023-07-02 10:24:52,900 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,900 [mcmc] New sample, #433:
   Omega_m:0.1777258
 2023-07-02 10:24:52,900 [model] Posterior to be computed for parameters {'Omega_m': 0.35119760407553424}
 2023-07-02 10:24:52,900 [prior] Evaluating prior at array([0.3511976])
 2023-07-02 10:24:52,900 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,900 [model] Got input parameters: {'Omega_m': 0.35119760407553424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,900 [classy] Got parameters {'Omega_m': 0.35119760407553424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,900 [classy] Computing new state
 2023-07-02 10:24:52,900 [classy] Setting parameters: {'Omega_m': 0.35119760407553424, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:52,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.84235238186002}
 2023-07-02 10:24:52,950 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:52,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0839509
 2023-07-02 10:24:52,951 [model] Computed derived parameters: {}
 2023-07-02 10:24:52,951 [mcmc] New sample, #434:
   Omega_m:0.1695721
 2023-07-02 10:24:52,951 [model] Posterior to be computed for parameters {'Omega_m': -0.09756868853909945}
 2023-07-02 10:24:52,952 [prior] Evaluating prior at array([-0.09756869])
 2023-07-02 10:24:52,952 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:52,952 [model] Posterior to be computed for parameters {'Omega_m': -0.34353085489925617}
 2023-07-02 10:24:52,952 [prior] Evaluating prior at array([-0.34353085])
 2023-07-02 10:24:52,952 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:52,952 [model] Posterior to be computed for parameters {'Omega_m': 0.22860511962845703}
 2023-07-02 10:24:52,952 [prior] Evaluating prior at array([0.22860512])
 2023-07-02 10:24:52,952 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:52,952 [model] Got input parameters: {'Omega_m': 0.22860511962845703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,952 [classy] Got parameters {'Omega_m': 0.22860511962845703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:52,952 [classy] Computing new state
 2023-07-02 10:24:52,952 [classy] Setting parameters: {'Omega_m': 0.22860511962845703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.7565575633803}
 2023-07-02 10:24:53,001 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.542026
 2023-07-02 10:24:53,003 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,004 [model] Posterior to be computed for parameters {'Omega_m': 0.6533852298182787}
 2023-07-02 10:24:53,004 [prior] Evaluating prior at array([0.65338523])
 2023-07-02 10:24:53,004 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,004 [model] Got input parameters: {'Omega_m': 0.6533852298182787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,004 [classy] Got parameters {'Omega_m': 0.6533852298182787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,004 [classy] Computing new state
 2023-07-02 10:24:53,004 [classy] Setting parameters: {'Omega_m': 0.6533852298182787, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,053 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.0163331278112}
 2023-07-02 10:24:53,053 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,055 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.70075
 2023-07-02 10:24:53,055 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,055 [model] Posterior to be computed for parameters {'Omega_m': 0.5747935099801675}
 2023-07-02 10:24:53,055 [prior] Evaluating prior at array([0.57479351])
 2023-07-02 10:24:53,055 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,055 [model] Got input parameters: {'Omega_m': 0.5747935099801675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,055 [classy] Got parameters {'Omega_m': 0.5747935099801675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,055 [classy] Computing new state
 2023-07-02 10:24:53,056 [classy] Setting parameters: {'Omega_m': 0.5747935099801675, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.92280915182621}
 2023-07-02 10:24:53,105 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,107 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.48367
 2023-07-02 10:24:53,107 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,107 [model] Posterior to be computed for parameters {'Omega_m': 0.2955783918740894}
 2023-07-02 10:24:53,107 [prior] Evaluating prior at array([0.29557839])
 2023-07-02 10:24:53,107 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,107 [model] Got input parameters: {'Omega_m': 0.2955783918740894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,107 [classy] Got parameters {'Omega_m': 0.2955783918740894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,107 [classy] Computing new state
 2023-07-02 10:24:53,108 [classy] Setting parameters: {'Omega_m': 0.2955783918740894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.34458724194678}
 2023-07-02 10:24:53,158 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0184937
 2023-07-02 10:24:53,160 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,160 [mcmc] New sample, #435:
   Omega_m:0.3511976
 2023-07-02 10:24:53,160 [model] Posterior to be computed for parameters {'Omega_m': 0.18709117175057555}
 2023-07-02 10:24:53,160 [prior] Evaluating prior at array([0.18709117])
 2023-07-02 10:24:53,160 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,160 [model] Got input parameters: {'Omega_m': 0.18709117175057555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,160 [classy] Got parameters {'Omega_m': 0.18709117175057555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,160 [classy] Computing new state
 2023-07-02 10:24:53,160 [classy] Setting parameters: {'Omega_m': 0.18709117175057555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,211 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.77685888245034}
 2023-07-02 10:24:53,211 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,213 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.37932
 2023-07-02 10:24:53,213 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,213 [mcmc] New sample, #436:
   Omega_m:0.2955784
 2023-07-02 10:24:53,213 [model] Posterior to be computed for parameters {'Omega_m': -0.10217597968914022}
 2023-07-02 10:24:53,213 [prior] Evaluating prior at array([-0.10217598])
 2023-07-02 10:24:53,213 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:53,214 [model] Posterior to be computed for parameters {'Omega_m': 0.2443235813161443}
 2023-07-02 10:24:53,214 [prior] Evaluating prior at array([0.24432358])
 2023-07-02 10:24:53,214 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,214 [model] Got input parameters: {'Omega_m': 0.2443235813161443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,214 [classy] Got parameters {'Omega_m': 0.2443235813161443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,214 [classy] Computing new state
 2023-07-02 10:24:53,214 [classy] Setting parameters: {'Omega_m': 0.2443235813161443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.35984802825078}
 2023-07-02 10:24:53,264 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.34192
 2023-07-02 10:24:53,266 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,266 [mcmc] New sample, #437:
   Omega_m:0.1870912
 2023-07-02 10:24:53,266 [model] Posterior to be computed for parameters {'Omega_m': 0.4390780027300739}
 2023-07-02 10:24:53,266 [prior] Evaluating prior at array([0.439078])
 2023-07-02 10:24:53,266 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,266 [model] Got input parameters: {'Omega_m': 0.4390780027300739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,266 [classy] Got parameters {'Omega_m': 0.4390780027300739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,266 [classy] Computing new state
 2023-07-02 10:24:53,266 [classy] Setting parameters: {'Omega_m': 0.4390780027300739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.29052797349036}
 2023-07-02 10:24:53,316 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.741372
 2023-07-02 10:24:53,318 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,318 [mcmc] New sample, #438:
   Omega_m:0.2443236
 2023-07-02 10:24:53,318 [model] Posterior to be computed for parameters {'Omega_m': 0.9962645781022594}
 2023-07-02 10:24:53,318 [prior] Evaluating prior at array([0.99626458])
 2023-07-02 10:24:53,318 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,318 [model] Got input parameters: {'Omega_m': 0.9962645781022594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,318 [classy] Got parameters {'Omega_m': 0.9962645781022594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,318 [classy] Computing new state
 2023-07-02 10:24:53,318 [classy] Setting parameters: {'Omega_m': 0.9962645781022594, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.23978926683354}
 2023-07-02 10:24:53,367 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.54631
 2023-07-02 10:24:53,368 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,368 [model] Posterior to be computed for parameters {'Omega_m': 0.6529173404474666}
 2023-07-02 10:24:53,368 [prior] Evaluating prior at array([0.65291734])
 2023-07-02 10:24:53,369 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,369 [model] Got input parameters: {'Omega_m': 0.6529173404474666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,369 [classy] Got parameters {'Omega_m': 0.6529173404474666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,369 [classy] Computing new state
 2023-07-02 10:24:53,369 [classy] Setting parameters: {'Omega_m': 0.6529173404474666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,416 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.04366058374174}
 2023-07-02 10:24:53,416 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,418 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.69324
 2023-07-02 10:24:53,418 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,418 [model] Posterior to be computed for parameters {'Omega_m': 0.07498858836129024}
 2023-07-02 10:24:53,418 [prior] Evaluating prior at array([0.07498859])
 2023-07-02 10:24:53,419 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:53,419 [model] Posterior to be computed for parameters {'Omega_m': 0.6787494557828322}
 2023-07-02 10:24:53,419 [prior] Evaluating prior at array([0.67874946])
 2023-07-02 10:24:53,419 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,419 [model] Got input parameters: {'Omega_m': 0.6787494557828322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,419 [classy] Got parameters {'Omega_m': 0.6787494557828322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,419 [classy] Computing new state
 2023-07-02 10:24:53,419 [classy] Setting parameters: {'Omega_m': 0.6787494557828322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,465 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.5654292590559}
 2023-07-02 10:24:53,465 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,467 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.11209
 2023-07-02 10:24:53,467 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,467 [model] Posterior to be computed for parameters {'Omega_m': 0.8964698385562446}
 2023-07-02 10:24:53,467 [prior] Evaluating prior at array([0.89646984])
 2023-07-02 10:24:53,467 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,467 [model] Got input parameters: {'Omega_m': 0.8964698385562446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,468 [classy] Got parameters {'Omega_m': 0.8964698385562446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,468 [classy] Computing new state
 2023-07-02 10:24:53,468 [classy] Setting parameters: {'Omega_m': 0.8964698385562446, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,514 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.11590141661479}
 2023-07-02 10:24:53,514 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,516 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.81708
 2023-07-02 10:24:53,516 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,516 [model] Posterior to be computed for parameters {'Omega_m': 0.07842868325733798}
 2023-07-02 10:24:53,516 [prior] Evaluating prior at array([0.07842868])
 2023-07-02 10:24:53,516 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:53,516 [model] Posterior to be computed for parameters {'Omega_m': -0.04992282667118003}
 2023-07-02 10:24:53,516 [prior] Evaluating prior at array([-0.04992283])
 2023-07-02 10:24:53,516 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:53,517 [model] Posterior to be computed for parameters {'Omega_m': 0.4391277894817036}
 2023-07-02 10:24:53,517 [prior] Evaluating prior at array([0.43912779])
 2023-07-02 10:24:53,517 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,517 [model] Got input parameters: {'Omega_m': 0.4391277894817036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,517 [classy] Got parameters {'Omega_m': 0.4391277894817036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,517 [classy] Computing new state
 2023-07-02 10:24:53,517 [classy] Setting parameters: {'Omega_m': 0.4391277894817036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,565 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.28616344845622}
 2023-07-02 10:24:53,565 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,567 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.741882
 2023-07-02 10:24:53,567 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,567 [mcmc] New sample, #439:
   Omega_m:0.439078
 2023-07-02 10:24:53,567 [model] Posterior to be computed for parameters {'Omega_m': 0.10599605075573809}
 2023-07-02 10:24:53,567 [prior] Evaluating prior at array([0.10599605])
 2023-07-02 10:24:53,567 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,567 [model] Got input parameters: {'Omega_m': 0.10599605075573809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,567 [classy] Got parameters {'Omega_m': 0.10599605075573809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,567 [classy] Computing new state
 2023-07-02 10:24:53,567 [classy] Setting parameters: {'Omega_m': 0.10599605075573809, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,615 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.56238438227797}
 2023-07-02 10:24:53,615 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,617 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.062
 2023-07-02 10:24:53,617 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,617 [model] Posterior to be computed for parameters {'Omega_m': 0.48039377902710834}
 2023-07-02 10:24:53,617 [prior] Evaluating prior at array([0.48039378])
 2023-07-02 10:24:53,617 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,617 [model] Got input parameters: {'Omega_m': 0.48039377902710834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,617 [classy] Got parameters {'Omega_m': 0.48039377902710834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,617 [classy] Computing new state
 2023-07-02 10:24:53,617 [classy] Setting parameters: {'Omega_m': 0.48039377902710834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.82758881330835}
 2023-07-02 10:24:53,666 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.20336
 2023-07-02 10:24:53,668 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,668 [mcmc] New sample, #440:
   Omega_m:0.4391278
 2023-07-02 10:24:53,668 [mcmc] Learn + convergence test @ 440 samples accepted.
 2023-07-02 10:24:53,668 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:53,673 [mcmc]  - Acceptance rate: 0.420
 2023-07-02 10:24:53,673 [mcmc]  - Condition number = 1
 2023-07-02 10:24:53,673 [mcmc]  - Eigenvalues = array([0.02193125])
 2023-07-02 10:24:53,673 [mcmc]  - Convergence of means: R-1 = 0.021931 after 352 accepted steps
 2023-07-02 10:24:53,673 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:53,673 [mcmc] array([[0.01224873]])
 2023-07-02 10:24:53,684 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:53,684 [model] Posterior to be computed for parameters {'Omega_m': 0.7840185275272447}
 2023-07-02 10:24:53,684 [prior] Evaluating prior at array([0.78401853])
 2023-07-02 10:24:53,684 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,684 [model] Got input parameters: {'Omega_m': 0.7840185275272447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,684 [classy] Got parameters {'Omega_m': 0.7840185275272447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,684 [classy] Computing new state
 2023-07-02 10:24:53,684 [classy] Setting parameters: {'Omega_m': 0.7840185275272447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,730 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.11307230323}
 2023-07-02 10:24:53,730 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,732 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.87784
 2023-07-02 10:24:53,732 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,732 [model] Posterior to be computed for parameters {'Omega_m': 1.0345929950379507}
 2023-07-02 10:24:53,732 [prior] Evaluating prior at array([1.034593])
 2023-07-02 10:24:53,732 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:53,732 [model] Posterior to be computed for parameters {'Omega_m': 0.5859445836287613}
 2023-07-02 10:24:53,732 [prior] Evaluating prior at array([0.58594458])
 2023-07-02 10:24:53,732 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,732 [model] Got input parameters: {'Omega_m': 0.5859445836287613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,733 [classy] Got parameters {'Omega_m': 0.5859445836287613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,733 [classy] Computing new state
 2023-07-02 10:24:53,733 [classy] Setting parameters: {'Omega_m': 0.5859445836287613, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.18519974739237}
 2023-07-02 10:24:53,780 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.64987
 2023-07-02 10:24:53,782 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,782 [model] Posterior to be computed for parameters {'Omega_m': 0.9266418805082961}
 2023-07-02 10:24:53,782 [prior] Evaluating prior at array([0.92664188])
 2023-07-02 10:24:53,782 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,782 [model] Got input parameters: {'Omega_m': 0.9266418805082961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,782 [classy] Got parameters {'Omega_m': 0.9266418805082961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,782 [classy] Computing new state
 2023-07-02 10:24:53,782 [classy] Setting parameters: {'Omega_m': 0.9266418805082961, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 105.89423552218476}
 2023-07-02 10:24:53,828 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.34028
 2023-07-02 10:24:53,830 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,830 [model] Posterior to be computed for parameters {'Omega_m': -0.06098955566050912}
 2023-07-02 10:24:53,830 [prior] Evaluating prior at array([-0.06098956])
 2023-07-02 10:24:53,830 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:53,830 [model] Posterior to be computed for parameters {'Omega_m': 0.3758760651720021}
 2023-07-02 10:24:53,830 [prior] Evaluating prior at array([0.37587607])
 2023-07-02 10:24:53,831 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,831 [model] Got input parameters: {'Omega_m': 0.3758760651720021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,831 [classy] Got parameters {'Omega_m': 0.3758760651720021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,831 [classy] Computing new state
 2023-07-02 10:24:53,831 [classy] Setting parameters: {'Omega_m': 0.3758760651720021, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.25322182260336}
 2023-07-02 10:24:53,878 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.212546
 2023-07-02 10:24:53,880 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,880 [mcmc] New sample, #441:
   Omega_m:0.4803938
 2023-07-02 10:24:53,880 [model] Posterior to be computed for parameters {'Omega_m': 0.19723526986329767}
 2023-07-02 10:24:53,880 [prior] Evaluating prior at array([0.19723527])
 2023-07-02 10:24:53,880 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,880 [model] Got input parameters: {'Omega_m': 0.19723526986329767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,880 [classy] Got parameters {'Omega_m': 0.19723526986329767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,880 [classy] Computing new state
 2023-07-02 10:24:53,881 [classy] Setting parameters: {'Omega_m': 0.19723526986329767, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.95904617514472}
 2023-07-02 10:24:53,928 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.1273
 2023-07-02 10:24:53,930 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,930 [mcmc] New sample, #442:
   Omega_m:0.3758761
 2023-07-02 10:24:53,930 [model] Posterior to be computed for parameters {'Omega_m': 0.38158935821267803}
 2023-07-02 10:24:53,931 [prior] Evaluating prior at array([0.38158936])
 2023-07-02 10:24:53,931 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,931 [model] Got input parameters: {'Omega_m': 0.38158935821267803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,931 [classy] Got parameters {'Omega_m': 0.38158935821267803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,931 [classy] Computing new state
 2023-07-02 10:24:53,931 [classy] Setting parameters: {'Omega_m': 0.38158935821267803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:53,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.67647702415152}
 2023-07-02 10:24:53,979 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:53,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.249378
 2023-07-02 10:24:53,980 [model] Computed derived parameters: {}
 2023-07-02 10:24:53,980 [mcmc] New sample, #443:
   Omega_m:0.1972353
 2023-07-02 10:24:53,981 [model] Posterior to be computed for parameters {'Omega_m': 0.20808801155648604}
 2023-07-02 10:24:53,981 [prior] Evaluating prior at array([0.20808801])
 2023-07-02 10:24:53,981 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:53,981 [model] Got input parameters: {'Omega_m': 0.20808801155648604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,981 [classy] Got parameters {'Omega_m': 0.20808801155648604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:53,981 [classy] Computing new state
 2023-07-02 10:24:53,981 [classy] Setting parameters: {'Omega_m': 0.20808801155648604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,029 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.09090271294613}
 2023-07-02 10:24:54,029 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,031 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.893721
 2023-07-02 10:24:54,031 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,031 [mcmc] New sample, #444:
   Omega_m:0.3815894
 2023-07-02 10:24:54,031 [model] Posterior to be computed for parameters {'Omega_m': -0.0751473947532677}
 2023-07-02 10:24:54,032 [prior] Evaluating prior at array([-0.07514739])
 2023-07-02 10:24:54,032 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:54,032 [model] Posterior to be computed for parameters {'Omega_m': 0.3932800369841343}
 2023-07-02 10:24:54,032 [prior] Evaluating prior at array([0.39328004])
 2023-07-02 10:24:54,032 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,032 [model] Got input parameters: {'Omega_m': 0.3932800369841343, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,032 [classy] Got parameters {'Omega_m': 0.3932800369841343, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,032 [classy] Computing new state
 2023-07-02 10:24:54,032 [classy] Setting parameters: {'Omega_m': 0.3932800369841343, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.52116867122453}
 2023-07-02 10:24:54,079 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,081 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.332263
 2023-07-02 10:24:54,081 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,081 [mcmc] New sample, #445:
   Omega_m:0.208088
 2023-07-02 10:24:54,081 [model] Posterior to be computed for parameters {'Omega_m': 0.6306143938372174}
 2023-07-02 10:24:54,081 [prior] Evaluating prior at array([0.63061439])
 2023-07-02 10:24:54,082 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,082 [model] Got input parameters: {'Omega_m': 0.6306143938372174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,082 [classy] Got parameters {'Omega_m': 0.6306143938372174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,082 [classy] Computing new state
 2023-07-02 10:24:54,082 [classy] Setting parameters: {'Omega_m': 0.6306143938372174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.37098193971023}
 2023-07-02 10:24:54,128 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,130 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.33819
 2023-07-02 10:24:54,130 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,130 [model] Posterior to be computed for parameters {'Omega_m': 0.4049576307928636}
 2023-07-02 10:24:54,130 [prior] Evaluating prior at array([0.40495763])
 2023-07-02 10:24:54,130 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,130 [model] Got input parameters: {'Omega_m': 0.4049576307928636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,130 [classy] Got parameters {'Omega_m': 0.4049576307928636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,130 [classy] Computing new state
 2023-07-02 10:24:54,130 [classy] Setting parameters: {'Omega_m': 0.4049576307928636, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.39922414455987}
 2023-07-02 10:24:54,178 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,180 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.424474
 2023-07-02 10:24:54,180 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,180 [mcmc] New sample, #446:
   Omega_m:0.39328
 2023-07-02 10:24:54,180 [model] Posterior to be computed for parameters {'Omega_m': -0.107305091829758}
 2023-07-02 10:24:54,180 [prior] Evaluating prior at array([-0.10730509])
 2023-07-02 10:24:54,180 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:54,180 [model] Posterior to be computed for parameters {'Omega_m': 0.556324701194813}
 2023-07-02 10:24:54,180 [prior] Evaluating prior at array([0.5563247])
 2023-07-02 10:24:54,180 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,180 [model] Got input parameters: {'Omega_m': 0.556324701194813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,180 [classy] Got parameters {'Omega_m': 0.556324701194813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,180 [classy] Computing new state
 2023-07-02 10:24:54,180 [classy] Setting parameters: {'Omega_m': 0.556324701194813, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.17770068983356}
 2023-07-02 10:24:54,228 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.21424
 2023-07-02 10:24:54,230 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,230 [model] Posterior to be computed for parameters {'Omega_m': 0.06717386186167223}
 2023-07-02 10:24:54,230 [prior] Evaluating prior at array([0.06717386])
 2023-07-02 10:24:54,230 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:54,230 [model] Posterior to be computed for parameters {'Omega_m': 0.48227738671100506}
 2023-07-02 10:24:54,230 [prior] Evaluating prior at array([0.48227739])
 2023-07-02 10:24:54,230 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,230 [model] Got input parameters: {'Omega_m': 0.48227738671100506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,230 [classy] Got parameters {'Omega_m': 0.48227738671100506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,230 [classy] Computing new state
 2023-07-02 10:24:54,230 [classy] Setting parameters: {'Omega_m': 0.48227738671100506, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,278 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.67683037164943}
 2023-07-02 10:24:54,278 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,280 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.22614
 2023-07-02 10:24:54,280 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,280 [model] Posterior to be computed for parameters {'Omega_m': 0.39716705814934616}
 2023-07-02 10:24:54,280 [prior] Evaluating prior at array([0.39716706])
 2023-07-02 10:24:54,280 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,280 [model] Got input parameters: {'Omega_m': 0.39716705814934616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,280 [classy] Got parameters {'Omega_m': 0.39716705814934616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,280 [classy] Computing new state
 2023-07-02 10:24:54,280 [classy] Setting parameters: {'Omega_m': 0.39716705814934616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.14425133847956}
 2023-07-02 10:24:54,328 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.361945
 2023-07-02 10:24:54,330 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,330 [mcmc] New sample, #447:
   Omega_m:0.4049576
 2023-07-02 10:24:54,330 [model] Posterior to be computed for parameters {'Omega_m': 0.40030809508707715}
 2023-07-02 10:24:54,330 [prior] Evaluating prior at array([0.4003081])
 2023-07-02 10:24:54,330 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,330 [model] Got input parameters: {'Omega_m': 0.40030809508707715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,330 [classy] Got parameters {'Omega_m': 0.40030809508707715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,330 [classy] Computing new state
 2023-07-02 10:24:54,331 [classy] Setting parameters: {'Omega_m': 0.40030809508707715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,379 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.84221319324757}
 2023-07-02 10:24:54,379 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,381 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.386676
 2023-07-02 10:24:54,381 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,381 [mcmc] New sample, #448:
   Omega_m:0.3971671
 2023-07-02 10:24:54,381 [model] Posterior to be computed for parameters {'Omega_m': 0.2947378661116574}
 2023-07-02 10:24:54,381 [prior] Evaluating prior at array([0.29473787])
 2023-07-02 10:24:54,381 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,381 [model] Got input parameters: {'Omega_m': 0.2947378661116574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,381 [classy] Got parameters {'Omega_m': 0.2947378661116574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,381 [classy] Computing new state
 2023-07-02 10:24:54,381 [classy] Setting parameters: {'Omega_m': 0.2947378661116574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45092573921787}
 2023-07-02 10:24:54,429 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0204013
 2023-07-02 10:24:54,431 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,431 [mcmc] New sample, #449:
   Omega_m:0.4003081
 2023-07-02 10:24:54,431 [model] Posterior to be computed for parameters {'Omega_m': -0.004448947850334728}
 2023-07-02 10:24:54,431 [prior] Evaluating prior at array([-0.00444895])
 2023-07-02 10:24:54,431 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:54,431 [model] Posterior to be computed for parameters {'Omega_m': 0.3168329439016637}
 2023-07-02 10:24:54,431 [prior] Evaluating prior at array([0.31683294])
 2023-07-02 10:24:54,431 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,431 [model] Got input parameters: {'Omega_m': 0.3168329439016637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,431 [classy] Got parameters {'Omega_m': 0.3168329439016637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,431 [classy] Computing new state
 2023-07-02 10:24:54,432 [classy] Setting parameters: {'Omega_m': 0.3168329439016637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7400401937837}
 2023-07-02 10:24:54,479 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00134972
 2023-07-02 10:24:54,481 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,481 [mcmc] New sample, #450:
   Omega_m:0.2947379
 2023-07-02 10:24:54,481 [model] Posterior to be computed for parameters {'Omega_m': 0.5641356858061696}
 2023-07-02 10:24:54,481 [prior] Evaluating prior at array([0.56413569])
 2023-07-02 10:24:54,481 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,481 [model] Got input parameters: {'Omega_m': 0.5641356858061696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,481 [classy] Got parameters {'Omega_m': 0.5641356858061696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,481 [classy] Computing new state
 2023-07-02 10:24:54,481 [classy] Setting parameters: {'Omega_m': 0.5641356858061696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.64177746891563}
 2023-07-02 10:24:54,529 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,531 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.32727
 2023-07-02 10:24:54,531 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,531 [model] Posterior to be computed for parameters {'Omega_m': 0.2165658239373025}
 2023-07-02 10:24:54,531 [prior] Evaluating prior at array([0.21656582])
 2023-07-02 10:24:54,531 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,531 [model] Got input parameters: {'Omega_m': 0.2165658239373025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,531 [classy] Got parameters {'Omega_m': 0.2165658239373025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,531 [classy] Computing new state
 2023-07-02 10:24:54,531 [classy] Setting parameters: {'Omega_m': 0.2165658239373025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,578 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.68317089454933}
 2023-07-02 10:24:54,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.734956
 2023-07-02 10:24:54,580 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,580 [model] Posterior to be computed for parameters {'Omega_m': 0.5191713834429545}
 2023-07-02 10:24:54,581 [prior] Evaluating prior at array([0.51917138])
 2023-07-02 10:24:54,581 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,581 [model] Got input parameters: {'Omega_m': 0.5191713834429545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,581 [classy] Got parameters {'Omega_m': 0.5191713834429545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,581 [classy] Computing new state
 2023-07-02 10:24:54,581 [classy] Setting parameters: {'Omega_m': 0.5191713834429545, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.83733235059971}
 2023-07-02 10:24:54,628 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.69775
 2023-07-02 10:24:54,630 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,630 [mcmc] New sample, #451:
   Omega_m:0.3168329
 2023-07-02 10:24:54,630 [model] Posterior to be computed for parameters {'Omega_m': 0.48376521713630505}
 2023-07-02 10:24:54,630 [prior] Evaluating prior at array([0.48376522])
 2023-07-02 10:24:54,630 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,630 [model] Got input parameters: {'Omega_m': 0.48376521713630505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,631 [classy] Got parameters {'Omega_m': 0.48376521713630505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,631 [classy] Computing new state
 2023-07-02 10:24:54,631 [classy] Setting parameters: {'Omega_m': 0.48376521713630505, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.55816270696}
 2023-07-02 10:24:54,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.24423
 2023-07-02 10:24:54,681 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,681 [mcmc] New sample, #452:
   Omega_m:0.5191714
 2023-07-02 10:24:54,681 [model] Posterior to be computed for parameters {'Omega_m': 0.8233428947211128}
 2023-07-02 10:24:54,681 [prior] Evaluating prior at array([0.82334289])
 2023-07-02 10:24:54,681 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,681 [model] Got input parameters: {'Omega_m': 0.8233428947211128, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,681 [classy] Got parameters {'Omega_m': 0.8233428947211128, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,681 [classy] Computing new state
 2023-07-02 10:24:54,681 [classy] Setting parameters: {'Omega_m': 0.8233428947211128, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.27952478175851}
 2023-07-02 10:24:54,727 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,729 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.55261
 2023-07-02 10:24:54,729 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,729 [model] Posterior to be computed for parameters {'Omega_m': 0.7153165323043591}
 2023-07-02 10:24:54,729 [prior] Evaluating prior at array([0.71531653])
 2023-07-02 10:24:54,729 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,729 [model] Got input parameters: {'Omega_m': 0.7153165323043591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,729 [classy] Got parameters {'Omega_m': 0.7153165323043591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,729 [classy] Computing new state
 2023-07-02 10:24:54,729 [classy] Setting parameters: {'Omega_m': 0.7153165323043591, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.57316027019607}
 2023-07-02 10:24:54,777 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,778 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.71643
 2023-07-02 10:24:54,778 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,779 [model] Posterior to be computed for parameters {'Omega_m': 0.7668818066220325}
 2023-07-02 10:24:54,779 [prior] Evaluating prior at array([0.76688181])
 2023-07-02 10:24:54,779 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,779 [model] Got input parameters: {'Omega_m': 0.7668818066220325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,779 [classy] Got parameters {'Omega_m': 0.7668818066220325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,779 [classy] Computing new state
 2023-07-02 10:24:54,779 [classy] Setting parameters: {'Omega_m': 0.7668818066220325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.94412389301489}
 2023-07-02 10:24:54,824 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.58569
 2023-07-02 10:24:54,827 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,827 [model] Posterior to be computed for parameters {'Omega_m': 0.6351085290230681}
 2023-07-02 10:24:54,827 [prior] Evaluating prior at array([0.63510853])
 2023-07-02 10:24:54,827 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,827 [model] Got input parameters: {'Omega_m': 0.6351085290230681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,827 [classy] Got parameters {'Omega_m': 0.6351085290230681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,827 [classy] Computing new state
 2023-07-02 10:24:54,827 [classy] Setting parameters: {'Omega_m': 0.6351085290230681, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.09955677665717}
 2023-07-02 10:24:54,875 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,877 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.40919
 2023-07-02 10:24:54,877 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,877 [model] Posterior to be computed for parameters {'Omega_m': 0.6580998273455653}
 2023-07-02 10:24:54,877 [prior] Evaluating prior at array([0.65809983])
 2023-07-02 10:24:54,877 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,877 [model] Got input parameters: {'Omega_m': 0.6580998273455653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,878 [classy] Got parameters {'Omega_m': 0.6580998273455653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,878 [classy] Computing new state
 2023-07-02 10:24:54,878 [classy] Setting parameters: {'Omega_m': 0.6580998273455653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.74213798958785}
 2023-07-02 10:24:54,924 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,926 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.77665
 2023-07-02 10:24:54,926 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,926 [model] Posterior to be computed for parameters {'Omega_m': 0.3848386847953992}
 2023-07-02 10:24:54,927 [prior] Evaluating prior at array([0.38483868])
 2023-07-02 10:24:54,927 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,927 [model] Got input parameters: {'Omega_m': 0.3848386847953992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,927 [classy] Got parameters {'Omega_m': 0.3848386847953992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,927 [classy] Computing new state
 2023-07-02 10:24:54,927 [classy] Setting parameters: {'Omega_m': 0.3848386847953992, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:54,973 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.35205745348682}
 2023-07-02 10:24:54,973 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:54,975 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.271424
 2023-07-02 10:24:54,975 [model] Computed derived parameters: {}
 2023-07-02 10:24:54,975 [mcmc] New sample, #453:
   Omega_m:0.4837652
 2023-07-02 10:24:54,975 [model] Posterior to be computed for parameters {'Omega_m': 0.2596717759058505}
 2023-07-02 10:24:54,975 [prior] Evaluating prior at array([0.25967178])
 2023-07-02 10:24:54,975 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:54,975 [model] Got input parameters: {'Omega_m': 0.2596717759058505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,975 [classy] Got parameters {'Omega_m': 0.2596717759058505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:54,975 [classy] Computing new state
 2023-07-02 10:24:54,975 [classy] Setting parameters: {'Omega_m': 0.2596717759058505, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1383923018722}
 2023-07-02 10:24:55,023 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,025 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.19666
 2023-07-02 10:24:55,025 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,025 [mcmc] New sample, #454:
   Omega_m:0.3848387
 2023-07-02 10:24:55,025 [model] Posterior to be computed for parameters {'Omega_m': 0.1198914501626149}
 2023-07-02 10:24:55,025 [prior] Evaluating prior at array([0.11989145])
 2023-07-02 10:24:55,025 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,026 [model] Got input parameters: {'Omega_m': 0.1198914501626149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,026 [classy] Got parameters {'Omega_m': 0.1198914501626149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,026 [classy] Computing new state
 2023-07-02 10:24:55,026 [classy] Setting parameters: {'Omega_m': 0.1198914501626149, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 180.01014318615356}
 2023-07-02 10:24:55,074 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,076 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.15726
 2023-07-02 10:24:55,076 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,076 [mcmc] New sample, #455:
   Omega_m:0.2596718
 2023-07-02 10:24:55,076 [model] Posterior to be computed for parameters {'Omega_m': 0.31047758779691703}
 2023-07-02 10:24:55,076 [prior] Evaluating prior at array([0.31047759])
 2023-07-02 10:24:55,077 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,077 [model] Got input parameters: {'Omega_m': 0.31047758779691703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,077 [classy] Got parameters {'Omega_m': 0.31047758779691703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,077 [classy] Computing new state
 2023-07-02 10:24:55,077 [classy] Setting parameters: {'Omega_m': 0.31047758779691703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5022462286668}
 2023-07-02 10:24:55,126 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000450484
 2023-07-02 10:24:55,128 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,128 [mcmc] New sample, #456:
   Omega_m:0.1198915
 2023-07-02 10:24:55,128 [model] Posterior to be computed for parameters {'Omega_m': 0.2918354009381155}
 2023-07-02 10:24:55,128 [prior] Evaluating prior at array([0.2918354])
 2023-07-02 10:24:55,129 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,129 [model] Got input parameters: {'Omega_m': 0.2918354009381155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,129 [classy] Got parameters {'Omega_m': 0.2918354009381155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,129 [classy] Computing new state
 2023-07-02 10:24:55,129 [classy] Setting parameters: {'Omega_m': 0.2918354009381155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.8201830093982}
 2023-07-02 10:24:55,176 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,178 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0277547
 2023-07-02 10:24:55,178 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,178 [mcmc] New sample, #457:
   Omega_m:0.3104776
 2023-07-02 10:24:55,178 [model] Posterior to be computed for parameters {'Omega_m': 0.6171402613140168}
 2023-07-02 10:24:55,178 [prior] Evaluating prior at array([0.61714026])
 2023-07-02 10:24:55,178 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,178 [model] Got input parameters: {'Omega_m': 0.6171402613140168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,179 [classy] Got parameters {'Omega_m': 0.6171402613140168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,179 [classy] Computing new state
 2023-07-02 10:24:55,179 [classy] Setting parameters: {'Omega_m': 0.6171402613140168, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,227 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.19719842012466}
 2023-07-02 10:24:55,227 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,229 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.1271
 2023-07-02 10:24:55,229 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,230 [model] Posterior to be computed for parameters {'Omega_m': -0.05874593285529228}
 2023-07-02 10:24:55,230 [prior] Evaluating prior at array([-0.05874593])
 2023-07-02 10:24:55,230 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,230 [model] Posterior to be computed for parameters {'Omega_m': 0.13561171842788733}
 2023-07-02 10:24:55,230 [prior] Evaluating prior at array([0.13561172])
 2023-07-02 10:24:55,230 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,230 [model] Got input parameters: {'Omega_m': 0.13561171842788733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,230 [classy] Got parameters {'Omega_m': 0.13561171842788733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,230 [classy] Computing new state
 2023-07-02 10:24:55,231 [classy] Setting parameters: {'Omega_m': 0.13561171842788733, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,278 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.28039883086342}
 2023-07-02 10:24:55,278 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,280 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.29571
 2023-07-02 10:24:55,281 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,281 [model] Posterior to be computed for parameters {'Omega_m': -0.050639235292443574}
 2023-07-02 10:24:55,281 [prior] Evaluating prior at array([-0.05063924])
 2023-07-02 10:24:55,281 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,281 [model] Posterior to be computed for parameters {'Omega_m': 1.2232412840423736}
 2023-07-02 10:24:55,281 [prior] Evaluating prior at array([1.22324128])
 2023-07-02 10:24:55,281 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,281 [model] Posterior to be computed for parameters {'Omega_m': 0.6018682596413101}
 2023-07-02 10:24:55,281 [prior] Evaluating prior at array([0.60186826])
 2023-07-02 10:24:55,281 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,281 [model] Got input parameters: {'Omega_m': 0.6018682596413101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,281 [classy] Got parameters {'Omega_m': 0.6018682596413101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,282 [classy] Computing new state
 2023-07-02 10:24:55,282 [classy] Setting parameters: {'Omega_m': 0.6018682596413101, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,331 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.15693789085411}
 2023-07-02 10:24:55,331 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,333 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.89134
 2023-07-02 10:24:55,333 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,333 [model] Posterior to be computed for parameters {'Omega_m': 0.030149267931499135}
 2023-07-02 10:24:55,333 [prior] Evaluating prior at array([0.03014927])
 2023-07-02 10:24:55,333 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,333 [model] Posterior to be computed for parameters {'Omega_m': -0.040187964325526626}
 2023-07-02 10:24:55,333 [prior] Evaluating prior at array([-0.04018796])
 2023-07-02 10:24:55,333 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,333 [model] Posterior to be computed for parameters {'Omega_m': 0.5284874582816548}
 2023-07-02 10:24:55,333 [prior] Evaluating prior at array([0.52848746])
 2023-07-02 10:24:55,333 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,333 [model] Got input parameters: {'Omega_m': 0.5284874582816548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,333 [classy] Got parameters {'Omega_m': 0.5284874582816548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,334 [classy] Computing new state
 2023-07-02 10:24:55,334 [classy] Setting parameters: {'Omega_m': 0.5284874582816548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,388 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.15256699508025}
 2023-07-02 10:24:55,388 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,390 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.82374
 2023-07-02 10:24:55,390 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,390 [model] Posterior to be computed for parameters {'Omega_m': 0.40402916126575134}
 2023-07-02 10:24:55,390 [prior] Evaluating prior at array([0.40402916])
 2023-07-02 10:24:55,390 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,390 [model] Got input parameters: {'Omega_m': 0.40402916126575134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,390 [classy] Got parameters {'Omega_m': 0.40402916126575134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,390 [classy] Computing new state
 2023-07-02 10:24:55,390 [classy] Setting parameters: {'Omega_m': 0.40402916126575134, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.48729700717303}
 2023-07-02 10:24:55,440 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,442 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.416814
 2023-07-02 10:24:55,442 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,442 [mcmc] New sample, #458:
   Omega_m:0.2918354
 2023-07-02 10:24:55,442 [model] Posterior to be computed for parameters {'Omega_m': -0.7836151030940739}
 2023-07-02 10:24:55,442 [prior] Evaluating prior at array([-0.7836151])
 2023-07-02 10:24:55,442 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,442 [model] Posterior to be computed for parameters {'Omega_m': 0.5372363393726617}
 2023-07-02 10:24:55,442 [prior] Evaluating prior at array([0.53723634])
 2023-07-02 10:24:55,442 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,442 [model] Got input parameters: {'Omega_m': 0.5372363393726617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,442 [classy] Got parameters {'Omega_m': 0.5372363393726617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,443 [classy] Computing new state
 2023-07-02 10:24:55,443 [classy] Setting parameters: {'Omega_m': 0.5372363393726617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,493 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.52064485926047}
 2023-07-02 10:24:55,493 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,495 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.94427
 2023-07-02 10:24:55,495 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,495 [model] Posterior to be computed for parameters {'Omega_m': 1.1821444200179239}
 2023-07-02 10:24:55,495 [prior] Evaluating prior at array([1.18214442])
 2023-07-02 10:24:55,495 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,495 [model] Posterior to be computed for parameters {'Omega_m': 0.5011826557401233}
 2023-07-02 10:24:55,495 [prior] Evaluating prior at array([0.50118266])
 2023-07-02 10:24:55,495 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,495 [model] Got input parameters: {'Omega_m': 0.5011826557401233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,496 [classy] Got parameters {'Omega_m': 0.5011826557401233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,496 [classy] Computing new state
 2023-07-02 10:24:55,496 [classy] Setting parameters: {'Omega_m': 0.5011826557401233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.19550834761623}
 2023-07-02 10:24:55,546 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.46204
 2023-07-02 10:24:55,548 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,548 [mcmc] New sample, #459:
   Omega_m:0.4040292
 2023-07-02 10:24:55,548 [model] Posterior to be computed for parameters {'Omega_m': 0.4658319347356983}
 2023-07-02 10:24:55,548 [prior] Evaluating prior at array([0.46583193])
 2023-07-02 10:24:55,548 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,548 [model] Got input parameters: {'Omega_m': 0.4658319347356983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,548 [classy] Got parameters {'Omega_m': 0.4658319347356983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,548 [classy] Computing new state
 2023-07-02 10:24:55,548 [classy] Setting parameters: {'Omega_m': 0.4658319347356983, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,597 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.0133456158857}
 2023-07-02 10:24:55,597 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,599 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.032
 2023-07-02 10:24:55,599 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,599 [mcmc] New sample, #460:
   Omega_m:0.5011827
 2023-07-02 10:24:55,599 [model] Posterior to be computed for parameters {'Omega_m': 0.9738955805389513}
 2023-07-02 10:24:55,599 [prior] Evaluating prior at array([0.97389558])
 2023-07-02 10:24:55,600 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,600 [model] Got input parameters: {'Omega_m': 0.9738955805389513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,600 [classy] Got parameters {'Omega_m': 0.9738955805389513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,600 [classy] Computing new state
 2023-07-02 10:24:55,600 [classy] Setting parameters: {'Omega_m': 0.9738955805389513, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,649 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.06892453909201}
 2023-07-02 10:24:55,649 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,650 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.15927
 2023-07-02 10:24:55,651 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,651 [model] Posterior to be computed for parameters {'Omega_m': 0.48956667763627115}
 2023-07-02 10:24:55,651 [prior] Evaluating prior at array([0.48956668])
 2023-07-02 10:24:55,651 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,651 [model] Got input parameters: {'Omega_m': 0.48956667763627115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,651 [classy] Got parameters {'Omega_m': 0.48956667763627115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,651 [classy] Computing new state
 2023-07-02 10:24:55,651 [classy] Setting parameters: {'Omega_m': 0.48956667763627115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.0988874024501}
 2023-07-02 10:24:55,700 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.31557
 2023-07-02 10:24:55,702 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,702 [mcmc] New sample, #461:
   Omega_m:0.4658319
 2023-07-02 10:24:55,702 [model] Posterior to be computed for parameters {'Omega_m': 0.24240954412105067}
 2023-07-02 10:24:55,702 [prior] Evaluating prior at array([0.24240954])
 2023-07-02 10:24:55,703 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,703 [model] Got input parameters: {'Omega_m': 0.24240954412105067, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,703 [classy] Got parameters {'Omega_m': 0.24240954412105067, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,703 [classy] Computing new state
 2023-07-02 10:24:55,703 [classy] Setting parameters: {'Omega_m': 0.24240954412105067, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.64489359796235}
 2023-07-02 10:24:55,752 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.363376
 2023-07-02 10:24:55,754 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,754 [mcmc] New sample, #462:
   Omega_m:0.4895667
 2023-07-02 10:24:55,754 [model] Posterior to be computed for parameters {'Omega_m': 0.00033519678364549166}
 2023-07-02 10:24:55,754 [prior] Evaluating prior at array([0.0003352])
 2023-07-02 10:24:55,754 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:55,754 [model] Posterior to be computed for parameters {'Omega_m': 0.8924294166640759}
 2023-07-02 10:24:55,754 [prior] Evaluating prior at array([0.89242942])
 2023-07-02 10:24:55,754 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,754 [model] Got input parameters: {'Omega_m': 0.8924294166640759, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,754 [classy] Got parameters {'Omega_m': 0.8924294166640759, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,754 [classy] Computing new state
 2023-07-02 10:24:55,754 [classy] Setting parameters: {'Omega_m': 0.8924294166640759, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.28301668755911}
 2023-07-02 10:24:55,803 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,805 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.74704
 2023-07-02 10:24:55,805 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,805 [model] Posterior to be computed for parameters {'Omega_m': 0.6100593221132335}
 2023-07-02 10:24:55,805 [prior] Evaluating prior at array([0.61005932])
 2023-07-02 10:24:55,805 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,805 [model] Got input parameters: {'Omega_m': 0.6100593221132335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,805 [classy] Got parameters {'Omega_m': 0.6100593221132335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,805 [classy] Computing new state
 2023-07-02 10:24:55,805 [classy] Setting parameters: {'Omega_m': 0.6100593221132335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,854 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.63904294709232}
 2023-07-02 10:24:55,855 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.01731
 2023-07-02 10:24:55,857 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,857 [mcmc] New sample, #463:
   Omega_m:0.2424095
 2023-07-02 10:24:55,857 [model] Posterior to be computed for parameters {'Omega_m': 0.39830429038834736}
 2023-07-02 10:24:55,857 [prior] Evaluating prior at array([0.39830429])
 2023-07-02 10:24:55,857 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,857 [model] Got input parameters: {'Omega_m': 0.39830429038834736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,857 [classy] Got parameters {'Omega_m': 0.39830429038834736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,857 [classy] Computing new state
 2023-07-02 10:24:55,857 [classy] Setting parameters: {'Omega_m': 0.39830429038834736, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.0346365040614}
 2023-07-02 10:24:55,906 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,908 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.370823
 2023-07-02 10:24:55,908 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,908 [mcmc] New sample, #464:
   Omega_m:0.6100593
 2023-07-02 10:24:55,908 [model] Posterior to be computed for parameters {'Omega_m': 0.11964120511788973}
 2023-07-02 10:24:55,908 [prior] Evaluating prior at array([0.11964121])
 2023-07-02 10:24:55,908 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,908 [model] Got input parameters: {'Omega_m': 0.11964120511788973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,908 [classy] Got parameters {'Omega_m': 0.11964120511788973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,908 [classy] Computing new state
 2023-07-02 10:24:55,908 [classy] Setting parameters: {'Omega_m': 0.11964120511788973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:55,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 180.0718942490337}
 2023-07-02 10:24:55,956 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:55,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.17229
 2023-07-02 10:24:55,958 [model] Computed derived parameters: {}
 2023-07-02 10:24:55,958 [model] Posterior to be computed for parameters {'Omega_m': 0.1764226137087952}
 2023-07-02 10:24:55,958 [prior] Evaluating prior at array([0.17642261])
 2023-07-02 10:24:55,958 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:55,958 [model] Got input parameters: {'Omega_m': 0.1764226137087952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,958 [classy] Got parameters {'Omega_m': 0.1764226137087952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:55,958 [classy] Computing new state
 2023-07-02 10:24:55,958 [classy] Setting parameters: {'Omega_m': 0.1764226137087952, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.76908658113405}
 2023-07-02 10:24:56,007 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,008 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.68311
 2023-07-02 10:24:56,008 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,009 [mcmc] New sample, #465:
   Omega_m:0.3983043
 2023-07-02 10:24:56,009 [model] Posterior to be computed for parameters {'Omega_m': 0.149367286287286}
 2023-07-02 10:24:56,009 [prior] Evaluating prior at array([0.14936729])
 2023-07-02 10:24:56,009 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,009 [model] Got input parameters: {'Omega_m': 0.149367286287286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,009 [classy] Got parameters {'Omega_m': 0.149367286287286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,009 [classy] Computing new state
 2023-07-02 10:24:56,009 [classy] Setting parameters: {'Omega_m': 0.149367286287286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,058 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.23786911371818}
 2023-07-02 10:24:56,059 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,060 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.6618
 2023-07-02 10:24:56,060 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,060 [mcmc] New sample, #466:
   Omega_m:0.1764226
 2023-07-02 10:24:56,061 [model] Posterior to be computed for parameters {'Omega_m': -0.16895233755754288}
 2023-07-02 10:24:56,061 [prior] Evaluating prior at array([-0.16895234])
 2023-07-02 10:24:56,061 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,061 [model] Posterior to be computed for parameters {'Omega_m': 0.1934104067147679}
 2023-07-02 10:24:56,061 [prior] Evaluating prior at array([0.19341041])
 2023-07-02 10:24:56,061 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,061 [model] Got input parameters: {'Omega_m': 0.1934104067147679, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,061 [classy] Got parameters {'Omega_m': 0.1934104067147679, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,061 [classy] Computing new state
 2023-07-02 10:24:56,061 [classy] Setting parameters: {'Omega_m': 0.1934104067147679, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.63606040667446}
 2023-07-02 10:24:56,109 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.21833
 2023-07-02 10:24:56,111 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,111 [mcmc] New sample, #467:
   Omega_m:0.1493673
 2023-07-02 10:24:56,111 [model] Posterior to be computed for parameters {'Omega_m': 0.08160074926509314}
 2023-07-02 10:24:56,111 [prior] Evaluating prior at array([0.08160075])
 2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,112 [model] Posterior to be computed for parameters {'Omega_m': -0.16623112981685167}
 2023-07-02 10:24:56,112 [prior] Evaluating prior at array([-0.16623113])
 2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,112 [model] Posterior to be computed for parameters {'Omega_m': -0.08822334226108064}
 2023-07-02 10:24:56,112 [prior] Evaluating prior at array([-0.08822334])
 2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,112 [model] Posterior to be computed for parameters {'Omega_m': 0.27196797214811486}
 2023-07-02 10:24:56,112 [prior] Evaluating prior at array([0.27196797])
 2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,112 [model] Got input parameters: {'Omega_m': 0.27196797214811486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,112 [classy] Got parameters {'Omega_m': 0.27196797214811486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,112 [classy] Computing new state
 2023-07-02 10:24:56,112 [classy] Setting parameters: {'Omega_m': 0.27196797214811486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.43643262126605}
 2023-07-02 10:24:56,161 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,162 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.112002
 2023-07-02 10:24:56,162 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,162 [mcmc] New sample, #468:
   Omega_m:0.1934104
 2023-07-02 10:24:56,163 [model] Posterior to be computed for parameters {'Omega_m': 0.23969080033112217}
 2023-07-02 10:24:56,163 [prior] Evaluating prior at array([0.2396908])
 2023-07-02 10:24:56,163 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,163 [model] Got input parameters: {'Omega_m': 0.23969080033112217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,163 [classy] Got parameters {'Omega_m': 0.23969080033112217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,163 [classy] Computing new state
 2023-07-02 10:24:56,163 [classy] Setting parameters: {'Omega_m': 0.23969080033112217, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,213 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.05294502371925}
 2023-07-02 10:24:56,213 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,215 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.395197
 2023-07-02 10:24:56,215 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,215 [mcmc] New sample, #469:
   Omega_m:0.271968
 2023-07-02 10:24:56,215 [model] Posterior to be computed for parameters {'Omega_m': 0.20171543743059936}
 2023-07-02 10:24:56,215 [prior] Evaluating prior at array([0.20171544])
 2023-07-02 10:24:56,215 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,215 [model] Got input parameters: {'Omega_m': 0.20171543743059936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,215 [classy] Got parameters {'Omega_m': 0.20171543743059936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,215 [classy] Computing new state
 2023-07-02 10:24:56,215 [classy] Setting parameters: {'Omega_m': 0.20171543743059936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.17859970336679}
 2023-07-02 10:24:56,266 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.02657
 2023-07-02 10:24:56,268 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,268 [mcmc] New sample, #470:
   Omega_m:0.2396908
 2023-07-02 10:24:56,268 [model] Posterior to be computed for parameters {'Omega_m': 0.0033737735880343123}
 2023-07-02 10:24:56,268 [prior] Evaluating prior at array([0.00337377])
 2023-07-02 10:24:56,268 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3658812234313563}
 2023-07-02 10:24:56,268 [prior] Evaluating prior at array([0.36588122])
 2023-07-02 10:24:56,269 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,269 [model] Got input parameters: {'Omega_m': 0.3658812234313563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,269 [classy] Got parameters {'Omega_m': 0.3658812234313563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,269 [classy] Computing new state
 2023-07-02 10:24:56,269 [classy] Setting parameters: {'Omega_m': 0.3658812234313563, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,318 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.2822633703795}
 2023-07-02 10:24:56,318 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,320 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.15427
 2023-07-02 10:24:56,320 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,320 [mcmc] New sample, #471:
   Omega_m:0.2017154
 2023-07-02 10:24:56,320 [model] Posterior to be computed for parameters {'Omega_m': 0.4975570278610173}
 2023-07-02 10:24:56,320 [prior] Evaluating prior at array([0.49755703])
 2023-07-02 10:24:56,320 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,321 [model] Got input parameters: {'Omega_m': 0.4975570278610173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,321 [classy] Got parameters {'Omega_m': 0.4975570278610173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,321 [classy] Computing new state
 2023-07-02 10:24:56,321 [classy] Setting parameters: {'Omega_m': 0.4975570278610173, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.47519381403762}
 2023-07-02 10:24:56,371 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,373 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.41581
 2023-07-02 10:24:56,373 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,373 [model] Posterior to be computed for parameters {'Omega_m': 0.36689318576364804}
 2023-07-02 10:24:56,373 [prior] Evaluating prior at array([0.36689319])
 2023-07-02 10:24:56,373 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,373 [model] Got input parameters: {'Omega_m': 0.36689318576364804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,373 [classy] Got parameters {'Omega_m': 0.36689318576364804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,373 [classy] Computing new state
 2023-07-02 10:24:56,374 [classy] Setting parameters: {'Omega_m': 0.36689318576364804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,420 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.1768942031325}
 2023-07-02 10:24:56,420 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,422 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.1598
 2023-07-02 10:24:56,422 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,423 [mcmc] New sample, #472:
   Omega_m:0.3658812
 2023-07-02 10:24:56,423 [model] Posterior to be computed for parameters {'Omega_m': 0.5532205457305936}
 2023-07-02 10:24:56,423 [prior] Evaluating prior at array([0.55322055])
 2023-07-02 10:24:56,423 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,423 [model] Got input parameters: {'Omega_m': 0.5532205457305936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,423 [classy] Got parameters {'Omega_m': 0.5532205457305936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,423 [classy] Computing new state
 2023-07-02 10:24:56,423 [classy] Setting parameters: {'Omega_m': 0.5532205457305936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.39283261886278}
 2023-07-02 10:24:56,472 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,474 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.16973
 2023-07-02 10:24:56,474 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,474 [model] Posterior to be computed for parameters {'Omega_m': 0.6258599191147033}
 2023-07-02 10:24:56,474 [prior] Evaluating prior at array([0.62585992])
 2023-07-02 10:24:56,474 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,474 [model] Got input parameters: {'Omega_m': 0.6258599191147033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,474 [classy] Got parameters {'Omega_m': 0.6258599191147033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,474 [classy] Computing new state
 2023-07-02 10:24:56,474 [classy] Setting parameters: {'Omega_m': 0.6258599191147033, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.66035597168865}
 2023-07-02 10:24:56,520 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.26341
 2023-07-02 10:24:56,521 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,522 [model] Posterior to be computed for parameters {'Omega_m': 0.5883179222338727}
 2023-07-02 10:24:56,522 [prior] Evaluating prior at array([0.58831792])
 2023-07-02 10:24:56,522 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,522 [model] Got input parameters: {'Omega_m': 0.5883179222338727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,522 [classy] Got parameters {'Omega_m': 0.5883179222338727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,522 [classy] Computing new state
 2023-07-02 10:24:56,522 [classy] Setting parameters: {'Omega_m': 0.5883179222338727, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,572 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.03011159903112}
 2023-07-02 10:24:56,572 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,573 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.68555
 2023-07-02 10:24:56,573 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,574 [model] Posterior to be computed for parameters {'Omega_m': 0.007121882756645437}
 2023-07-02 10:24:56,574 [prior] Evaluating prior at array([0.00712188])
 2023-07-02 10:24:56,574 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,574 [model] Posterior to be computed for parameters {'Omega_m': 0.3224310114139725}
 2023-07-02 10:24:56,574 [prior] Evaluating prior at array([0.32243101])
 2023-07-02 10:24:56,574 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,574 [model] Got input parameters: {'Omega_m': 0.3224310114139725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,574 [classy] Got parameters {'Omega_m': 0.3224310114139725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,574 [classy] Computing new state
 2023-07-02 10:24:56,574 [classy] Setting parameters: {'Omega_m': 0.3224310114139725, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.079882795819}
 2023-07-02 10:24:56,621 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,622 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00612228
 2023-07-02 10:24:56,622 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,622 [mcmc] New sample, #473:
   Omega_m:0.3668932
 2023-07-02 10:24:56,622 [model] Posterior to be computed for parameters {'Omega_m': 0.33198566070181174}
 2023-07-02 10:24:56,622 [prior] Evaluating prior at array([0.33198566])
 2023-07-02 10:24:56,623 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,623 [model] Got input parameters: {'Omega_m': 0.33198566070181174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,623 [classy] Got parameters {'Omega_m': 0.33198566070181174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,623 [classy] Computing new state
 2023-07-02 10:24:56,623 [classy] Setting parameters: {'Omega_m': 0.33198566070181174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.97648727122817}
 2023-07-02 10:24:56,673 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,674 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0224385
 2023-07-02 10:24:56,675 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,675 [mcmc] New sample, #474:
   Omega_m:0.322431
 2023-07-02 10:24:56,675 [model] Posterior to be computed for parameters {'Omega_m': 0.60359376854119}
 2023-07-02 10:24:56,675 [prior] Evaluating prior at array([0.60359377])
 2023-07-02 10:24:56,675 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,675 [model] Got input parameters: {'Omega_m': 0.60359376854119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,675 [classy] Got parameters {'Omega_m': 0.60359376854119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,675 [classy] Computing new state
 2023-07-02 10:24:56,675 [classy] Setting parameters: {'Omega_m': 0.60359376854119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.04721871501327}
 2023-07-02 10:24:56,726 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,729 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.91778
 2023-07-02 10:24:56,729 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,729 [model] Posterior to be computed for parameters {'Omega_m': 0.15200950509395011}
 2023-07-02 10:24:56,729 [prior] Evaluating prior at array([0.15200951])
 2023-07-02 10:24:56,729 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,729 [model] Got input parameters: {'Omega_m': 0.15200950509395011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,729 [classy] Got parameters {'Omega_m': 0.15200950509395011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,729 [classy] Computing new state
 2023-07-02 10:24:56,730 [classy] Setting parameters: {'Omega_m': 0.15200950509395011, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.67499855735954}
 2023-07-02 10:24:56,778 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.55145
 2023-07-02 10:24:56,780 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,780 [model] Posterior to be computed for parameters {'Omega_m': 0.26870541247070573}
 2023-07-02 10:24:56,780 [prior] Evaluating prior at array([0.26870541])
 2023-07-02 10:24:56,781 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,781 [model] Got input parameters: {'Omega_m': 0.26870541247070573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,781 [classy] Got parameters {'Omega_m': 0.26870541247070573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,781 [classy] Computing new state
 2023-07-02 10:24:56,781 [classy] Setting parameters: {'Omega_m': 0.26870541247070573, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.88160714070378}
 2023-07-02 10:24:56,829 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,831 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.131894
 2023-07-02 10:24:56,831 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,832 [mcmc] New sample, #475:
   Omega_m:0.3319857
 2023-07-02 10:24:56,832 [model] Posterior to be computed for parameters {'Omega_m': 0.06187105319800107}
 2023-07-02 10:24:56,832 [prior] Evaluating prior at array([0.06187105])
 2023-07-02 10:24:56,832 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:56,832 [model] Posterior to be computed for parameters {'Omega_m': 0.7421253746372425}
 2023-07-02 10:24:56,832 [prior] Evaluating prior at array([0.74212537])
 2023-07-02 10:24:56,832 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,832 [model] Got input parameters: {'Omega_m': 0.7421253746372425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,832 [classy] Got parameters {'Omega_m': 0.7421253746372425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,832 [classy] Computing new state
 2023-07-02 10:24:56,832 [classy] Setting parameters: {'Omega_m': 0.7421253746372425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.18141965632469}
 2023-07-02 10:24:56,879 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,882 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.16628
 2023-07-02 10:24:56,882 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3610544096983999}
 2023-07-02 10:24:56,882 [prior] Evaluating prior at array([0.36105441])
 2023-07-02 10:24:56,882 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,882 [model] Got input parameters: {'Omega_m': 0.3610544096983999, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,883 [classy] Got parameters {'Omega_m': 0.3610544096983999, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,883 [classy] Computing new state
 2023-07-02 10:24:56,883 [classy] Setting parameters: {'Omega_m': 0.3610544096983999, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.78858586836583}
 2023-07-02 10:24:56,931 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.12908
 2023-07-02 10:24:56,934 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,934 [mcmc] New sample, #476:
   Omega_m:0.2687054
 2023-07-02 10:24:56,934 [model] Posterior to be computed for parameters {'Omega_m': 0.7661509377562101}
 2023-07-02 10:24:56,934 [prior] Evaluating prior at array([0.76615094])
 2023-07-02 10:24:56,934 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,935 [model] Got input parameters: {'Omega_m': 0.7661509377562101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,935 [classy] Got parameters {'Omega_m': 0.7661509377562101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,935 [classy] Computing new state
 2023-07-02 10:24:56,935 [classy] Setting parameters: {'Omega_m': 0.7661509377562101, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:56,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.98002200321469}
 2023-07-02 10:24:56,981 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:56,984 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.57326
 2023-07-02 10:24:56,984 [model] Computed derived parameters: {}
 2023-07-02 10:24:56,984 [model] Posterior to be computed for parameters {'Omega_m': 0.44701356579548246}
 2023-07-02 10:24:56,984 [prior] Evaluating prior at array([0.44701357])
 2023-07-02 10:24:56,984 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:56,984 [model] Got input parameters: {'Omega_m': 0.44701356579548246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,984 [classy] Got parameters {'Omega_m': 0.44701356579548246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:56,984 [classy] Computing new state
 2023-07-02 10:24:56,985 [classy] Setting parameters: {'Omega_m': 0.44701356579548246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,035 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.60119362147717}
 2023-07-02 10:24:57,036 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,038 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.824061
 2023-07-02 10:24:57,038 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,038 [mcmc] New sample, #477:
   Omega_m:0.3610544
 2023-07-02 10:24:57,038 [model] Posterior to be computed for parameters {'Omega_m': 0.19308934838203123}
 2023-07-02 10:24:57,039 [prior] Evaluating prior at array([0.19308935])
 2023-07-02 10:24:57,039 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,039 [model] Got input parameters: {'Omega_m': 0.19308934838203123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,039 [classy] Got parameters {'Omega_m': 0.19308934838203123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,039 [classy] Computing new state
 2023-07-02 10:24:57,039 [classy] Setting parameters: {'Omega_m': 0.19308934838203123, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.69334557494722}
 2023-07-02 10:24:57,087 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.22619
 2023-07-02 10:24:57,089 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,089 [model] Posterior to be computed for parameters {'Omega_m': 0.3511332622061472}
 2023-07-02 10:24:57,089 [prior] Evaluating prior at array([0.35113326])
 2023-07-02 10:24:57,089 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,089 [model] Got input parameters: {'Omega_m': 0.3511332622061472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,089 [classy] Got parameters {'Omega_m': 0.3511332622061472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,089 [classy] Computing new state
 2023-07-02 10:24:57,089 [classy] Setting parameters: {'Omega_m': 0.3511332622061472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,138 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.84932109338956}
 2023-07-02 10:24:57,138 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,140 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0836851
 2023-07-02 10:24:57,140 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,140 [mcmc] New sample, #478:
   Omega_m:0.4470136
 2023-07-02 10:24:57,140 [model] Posterior to be computed for parameters {'Omega_m': 0.24449886285267897}
 2023-07-02 10:24:57,140 [prior] Evaluating prior at array([0.24449886])
 2023-07-02 10:24:57,140 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,140 [model] Got input parameters: {'Omega_m': 0.24449886285267897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,140 [classy] Got parameters {'Omega_m': 0.24449886285267897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,140 [classy] Computing new state
 2023-07-02 10:24:57,140 [classy] Setting parameters: {'Omega_m': 0.24449886285267897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,190 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.33383493088584}
 2023-07-02 10:24:57,190 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,192 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.339993
 2023-07-02 10:24:57,192 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,192 [mcmc] New sample, #479:
   Omega_m:0.3511333
 2023-07-02 10:24:57,192 [model] Posterior to be computed for parameters {'Omega_m': 0.4793283838172733}
 2023-07-02 10:24:57,193 [prior] Evaluating prior at array([0.47932838])
 2023-07-02 10:24:57,193 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,193 [model] Got input parameters: {'Omega_m': 0.4793283838172733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,193 [classy] Got parameters {'Omega_m': 0.4793283838172733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,193 [classy] Computing new state
 2023-07-02 10:24:57,193 [classy] Setting parameters: {'Omega_m': 0.4793283838172733, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.9131198440028}
 2023-07-02 10:24:57,242 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,244 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.19053
 2023-07-02 10:24:57,244 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,244 [model] Posterior to be computed for parameters {'Omega_m': -0.22025253538277467}
 2023-07-02 10:24:57,245 [prior] Evaluating prior at array([-0.22025254])
 2023-07-02 10:24:57,245 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:57,245 [model] Posterior to be computed for parameters {'Omega_m': 0.002748045088537654}
 2023-07-02 10:24:57,245 [prior] Evaluating prior at array([0.00274805])
 2023-07-02 10:24:57,245 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:57,245 [model] Posterior to be computed for parameters {'Omega_m': 0.44862691641739383}
 2023-07-02 10:24:57,245 [prior] Evaluating prior at array([0.44862692])
 2023-07-02 10:24:57,245 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,245 [model] Got input parameters: {'Omega_m': 0.44862691641739383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,245 [classy] Got parameters {'Omega_m': 0.44862691641739383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,245 [classy] Computing new state
 2023-07-02 10:24:57,245 [classy] Setting parameters: {'Omega_m': 0.44862691641739383, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,293 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.46251301094304}
 2023-07-02 10:24:57,293 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,296 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.841248
 2023-07-02 10:24:57,296 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,296 [model] Posterior to be computed for parameters {'Omega_m': 0.33966348090923326}
 2023-07-02 10:24:57,296 [prior] Evaluating prior at array([0.33966348])
 2023-07-02 10:24:57,296 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,297 [model] Got input parameters: {'Omega_m': 0.33966348090923326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,297 [classy] Got parameters {'Omega_m': 0.33966348090923326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,297 [classy] Computing new state
 2023-07-02 10:24:57,297 [classy] Setting parameters: {'Omega_m': 0.33966348090923326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1104494268838}
 2023-07-02 10:24:57,344 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0426108
 2023-07-02 10:24:57,347 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,347 [mcmc] New sample, #480:
   Omega_m:0.2444989
 2023-07-02 10:24:57,347 [mcmc] Learn + convergence test @ 480 samples accepted.
 2023-07-02 10:24:57,347 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:24:57,353 [mcmc]  - Acceptance rate: 0.416
 2023-07-02 10:24:57,354 [mcmc]  - Condition number = 1
 2023-07-02 10:24:57,354 [mcmc]  - Eigenvalues = array([0.0089159])
 2023-07-02 10:24:57,354 [mcmc]  - Convergence of means: R-1 = 0.008916 after 384 accepted steps
 2023-07-02 10:24:57,354 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:24:57,354 [mcmc] array([[0.01221298]])
 2023-07-02 10:24:57,364 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:24:57,364 [model] Posterior to be computed for parameters {'Omega_m': 0.6867707876486637}
 2023-07-02 10:24:57,364 [prior] Evaluating prior at array([0.68677079])
 2023-07-02 10:24:57,365 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,365 [model] Got input parameters: {'Omega_m': 0.6867707876486637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,365 [classy] Got parameters {'Omega_m': 0.6867707876486637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,365 [classy] Computing new state
 2023-07-02 10:24:57,365 [classy] Setting parameters: {'Omega_m': 0.6867707876486637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.11863918175084}
 2023-07-02 10:24:57,415 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,417 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.24362
 2023-07-02 10:24:57,417 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,417 [model] Posterior to be computed for parameters {'Omega_m': 0.27133818609766547}
 2023-07-02 10:24:57,417 [prior] Evaluating prior at array([0.27133819])
 2023-07-02 10:24:57,417 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,417 [model] Got input parameters: {'Omega_m': 0.27133818609766547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,417 [classy] Got parameters {'Omega_m': 0.27133818609766547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,417 [classy] Computing new state
 2023-07-02 10:24:57,417 [classy] Setting parameters: {'Omega_m': 0.27133818609766547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,468 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.5220130664281}
 2023-07-02 10:24:57,468 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,470 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.115702
 2023-07-02 10:24:57,470 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,470 [mcmc] New sample, #481:
   Omega_m:0.3396635
 2023-07-02 10:24:57,470 [model] Posterior to be computed for parameters {'Omega_m': -0.159431386035431}
 2023-07-02 10:24:57,470 [prior] Evaluating prior at array([-0.15943139])
 2023-07-02 10:24:57,470 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:57,471 [model] Posterior to be computed for parameters {'Omega_m': 0.22743338916384875}
 2023-07-02 10:24:57,471 [prior] Evaluating prior at array([0.22743339])
 2023-07-02 10:24:57,471 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,471 [model] Got input parameters: {'Omega_m': 0.22743338916384875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,471 [classy] Got parameters {'Omega_m': 0.22743338916384875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,471 [classy] Computing new state
 2023-07-02 10:24:57,471 [classy] Setting parameters: {'Omega_m': 0.22743338916384875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.9404831028675}
 2023-07-02 10:24:57,523 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.559219
 2023-07-02 10:24:57,525 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,525 [mcmc] New sample, #482:
   Omega_m:0.2713382
 2023-07-02 10:24:57,526 [model] Posterior to be computed for parameters {'Omega_m': 0.22064955407671344}
 2023-07-02 10:24:57,526 [prior] Evaluating prior at array([0.22064955])
 2023-07-02 10:24:57,526 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,526 [model] Got input parameters: {'Omega_m': 0.22064955407671344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,526 [classy] Got parameters {'Omega_m': 0.22064955407671344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,526 [classy] Computing new state
 2023-07-02 10:24:57,526 [classy] Setting parameters: {'Omega_m': 0.22064955407671344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.02034720876546}
 2023-07-02 10:24:57,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.665384
 2023-07-02 10:24:57,581 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,581 [mcmc] New sample, #483:
   Omega_m:0.2274334
 2023-07-02 10:24:57,581 [model] Posterior to be computed for parameters {'Omega_m': -0.26316354009123577}
 2023-07-02 10:24:57,581 [prior] Evaluating prior at array([-0.26316354])
 2023-07-02 10:24:57,581 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:57,581 [model] Posterior to be computed for parameters {'Omega_m': 0.8440387668413107}
 2023-07-02 10:24:57,581 [prior] Evaluating prior at array([0.84403877])
 2023-07-02 10:24:57,581 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,581 [model] Got input parameters: {'Omega_m': 0.8440387668413107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,581 [classy] Got parameters {'Omega_m': 0.8440387668413107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,581 [classy] Computing new state
 2023-07-02 10:24:57,581 [classy] Setting parameters: {'Omega_m': 0.8440387668413107, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.3532128671015}
 2023-07-02 10:24:57,632 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,634 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.90956
 2023-07-02 10:24:57,634 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,634 [model] Posterior to be computed for parameters {'Omega_m': 0.4023210000821952}
 2023-07-02 10:24:57,634 [prior] Evaluating prior at array([0.402321])
 2023-07-02 10:24:57,634 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,634 [model] Got input parameters: {'Omega_m': 0.4023210000821952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,634 [classy] Got parameters {'Omega_m': 0.4023210000821952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,634 [classy] Computing new state
 2023-07-02 10:24:57,634 [classy] Setting parameters: {'Omega_m': 0.4023210000821952, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.6498341368594}
 2023-07-02 10:24:57,685 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.402867
 2023-07-02 10:24:57,687 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,687 [mcmc] New sample, #484:
   Omega_m:0.2206496
 2023-07-02 10:24:57,687 [model] Posterior to be computed for parameters {'Omega_m': 0.20792652340549492}
 2023-07-02 10:24:57,687 [prior] Evaluating prior at array([0.20792652])
 2023-07-02 10:24:57,687 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,687 [model] Got input parameters: {'Omega_m': 0.20792652340549492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,687 [classy] Got parameters {'Omega_m': 0.20792652340549492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,687 [classy] Computing new state
 2023-07-02 10:24:57,687 [classy] Setting parameters: {'Omega_m': 0.20792652340549492, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.11814671477725}
 2023-07-02 10:24:57,740 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,742 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.89694
 2023-07-02 10:24:57,742 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,742 [model] Posterior to be computed for parameters {'Omega_m': 0.040691792035609575}
 2023-07-02 10:24:57,742 [prior] Evaluating prior at array([0.04069179])
 2023-07-02 10:24:57,743 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:57,743 [model] Posterior to be computed for parameters {'Omega_m': 0.7369371268068596}
 2023-07-02 10:24:57,743 [prior] Evaluating prior at array([0.73693713])
 2023-07-02 10:24:57,743 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,743 [model] Got input parameters: {'Omega_m': 0.7369371268068596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,743 [classy] Got parameters {'Omega_m': 0.7369371268068596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,743 [classy] Computing new state
 2023-07-02 10:24:57,743 [classy] Setting parameters: {'Omega_m': 0.7369371268068596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.44644197599506}
 2023-07-02 10:24:57,792 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,795 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.07883
 2023-07-02 10:24:57,795 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,795 [model] Posterior to be computed for parameters {'Omega_m': 0.21746467085280555}
 2023-07-02 10:24:57,795 [prior] Evaluating prior at array([0.21746467])
 2023-07-02 10:24:57,795 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,795 [model] Got input parameters: {'Omega_m': 0.21746467085280555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,795 [classy] Got parameters {'Omega_m': 0.21746467085280555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,795 [classy] Computing new state
 2023-07-02 10:24:57,795 [classy] Setting parameters: {'Omega_m': 0.21746467085280555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.5364444131339}
 2023-07-02 10:24:57,845 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.719268
 2023-07-02 10:24:57,848 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,848 [model] Posterior to be computed for parameters {'Omega_m': 0.49272648164610805}
 2023-07-02 10:24:57,848 [prior] Evaluating prior at array([0.49272648])
 2023-07-02 10:24:57,848 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,848 [model] Got input parameters: {'Omega_m': 0.49272648164610805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,848 [classy] Got parameters {'Omega_m': 0.49272648164610805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,848 [classy] Computing new state
 2023-07-02 10:24:57,848 [classy] Setting parameters: {'Omega_m': 0.49272648164610805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,897 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.85101765769232}
 2023-07-02 10:24:57,897 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.35495
 2023-07-02 10:24:57,900 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,900 [model] Posterior to be computed for parameters {'Omega_m': 0.2666145038243846}
 2023-07-02 10:24:57,900 [prior] Evaluating prior at array([0.2666145])
 2023-07-02 10:24:57,900 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,900 [model] Got input parameters: {'Omega_m': 0.2666145038243846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,900 [classy] Got parameters {'Omega_m': 0.2666145038243846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,900 [classy] Computing new state
 2023-07-02 10:24:57,900 [classy] Setting parameters: {'Omega_m': 0.2666145038243846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.16931507937986}
 2023-07-02 10:24:57,948 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:57,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.1456
 2023-07-02 10:24:57,951 [model] Computed derived parameters: {}
 2023-07-02 10:24:57,951 [mcmc] New sample, #485:
   Omega_m:0.402321
 2023-07-02 10:24:57,951 [model] Posterior to be computed for parameters {'Omega_m': 0.20703986222239235}
 2023-07-02 10:24:57,951 [prior] Evaluating prior at array([0.20703986])
 2023-07-02 10:24:57,951 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:57,951 [model] Got input parameters: {'Omega_m': 0.20703986222239235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,951 [classy] Got parameters {'Omega_m': 0.20703986222239235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:57,951 [classy] Computing new state
 2023-07-02 10:24:57,952 [classy] Setting parameters: {'Omega_m': 0.20703986222239235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:57,998 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.26803287057638}
 2023-07-02 10:24:57,998 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,000 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.914754
 2023-07-02 10:24:58,001 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,001 [model] Posterior to be computed for parameters {'Omega_m': 0.05911522687824197}
 2023-07-02 10:24:58,001 [prior] Evaluating prior at array([0.05911523])
 2023-07-02 10:24:58,001 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:58,001 [model] Posterior to be computed for parameters {'Omega_m': 0.3295998026546274}
 2023-07-02 10:24:58,001 [prior] Evaluating prior at array([0.3295998])
 2023-07-02 10:24:58,001 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,001 [model] Got input parameters: {'Omega_m': 0.3295998026546274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,001 [classy] Got parameters {'Omega_m': 0.3295998026546274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,001 [classy] Computing new state
 2023-07-02 10:24:58,001 [classy] Setting parameters: {'Omega_m': 0.3295998026546274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2492868779145}
 2023-07-02 10:24:58,048 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0174297
 2023-07-02 10:24:58,050 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,050 [mcmc] New sample, #486:
   Omega_m:0.2666145
 2023-07-02 10:24:58,050 [model] Posterior to be computed for parameters {'Omega_m': 0.303580996064218}
 2023-07-02 10:24:58,050 [prior] Evaluating prior at array([0.303581])
 2023-07-02 10:24:58,050 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,050 [model] Got input parameters: {'Omega_m': 0.303580996064218, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,050 [classy] Got parameters {'Omega_m': 0.303580996064218, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,050 [classy] Computing new state
 2023-07-02 10:24:58,050 [classy] Setting parameters: {'Omega_m': 0.303580996064218, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.34513852837438}
 2023-07-02 10:24:58,096 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00517269
 2023-07-02 10:24:58,098 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,098 [mcmc] New sample, #487:
   Omega_m:0.3295998
 2023-07-02 10:24:58,099 [model] Posterior to be computed for parameters {'Omega_m': 0.15086905549703236}
 2023-07-02 10:24:58,099 [prior] Evaluating prior at array([0.15086906])
 2023-07-02 10:24:58,099 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,099 [model] Got input parameters: {'Omega_m': 0.15086905549703236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,099 [classy] Got parameters {'Omega_m': 0.15086905549703236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,099 [classy] Computing new state
 2023-07-02 10:24:58,099 [classy] Setting parameters: {'Omega_m': 0.15086905549703236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,145 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.91711586445405}
 2023-07-02 10:24:58,145 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,147 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.59865
 2023-07-02 10:24:58,147 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,147 [model] Posterior to be computed for parameters {'Omega_m': 0.13199600682645402}
 2023-07-02 10:24:58,148 [prior] Evaluating prior at array([0.13199601])
 2023-07-02 10:24:58,148 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,148 [model] Got input parameters: {'Omega_m': 0.13199600682645402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,148 [classy] Got parameters {'Omega_m': 0.13199600682645402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,148 [classy] Computing new state
 2023-07-02 10:24:58,148 [classy] Setting parameters: {'Omega_m': 0.13199600682645402, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 177.11315902598756}
 2023-07-02 10:24:58,194 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,196 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.48009
 2023-07-02 10:24:58,196 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,197 [model] Posterior to be computed for parameters {'Omega_m': 1.2427119618064963}
 2023-07-02 10:24:58,197 [prior] Evaluating prior at array([1.24271196])
 2023-07-02 10:24:58,197 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:58,197 [model] Posterior to be computed for parameters {'Omega_m': 0.4472987085514163}
 2023-07-02 10:24:58,197 [prior] Evaluating prior at array([0.44729871])
 2023-07-02 10:24:58,197 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,197 [model] Got input parameters: {'Omega_m': 0.4472987085514163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,197 [classy] Got parameters {'Omega_m': 0.4472987085514163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,197 [classy] Computing new state
 2023-07-02 10:24:58,197 [classy] Setting parameters: {'Omega_m': 0.4472987085514163, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.57664917591535}
 2023-07-02 10:24:58,245 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,246 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.827089
 2023-07-02 10:24:58,247 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,247 [model] Posterior to be computed for parameters {'Omega_m': 0.44303977630074587}
 2023-07-02 10:24:58,247 [prior] Evaluating prior at array([0.44303978])
 2023-07-02 10:24:58,247 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,247 [model] Got input parameters: {'Omega_m': 0.44303977630074587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,247 [classy] Got parameters {'Omega_m': 0.44303977630074587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,247 [classy] Computing new state
 2023-07-02 10:24:58,247 [classy] Setting parameters: {'Omega_m': 0.44303977630074587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.9448687905368}
 2023-07-02 10:24:58,294 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,296 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.782266
 2023-07-02 10:24:58,296 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,296 [model] Posterior to be computed for parameters {'Omega_m': 0.6098798011584754}
 2023-07-02 10:24:58,296 [prior] Evaluating prior at array([0.6098798])
 2023-07-02 10:24:58,296 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,296 [model] Got input parameters: {'Omega_m': 0.6098798011584754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,296 [classy] Got parameters {'Omega_m': 0.6098798011584754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,296 [classy] Computing new state
 2023-07-02 10:24:58,296 [classy] Setting parameters: {'Omega_m': 0.6098798011584754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.65031555086593}
 2023-07-02 10:24:58,344 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.01453
 2023-07-02 10:24:58,345 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,346 [model] Posterior to be computed for parameters {'Omega_m': 0.39509618281919673}
 2023-07-02 10:24:58,346 [prior] Evaluating prior at array([0.39509618])
 2023-07-02 10:24:58,346 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,346 [model] Got input parameters: {'Omega_m': 0.39509618281919673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,346 [classy] Got parameters {'Omega_m': 0.39509618281919673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,346 [classy] Computing new state
 2023-07-02 10:24:58,346 [classy] Setting parameters: {'Omega_m': 0.39509618281919673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.34462348825278}
 2023-07-02 10:24:58,402 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.346003
 2023-07-02 10:24:58,404 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,404 [mcmc] New sample, #488:
   Omega_m:0.303581
 2023-07-02 10:24:58,404 [model] Posterior to be computed for parameters {'Omega_m': 0.3420387079439696}
 2023-07-02 10:24:58,404 [prior] Evaluating prior at array([0.34203871])
 2023-07-02 10:24:58,404 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,404 [model] Got input parameters: {'Omega_m': 0.3420387079439696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,404 [classy] Got parameters {'Omega_m': 0.3420387079439696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,405 [classy] Computing new state
 2023-07-02 10:24:58,405 [classy] Setting parameters: {'Omega_m': 0.3420387079439696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,453 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.84611518584913}
 2023-07-02 10:24:58,453 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,455 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0500675
 2023-07-02 10:24:58,456 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,456 [mcmc] New sample, #489:
   Omega_m:0.3950962
 2023-07-02 10:24:58,456 [model] Posterior to be computed for parameters {'Omega_m': 0.006289722193287661}
 2023-07-02 10:24:58,456 [prior] Evaluating prior at array([0.00628972])
 2023-07-02 10:24:58,456 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:58,456 [model] Posterior to be computed for parameters {'Omega_m': 0.3204165760127692}
 2023-07-02 10:24:58,456 [prior] Evaluating prior at array([0.32041658])
 2023-07-02 10:24:58,456 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,456 [model] Got input parameters: {'Omega_m': 0.3204165760127692, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,456 [classy] Got parameters {'Omega_m': 0.3204165760127692, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,456 [classy] Computing new state
 2023-07-02 10:24:58,457 [classy] Setting parameters: {'Omega_m': 0.3204165760127692, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3162532928452}
 2023-07-02 10:24:58,507 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00398586
 2023-07-02 10:24:58,509 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,509 [mcmc] New sample, #490:
   Omega_m:0.3420387
 2023-07-02 10:24:58,509 [model] Posterior to be computed for parameters {'Omega_m': 0.2316909815566665}
 2023-07-02 10:24:58,509 [prior] Evaluating prior at array([0.23169098])
 2023-07-02 10:24:58,510 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,510 [model] Got input parameters: {'Omega_m': 0.2316909815566665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,510 [classy] Got parameters {'Omega_m': 0.2316909815566665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,510 [classy] Computing new state
 2023-07-02 10:24:58,510 [classy] Setting parameters: {'Omega_m': 0.2316909815566665, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.2757439229257}
 2023-07-02 10:24:58,561 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,563 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.49831
 2023-07-02 10:24:58,563 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,563 [model] Posterior to be computed for parameters {'Omega_m': 0.4527346598486598}
 2023-07-02 10:24:58,564 [prior] Evaluating prior at array([0.45273466])
 2023-07-02 10:24:58,564 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,564 [model] Got input parameters: {'Omega_m': 0.4527346598486598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,564 [classy] Got parameters {'Omega_m': 0.4527346598486598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,564 [classy] Computing new state
 2023-07-02 10:24:58,564 [classy] Setting parameters: {'Omega_m': 0.4527346598486598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,613 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.11160756671094}
 2023-07-02 10:24:58,614 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.885568
 2023-07-02 10:24:58,616 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,616 [mcmc] New sample, #491:
   Omega_m:0.3204166
 2023-07-02 10:24:58,616 [model] Posterior to be computed for parameters {'Omega_m': 0.3149699203730418}
 2023-07-02 10:24:58,616 [prior] Evaluating prior at array([0.31496992])
 2023-07-02 10:24:58,617 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,617 [model] Got input parameters: {'Omega_m': 0.3149699203730418, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,617 [classy] Got parameters {'Omega_m': 0.3149699203730418, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,617 [classy] Computing new state
 2023-07-02 10:24:58,617 [classy] Setting parameters: {'Omega_m': 0.3149699203730418, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9620381223081}
 2023-07-02 10:24:58,668 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000579119
 2023-07-02 10:24:58,669 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,669 [mcmc] New sample, #492:
   Omega_m:0.4527347
 2023-07-02 10:24:58,670 [model] Posterior to be computed for parameters {'Omega_m': 0.000218796065928617}
 2023-07-02 10:24:58,670 [prior] Evaluating prior at array([0.0002188])
 2023-07-02 10:24:58,670 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:58,670 [model] Posterior to be computed for parameters {'Omega_m': 0.44650368618027025}
 2023-07-02 10:24:58,670 [prior] Evaluating prior at array([0.44650369])
 2023-07-02 10:24:58,670 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,670 [model] Got input parameters: {'Omega_m': 0.44650368618027025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,670 [classy] Got parameters {'Omega_m': 0.44650368618027025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,670 [classy] Computing new state
 2023-07-02 10:24:58,670 [classy] Setting parameters: {'Omega_m': 0.44650368618027025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.64512504730916}
 2023-07-02 10:24:58,720 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,722 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.818655
 2023-07-02 10:24:58,722 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,722 [mcmc] New sample, #493:
   Omega_m:0.3149699
 2023-07-02 10:24:58,723 [model] Posterior to be computed for parameters {'Omega_m': 0.19100925321391593}
 2023-07-02 10:24:58,723 [prior] Evaluating prior at array([0.19100925])
 2023-07-02 10:24:58,723 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,723 [model] Got input parameters: {'Omega_m': 0.19100925321391593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,723 [classy] Got parameters {'Omega_m': 0.19100925321391593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,723 [classy] Computing new state
 2023-07-02 10:24:58,723 [classy] Setting parameters: {'Omega_m': 0.19100925321391593, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.06622766378237}
 2023-07-02 10:24:58,775 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,778 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.27792
 2023-07-02 10:24:58,778 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,778 [model] Posterior to be computed for parameters {'Omega_m': 0.4504220668826536}
 2023-07-02 10:24:58,778 [prior] Evaluating prior at array([0.45042207])
 2023-07-02 10:24:58,779 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,779 [model] Got input parameters: {'Omega_m': 0.4504220668826536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,779 [classy] Got parameters {'Omega_m': 0.4504220668826536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,779 [classy] Computing new state
 2023-07-02 10:24:58,779 [classy] Setting parameters: {'Omega_m': 0.4504220668826536, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.30877578204175}
 2023-07-02 10:24:58,833 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,835 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.860519
 2023-07-02 10:24:58,835 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,835 [mcmc] New sample, #494:
   Omega_m:0.4465037
 2023-07-02 10:24:58,835 [model] Posterior to be computed for parameters {'Omega_m': 0.38098561200603404}
 2023-07-02 10:24:58,835 [prior] Evaluating prior at array([0.38098561])
 2023-07-02 10:24:58,836 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,836 [model] Got input parameters: {'Omega_m': 0.38098561200603404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,836 [classy] Got parameters {'Omega_m': 0.38098561200603404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,836 [classy] Computing new state
 2023-07-02 10:24:58,836 [classy] Setting parameters: {'Omega_m': 0.38098561200603404, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.73704023110884}
 2023-07-02 10:24:58,888 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,890 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.245369
 2023-07-02 10:24:58,890 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,890 [mcmc] New sample, #495:
   Omega_m:0.4504221
 2023-07-02 10:24:58,890 [model] Posterior to be computed for parameters {'Omega_m': 0.027363947613091133}
 2023-07-02 10:24:58,890 [prior] Evaluating prior at array([0.02736395])
 2023-07-02 10:24:58,890 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:58,890 [model] Posterior to be computed for parameters {'Omega_m': 0.2684475781084633}
 2023-07-02 10:24:58,890 [prior] Evaluating prior at array([0.26844758])
 2023-07-02 10:24:58,890 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,890 [model] Got input parameters: {'Omega_m': 0.2684475781084633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,890 [classy] Got parameters {'Omega_m': 0.2684475781084633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,890 [classy] Computing new state
 2023-07-02 10:24:58,890 [classy] Setting parameters: {'Omega_m': 0.2684475781084633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,941 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.91698180883932}
 2023-07-02 10:24:58,941 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,942 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.133543
 2023-07-02 10:24:58,943 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,943 [mcmc] New sample, #496:
   Omega_m:0.3809856
 2023-07-02 10:24:58,943 [model] Posterior to be computed for parameters {'Omega_m': 0.6460008213503673}
 2023-07-02 10:24:58,943 [prior] Evaluating prior at array([0.64600082])
 2023-07-02 10:24:58,943 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,943 [model] Got input parameters: {'Omega_m': 0.6460008213503673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,943 [classy] Got parameters {'Omega_m': 0.6460008213503673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,943 [classy] Computing new state
 2023-07-02 10:24:58,943 [classy] Setting parameters: {'Omega_m': 0.6460008213503673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:58,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.45004915319981}
 2023-07-02 10:24:58,993 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:58,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.58244
 2023-07-02 10:24:58,995 [model] Computed derived parameters: {}
 2023-07-02 10:24:58,995 [model] Posterior to be computed for parameters {'Omega_m': 0.18194352835918481}
 2023-07-02 10:24:58,995 [prior] Evaluating prior at array([0.18194353])
 2023-07-02 10:24:58,995 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:58,995 [model] Got input parameters: {'Omega_m': 0.18194352835918481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,995 [classy] Got parameters {'Omega_m': 0.18194352835918481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:58,995 [classy] Computing new state
 2023-07-02 10:24:58,995 [classy] Setting parameters: {'Omega_m': 0.18194352835918481, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,046 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.72743963252006}
 2023-07-02 10:24:59,046 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.5207
 2023-07-02 10:24:59,048 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,048 [model] Posterior to be computed for parameters {'Omega_m': 0.1429904125067427}
 2023-07-02 10:24:59,048 [prior] Evaluating prior at array([0.14299041])
 2023-07-02 10:24:59,048 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,048 [model] Got input parameters: {'Omega_m': 0.1429904125067427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,048 [classy] Got parameters {'Omega_m': 0.1429904125067427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,048 [classy] Computing new state
 2023-07-02 10:24:59,048 [classy] Setting parameters: {'Omega_m': 0.1429904125067427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.62434230295347}
 2023-07-02 10:24:59,096 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.94289
 2023-07-02 10:24:59,098 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,098 [model] Posterior to be computed for parameters {'Omega_m': 0.28883176986597187}
 2023-07-02 10:24:59,098 [prior] Evaluating prior at array([0.28883177])
 2023-07-02 10:24:59,098 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,098 [model] Got input parameters: {'Omega_m': 0.28883176986597187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,098 [classy] Got parameters {'Omega_m': 0.28883176986597187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,098 [classy] Computing new state
 2023-07-02 10:24:59,098 [classy] Setting parameters: {'Omega_m': 0.28883176986597187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.20567030704817}
 2023-07-02 10:24:59,146 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0366362
 2023-07-02 10:24:59,148 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,148 [mcmc] New sample, #497:
   Omega_m:0.2684476
 2023-07-02 10:24:59,148 [model] Posterior to be computed for parameters {'Omega_m': -0.18935579704719563}
 2023-07-02 10:24:59,148 [prior] Evaluating prior at array([-0.1893558])
 2023-07-02 10:24:59,148 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,148 [model] Posterior to be computed for parameters {'Omega_m': 0.6375616439072355}
 2023-07-02 10:24:59,149 [prior] Evaluating prior at array([0.63756164])
 2023-07-02 10:24:59,149 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,149 [model] Got input parameters: {'Omega_m': 0.6375616439072355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,149 [classy] Got parameters {'Omega_m': 0.6375616439072355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,149 [classy] Computing new state
 2023-07-02 10:24:59,149 [classy] Setting parameters: {'Omega_m': 0.6375616439072355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,195 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.95225342070886}
 2023-07-02 10:24:59,196 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,197 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.44807
 2023-07-02 10:24:59,197 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,197 [model] Posterior to be computed for parameters {'Omega_m': -0.19592901185617134}
 2023-07-02 10:24:59,198 [prior] Evaluating prior at array([-0.19592901])
 2023-07-02 10:24:59,198 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,198 [model] Posterior to be computed for parameters {'Omega_m': -0.045400155786379404}
 2023-07-02 10:24:59,198 [prior] Evaluating prior at array([-0.04540016])
 2023-07-02 10:24:59,198 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,198 [model] Posterior to be computed for parameters {'Omega_m': 0.3644019137285386}
 2023-07-02 10:24:59,198 [prior] Evaluating prior at array([0.36440191])
 2023-07-02 10:24:59,198 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,198 [model] Got input parameters: {'Omega_m': 0.3644019137285386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,198 [classy] Got parameters {'Omega_m': 0.3644019137285386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,198 [classy] Computing new state
 2023-07-02 10:24:59,198 [classy] Setting parameters: {'Omega_m': 0.3644019137285386, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.4367823130311}
 2023-07-02 10:24:59,246 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.14634
 2023-07-02 10:24:59,248 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,248 [mcmc] New sample, #498:
   Omega_m:0.2888318
 2023-07-02 10:24:59,248 [model] Posterior to be computed for parameters {'Omega_m': 0.0249409911446416}
 2023-07-02 10:24:59,248 [prior] Evaluating prior at array([0.02494099])
 2023-07-02 10:24:59,248 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,248 [model] Posterior to be computed for parameters {'Omega_m': 0.5829197022100089}
 2023-07-02 10:24:59,248 [prior] Evaluating prior at array([0.5829197])
 2023-07-02 10:24:59,249 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,249 [model] Got input parameters: {'Omega_m': 0.5829197022100089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,249 [classy] Got parameters {'Omega_m': 0.5829197022100089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,249 [classy] Computing new state
 2023-07-02 10:24:59,249 [classy] Setting parameters: {'Omega_m': 0.5829197022100089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.383836907}
 2023-07-02 10:24:59,296 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.60454
 2023-07-02 10:24:59,298 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,298 [model] Posterior to be computed for parameters {'Omega_m': 0.31695111855817837}
 2023-07-02 10:24:59,298 [prior] Evaluating prior at array([0.31695112])
 2023-07-02 10:24:59,298 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,298 [model] Got input parameters: {'Omega_m': 0.31695111855817837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,298 [classy] Got parameters {'Omega_m': 0.31695111855817837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,298 [classy] Computing new state
 2023-07-02 10:24:59,298 [classy] Setting parameters: {'Omega_m': 0.31695111855817837, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72599527735125}
 2023-07-02 10:24:59,346 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00141258
 2023-07-02 10:24:59,347 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,347 [mcmc] New sample, #499:
   Omega_m:0.3644019
 2023-07-02 10:24:59,348 [model] Posterior to be computed for parameters {'Omega_m': 0.15372104750792787}
 2023-07-02 10:24:59,348 [prior] Evaluating prior at array([0.15372105])
 2023-07-02 10:24:59,348 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,348 [model] Got input parameters: {'Omega_m': 0.15372104750792787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,348 [classy] Got parameters {'Omega_m': 0.15372104750792787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,348 [classy] Computing new state
 2023-07-02 10:24:59,348 [classy] Setting parameters: {'Omega_m': 0.15372104750792787, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.31394142664675}
 2023-07-02 10:24:59,395 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,396 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.48181
 2023-07-02 10:24:59,396 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,397 [model] Posterior to be computed for parameters {'Omega_m': -0.3289677563516449}
 2023-07-02 10:24:59,397 [prior] Evaluating prior at array([-0.32896776])
 2023-07-02 10:24:59,397 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,397 [model] Posterior to be computed for parameters {'Omega_m': 1.0192840218664285}
 2023-07-02 10:24:59,397 [prior] Evaluating prior at array([1.01928402])
 2023-07-02 10:24:59,397 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,397 [model] Posterior to be computed for parameters {'Omega_m': 0.27843262830493365}
 2023-07-02 10:24:59,397 [prior] Evaluating prior at array([0.27843263])
 2023-07-02 10:24:59,397 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,397 [model] Got input parameters: {'Omega_m': 0.27843262830493365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,397 [classy] Got parameters {'Omega_m': 0.27843262830493365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,397 [classy] Computing new state
 2023-07-02 10:24:59,397 [classy] Setting parameters: {'Omega_m': 0.27843262830493365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.56765463453382}
 2023-07-02 10:24:59,445 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,447 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0778159
 2023-07-02 10:24:59,447 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,447 [mcmc] New sample, #500:
   Omega_m:0.3169511
 2023-07-02 10:24:59,447 [model] Posterior to be computed for parameters {'Omega_m': 0.40583131383172233}
 2023-07-02 10:24:59,447 [prior] Evaluating prior at array([0.40583131])
 2023-07-02 10:24:59,447 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,447 [model] Got input parameters: {'Omega_m': 0.40583131383172233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,447 [classy] Got parameters {'Omega_m': 0.40583131383172233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,447 [classy] Computing new state
 2023-07-02 10:24:59,447 [classy] Setting parameters: {'Omega_m': 0.40583131383172233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.31652425787706}
 2023-07-02 10:24:59,495 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.431732
 2023-07-02 10:24:59,496 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,496 [mcmc] New sample, #501:
   Omega_m:0.2784326
 2023-07-02 10:24:59,497 [model] Posterior to be computed for parameters {'Omega_m': 0.2152010804542365}
 2023-07-02 10:24:59,497 [prior] Evaluating prior at array([0.21520108])
 2023-07-02 10:24:59,497 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,497 [model] Got input parameters: {'Omega_m': 0.2152010804542365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,497 [classy] Got parameters {'Omega_m': 0.2152010804542365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,497 [classy] Computing new state
 2023-07-02 10:24:59,497 [classy] Setting parameters: {'Omega_m': 0.2152010804542365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.90686101606065}
 2023-07-02 10:24:59,545 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.759186
 2023-07-02 10:24:59,547 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,547 [mcmc] New sample, #502:
   Omega_m:0.4058313
 2023-07-02 10:24:59,547 [model] Posterior to be computed for parameters {'Omega_m': 0.24083491369506746}
 2023-07-02 10:24:59,547 [prior] Evaluating prior at array([0.24083491])
 2023-07-02 10:24:59,547 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,547 [model] Got input parameters: {'Omega_m': 0.24083491369506746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,547 [classy] Got parameters {'Omega_m': 0.24083491369506746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,547 [classy] Computing new state
 2023-07-02 10:24:59,547 [classy] Setting parameters: {'Omega_m': 0.24083491369506746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.88077284093114}
 2023-07-02 10:24:59,595 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.381612
 2023-07-02 10:24:59,597 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,597 [mcmc] New sample, #503:
   Omega_m:0.2152011
 2023-07-02 10:24:59,597 [model] Posterior to be computed for parameters {'Omega_m': 0.21818592324265312}
 2023-07-02 10:24:59,597 [prior] Evaluating prior at array([0.21818592])
 2023-07-02 10:24:59,598 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,598 [model] Got input parameters: {'Omega_m': 0.21818592324265312, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,598 [classy] Got parameters {'Omega_m': 0.21818592324265312, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,598 [classy] Computing new state
 2023-07-02 10:24:59,598 [classy] Setting parameters: {'Omega_m': 0.21818592324265312, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,646 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.41905100810837}
 2023-07-02 10:24:59,646 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,647 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.706833
 2023-07-02 10:24:59,647 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,648 [model] Posterior to be computed for parameters {'Omega_m': 0.19965710470644535}
 2023-07-02 10:24:59,648 [prior] Evaluating prior at array([0.1996571])
 2023-07-02 10:24:59,648 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,648 [model] Got input parameters: {'Omega_m': 0.19965710470644535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,648 [classy] Got parameters {'Omega_m': 0.19965710470644535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,648 [classy] Computing new state
 2023-07-02 10:24:59,648 [classy] Setting parameters: {'Omega_m': 0.19965710470644535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.53551354914342}
 2023-07-02 10:24:59,696 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.07208
 2023-07-02 10:24:59,697 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,698 [model] Posterior to be computed for parameters {'Omega_m': 0.3272900214423215}
 2023-07-02 10:24:59,698 [prior] Evaluating prior at array([0.32729002])
 2023-07-02 10:24:59,698 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,698 [model] Got input parameters: {'Omega_m': 0.3272900214423215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,698 [classy] Got parameters {'Omega_m': 0.3272900214423215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,698 [classy] Computing new state
 2023-07-02 10:24:59,698 [classy] Setting parameters: {'Omega_m': 0.3272900214423215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,746 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5151228873236}
 2023-07-02 10:24:59,746 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,747 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131653
 2023-07-02 10:24:59,747 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,748 [mcmc] New sample, #504:
   Omega_m:0.2408349
 2023-07-02 10:24:59,748 [model] Posterior to be computed for parameters {'Omega_m': -0.3890205184394315}
 2023-07-02 10:24:59,748 [prior] Evaluating prior at array([-0.38902052])
 2023-07-02 10:24:59,748 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:24:59,748 [model] Posterior to be computed for parameters {'Omega_m': 0.4287357291747858}
 2023-07-02 10:24:59,748 [prior] Evaluating prior at array([0.42873573])
 2023-07-02 10:24:59,748 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,748 [model] Got input parameters: {'Omega_m': 0.4287357291747858, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,748 [classy] Got parameters {'Omega_m': 0.4287357291747858, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,748 [classy] Computing new state
 2023-07-02 10:24:59,748 [classy] Setting parameters: {'Omega_m': 0.4287357291747858, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.20741358414028}
 2023-07-02 10:24:59,796 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.63842
 2023-07-02 10:24:59,798 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,798 [mcmc] New sample, #505:
   Omega_m:0.32729
 2023-07-02 10:24:59,798 [model] Posterior to be computed for parameters {'Omega_m': 0.6069887891387977}
 2023-07-02 10:24:59,798 [prior] Evaluating prior at array([0.60698879])
 2023-07-02 10:24:59,798 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,798 [model] Got input parameters: {'Omega_m': 0.6069887891387977, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,798 [classy] Got parameters {'Omega_m': 0.6069887891387977, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,798 [classy] Computing new state
 2023-07-02 10:24:59,798 [classy] Setting parameters: {'Omega_m': 0.6069887891387977, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,848 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.83231517459835}
 2023-07-02 10:24:59,848 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,850 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.96996
 2023-07-02 10:24:59,850 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,850 [mcmc] New sample, #506:
   Omega_m:0.4287357
 2023-07-02 10:24:59,850 [model] Posterior to be computed for parameters {'Omega_m': 0.6812572224799933}
 2023-07-02 10:24:59,850 [prior] Evaluating prior at array([0.68125722])
 2023-07-02 10:24:59,850 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,850 [model] Got input parameters: {'Omega_m': 0.6812572224799933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,850 [classy] Got parameters {'Omega_m': 0.6812572224799933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,850 [classy] Computing new state
 2023-07-02 10:24:59,850 [classy] Setting parameters: {'Omega_m': 0.6812572224799933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.42514018091656}
 2023-07-02 10:24:59,899 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,901 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.15314
 2023-07-02 10:24:59,901 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,901 [mcmc] New sample, #507:
   Omega_m:0.6069888
 2023-07-02 10:24:59,901 [model] Posterior to be computed for parameters {'Omega_m': 0.9532714533403336}
 2023-07-02 10:24:59,901 [prior] Evaluating prior at array([0.95327145])
 2023-07-02 10:24:59,901 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,901 [model] Got input parameters: {'Omega_m': 0.9532714533403336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,901 [classy] Got parameters {'Omega_m': 0.9532714533403336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,901 [classy] Computing new state
 2023-07-02 10:24:59,901 [classy] Setting parameters: {'Omega_m': 0.9532714533403336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.85289745108174}
 2023-07-02 10:24:59,949 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:24:59,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.80199
 2023-07-02 10:24:59,951 [model] Computed derived parameters: {}
 2023-07-02 10:24:59,951 [model] Posterior to be computed for parameters {'Omega_m': 0.8146510914440364}
 2023-07-02 10:24:59,951 [prior] Evaluating prior at array([0.81465109])
 2023-07-02 10:24:59,951 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:24:59,951 [model] Got input parameters: {'Omega_m': 0.8146510914440364, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,951 [classy] Got parameters {'Omega_m': 0.8146510914440364, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:24:59,951 [classy] Computing new state
 2023-07-02 10:24:59,951 [classy] Setting parameters: {'Omega_m': 0.8146510914440364, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:24:59,999 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.67629036113388}
 2023-07-02 10:24:59,999 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,001 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.40305
 2023-07-02 10:25:00,001 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,001 [model] Posterior to be computed for parameters {'Omega_m': 0.4368508942887319}
 2023-07-02 10:25:00,001 [prior] Evaluating prior at array([0.43685089])
 2023-07-02 10:25:00,001 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,001 [model] Got input parameters: {'Omega_m': 0.4368508942887319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,001 [classy] Got parameters {'Omega_m': 0.4368508942887319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,001 [classy] Computing new state
 2023-07-02 10:25:00,001 [classy] Setting parameters: {'Omega_m': 0.4368508942887319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,050 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.4861873550882}
 2023-07-02 10:25:00,050 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,052 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.718729
 2023-07-02 10:25:00,052 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,052 [mcmc] New sample, #508:
   Omega_m:0.6812572
 2023-07-02 10:25:00,052 [model] Posterior to be computed for parameters {'Omega_m': 0.03043767468106101}
 2023-07-02 10:25:00,052 [prior] Evaluating prior at array([0.03043767])
 2023-07-02 10:25:00,052 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,052 [model] Posterior to be computed for parameters {'Omega_m': 0.6520482490851541}
 2023-07-02 10:25:00,053 [prior] Evaluating prior at array([0.65204825])
 2023-07-02 10:25:00,053 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,053 [model] Got input parameters: {'Omega_m': 0.6520482490851541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,053 [classy] Got parameters {'Omega_m': 0.6520482490851541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,053 [classy] Computing new state
 2023-07-02 10:25:00,053 [classy] Setting parameters: {'Omega_m': 0.6520482490851541, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.09447310723998}
 2023-07-02 10:25:00,099 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,101 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.67928
 2023-07-02 10:25:00,101 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,102 [model] Posterior to be computed for parameters {'Omega_m': 0.5298418992954042}
 2023-07-02 10:25:00,102 [prior] Evaluating prior at array([0.5298419])
 2023-07-02 10:25:00,102 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,102 [model] Got input parameters: {'Omega_m': 0.5298418992954042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,102 [classy] Got parameters {'Omega_m': 0.5298418992954042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,102 [classy] Computing new state
 2023-07-02 10:25:00,102 [classy] Setting parameters: {'Omega_m': 0.5298418992954042, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.05403777363148}
 2023-07-02 10:25:00,151 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.84226
 2023-07-02 10:25:00,152 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,153 [model] Posterior to be computed for parameters {'Omega_m': 0.5271170380259129}
 2023-07-02 10:25:00,153 [prior] Evaluating prior at array([0.52711704])
 2023-07-02 10:25:00,153 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,153 [model] Got input parameters: {'Omega_m': 0.5271170380259129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,153 [classy] Got parameters {'Omega_m': 0.5271170380259129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,153 [classy] Computing new state
 2023-07-02 10:25:00,153 [classy] Setting parameters: {'Omega_m': 0.5271170380259129, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.25252759793983}
 2023-07-02 10:25:00,201 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,203 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.80504
 2023-07-02 10:25:00,203 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,203 [model] Posterior to be computed for parameters {'Omega_m': 0.20360865673521666}
 2023-07-02 10:25:00,203 [prior] Evaluating prior at array([0.20360866])
 2023-07-02 10:25:00,203 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,203 [model] Got input parameters: {'Omega_m': 0.20360865673521666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,203 [classy] Got parameters {'Omega_m': 0.20360865673521666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,203 [classy] Computing new state
 2023-07-02 10:25:00,203 [classy] Setting parameters: {'Omega_m': 0.20360865673521666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.85274910686618}
 2023-07-02 10:25:00,252 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,254 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.985848
 2023-07-02 10:25:00,254 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,254 [mcmc] New sample, #509:
   Omega_m:0.4368509
 2023-07-02 10:25:00,254 [model] Posterior to be computed for parameters {'Omega_m': 0.41891353769913114}
 2023-07-02 10:25:00,254 [prior] Evaluating prior at array([0.41891354])
 2023-07-02 10:25:00,255 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,255 [model] Got input parameters: {'Omega_m': 0.41891353769913114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,255 [classy] Got parameters {'Omega_m': 0.41891353769913114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,255 [classy] Computing new state
 2023-07-02 10:25:00,255 [classy] Setting parameters: {'Omega_m': 0.41891353769913114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,303 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.09825634316107}
 2023-07-02 10:25:00,303 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,305 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.546026
 2023-07-02 10:25:00,306 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,306 [mcmc] New sample, #510:
   Omega_m:0.2036087
 2023-07-02 10:25:00,306 [model] Posterior to be computed for parameters {'Omega_m': 0.426431484356208}
 2023-07-02 10:25:00,306 [prior] Evaluating prior at array([0.42643148])
 2023-07-02 10:25:00,306 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,306 [model] Got input parameters: {'Omega_m': 0.426431484356208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,306 [classy] Got parameters {'Omega_m': 0.426431484356208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,306 [classy] Computing new state
 2023-07-02 10:25:00,306 [classy] Setting parameters: {'Omega_m': 0.426431484356208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.41460601900008}
 2023-07-02 10:25:00,354 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.616264
 2023-07-02 10:25:00,356 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,356 [mcmc] New sample, #511:
   Omega_m:0.4189135
 2023-07-02 10:25:00,356 [model] Posterior to be computed for parameters {'Omega_m': 0.4331236397817187}
 2023-07-02 10:25:00,356 [prior] Evaluating prior at array([0.43312364])
 2023-07-02 10:25:00,356 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,356 [model] Got input parameters: {'Omega_m': 0.4331236397817187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,356 [classy] Got parameters {'Omega_m': 0.4331236397817187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,356 [classy] Computing new state
 2023-07-02 10:25:00,356 [classy] Setting parameters: {'Omega_m': 0.4331236397817187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,404 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.8158189429784}
 2023-07-02 10:25:00,404 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,406 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.68141
 2023-07-02 10:25:00,406 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,406 [model] Posterior to be computed for parameters {'Omega_m': 0.3590992070220916}
 2023-07-02 10:25:00,406 [prior] Evaluating prior at array([0.35909921])
 2023-07-02 10:25:00,406 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,406 [model] Got input parameters: {'Omega_m': 0.3590992070220916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,406 [classy] Got parameters {'Omega_m': 0.3590992070220916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,406 [classy] Computing new state
 2023-07-02 10:25:00,406 [classy] Setting parameters: {'Omega_m': 0.3590992070220916, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,454 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99547961113245}
 2023-07-02 10:25:00,454 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,456 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119443
 2023-07-02 10:25:00,456 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,456 [mcmc] New sample, #512:
   Omega_m:0.4264315
 2023-07-02 10:25:00,456 [model] Posterior to be computed for parameters {'Omega_m': 0.4292568163630922}
 2023-07-02 10:25:00,456 [prior] Evaluating prior at array([0.42925682])
 2023-07-02 10:25:00,457 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,457 [model] Got input parameters: {'Omega_m': 0.4292568163630922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,457 [classy] Got parameters {'Omega_m': 0.4292568163630922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,457 [classy] Computing new state
 2023-07-02 10:25:00,457 [classy] Setting parameters: {'Omega_m': 0.4292568163630922, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.16070681432302}
 2023-07-02 10:25:00,504 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.643471
 2023-07-02 10:25:00,506 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,506 [model] Posterior to be computed for parameters {'Omega_m': 0.14034099639645511}
 2023-07-02 10:25:00,506 [prior] Evaluating prior at array([0.140341])
 2023-07-02 10:25:00,506 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,506 [model] Got input parameters: {'Omega_m': 0.14034099639645511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,506 [classy] Got parameters {'Omega_m': 0.14034099639645511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,506 [classy] Computing new state
 2023-07-02 10:25:00,506 [classy] Setting parameters: {'Omega_m': 0.14034099639645511, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,554 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.21238318984066}
 2023-07-02 10:25:00,554 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,556 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.06605
 2023-07-02 10:25:00,556 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,556 [model] Posterior to be computed for parameters {'Omega_m': 0.1352732136373893}
 2023-07-02 10:25:00,556 [prior] Evaluating prior at array([0.13527321])
 2023-07-02 10:25:00,556 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,556 [model] Got input parameters: {'Omega_m': 0.1352732136373893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,556 [classy] Got parameters {'Omega_m': 0.1352732136373893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,556 [classy] Computing new state
 2023-07-02 10:25:00,556 [classy] Setting parameters: {'Omega_m': 0.1352732136373893, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.35775461212725}
 2023-07-02 10:25:00,603 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,605 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.31265
 2023-07-02 10:25:00,605 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,606 [model] Posterior to be computed for parameters {'Omega_m': 0.5222116666774199}
 2023-07-02 10:25:00,606 [prior] Evaluating prior at array([0.52221167])
 2023-07-02 10:25:00,606 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,606 [model] Got input parameters: {'Omega_m': 0.5222116666774199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,606 [classy] Got parameters {'Omega_m': 0.5222116666774199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,606 [classy] Computing new state
 2023-07-02 10:25:00,606 [classy] Setting parameters: {'Omega_m': 0.5222116666774199, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.61250208223163}
 2023-07-02 10:25:00,655 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,656 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.73858
 2023-07-02 10:25:00,656 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,657 [model] Posterior to be computed for parameters {'Omega_m': 0.020585103948990657}
 2023-07-02 10:25:00,657 [prior] Evaluating prior at array([0.0205851])
 2023-07-02 10:25:00,657 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,657 [model] Posterior to be computed for parameters {'Omega_m': 1.0512445780095014}
 2023-07-02 10:25:00,657 [prior] Evaluating prior at array([1.05124458])
 2023-07-02 10:25:00,657 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,657 [model] Posterior to be computed for parameters {'Omega_m': 0.5746449049384776}
 2023-07-02 10:25:00,657 [prior] Evaluating prior at array([0.5746449])
 2023-07-02 10:25:00,657 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,657 [model] Got input parameters: {'Omega_m': 0.5746449049384776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,657 [classy] Got parameters {'Omega_m': 0.5746449049384776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,657 [classy] Computing new state
 2023-07-02 10:25:00,657 [classy] Setting parameters: {'Omega_m': 0.5746449049384776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.93273897843247}
 2023-07-02 10:25:00,705 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,707 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.48147
 2023-07-02 10:25:00,707 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,707 [model] Posterior to be computed for parameters {'Omega_m': -0.018261187069966267}
 2023-07-02 10:25:00,707 [prior] Evaluating prior at array([-0.01826119])
 2023-07-02 10:25:00,707 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,708 [model] Posterior to be computed for parameters {'Omega_m': 0.6524456064256794}
 2023-07-02 10:25:00,708 [prior] Evaluating prior at array([0.65244561])
 2023-07-02 10:25:00,708 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,708 [model] Got input parameters: {'Omega_m': 0.6524456064256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,708 [classy] Got parameters {'Omega_m': 0.6524456064256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,708 [classy] Computing new state
 2023-07-02 10:25:00,708 [classy] Setting parameters: {'Omega_m': 0.6524456064256794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.07123097320716}
 2023-07-02 10:25:00,756 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.68566
 2023-07-02 10:25:00,758 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,758 [model] Posterior to be computed for parameters {'Omega_m': 0.4878308793130527}
 2023-07-02 10:25:00,758 [prior] Evaluating prior at array([0.48783088])
 2023-07-02 10:25:00,758 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,758 [model] Got input parameters: {'Omega_m': 0.4878308793130527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,759 [classy] Got parameters {'Omega_m': 0.4878308793130527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,759 [classy] Computing new state
 2023-07-02 10:25:00,759 [classy] Setting parameters: {'Omega_m': 0.4878308793130527, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.23573327039216}
 2023-07-02 10:25:00,807 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,810 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.29409
 2023-07-02 10:25:00,810 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,810 [model] Posterior to be computed for parameters {'Omega_m': 0.26293436911561363}
 2023-07-02 10:25:00,810 [prior] Evaluating prior at array([0.26293437])
 2023-07-02 10:25:00,810 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,810 [model] Got input parameters: {'Omega_m': 0.26293436911561363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,811 [classy] Got parameters {'Omega_m': 0.26293436911561363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,811 [classy] Computing new state
 2023-07-02 10:25:00,811 [classy] Setting parameters: {'Omega_m': 0.26293436911561363, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.68032840352754}
 2023-07-02 10:25:00,859 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,861 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.171587
 2023-07-02 10:25:00,861 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,861 [mcmc] New sample, #513:
   Omega_m:0.3590992
 2023-07-02 10:25:00,861 [model] Posterior to be computed for parameters {'Omega_m': -0.0668037159471826}
 2023-07-02 10:25:00,861 [prior] Evaluating prior at array([-0.06680372])
 2023-07-02 10:25:00,861 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,862 [model] Posterior to be computed for parameters {'Omega_m': 0.4270595017916761}
 2023-07-02 10:25:00,862 [prior] Evaluating prior at array([0.4270595])
 2023-07-02 10:25:00,862 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,862 [model] Got input parameters: {'Omega_m': 0.4270595017916761, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,862 [classy] Got parameters {'Omega_m': 0.4270595017916761, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,862 [classy] Computing new state
 2023-07-02 10:25:00,862 [classy] Setting parameters: {'Omega_m': 0.4270595017916761, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,911 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.3580295449772}
 2023-07-02 10:25:00,911 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,912 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.622274
 2023-07-02 10:25:00,913 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,913 [model] Posterior to be computed for parameters {'Omega_m': -0.06052913516716146}
 2023-07-02 10:25:00,913 [prior] Evaluating prior at array([-0.06052914])
 2023-07-02 10:25:00,913 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,913 [model] Posterior to be computed for parameters {'Omega_m': -0.09805194209068252}
 2023-07-02 10:25:00,913 [prior] Evaluating prior at array([-0.09805194])
 2023-07-02 10:25:00,913 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:25:00,913 [model] Posterior to be computed for parameters {'Omega_m': 0.4166198707325491}
 2023-07-02 10:25:00,913 [prior] Evaluating prior at array([0.41661987])
 2023-07-02 10:25:00,913 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,913 [model] Got input parameters: {'Omega_m': 0.4166198707325491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,913 [classy] Got parameters {'Omega_m': 0.4166198707325491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,913 [classy] Computing new state
 2023-07-02 10:25:00,913 [classy] Setting parameters: {'Omega_m': 0.4166198707325491, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:00,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.30919160317976}
 2023-07-02 10:25:00,962 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:00,963 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.525243
 2023-07-02 10:25:00,963 [model] Computed derived parameters: {}
 2023-07-02 10:25:00,963 [model] Posterior to be computed for parameters {'Omega_m': 0.3302900486851549}
 2023-07-02 10:25:00,964 [prior] Evaluating prior at array([0.33029005])
 2023-07-02 10:25:00,964 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:00,964 [model] Got input parameters: {'Omega_m': 0.3302900486851549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,964 [classy] Got parameters {'Omega_m': 0.3302900486851549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:00,964 [classy] Computing new state
 2023-07-02 10:25:00,964 [classy] Setting parameters: {'Omega_m': 0.3302900486851549, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1701818798397}
 2023-07-02 10:25:01,011 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.018816
 2023-07-02 10:25:01,013 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,013 [mcmc] New sample, #514:
   Omega_m:0.2629344
 2023-07-02 10:25:01,013 [model] Posterior to be computed for parameters {'Omega_m': 0.35597247926532155}
 2023-07-02 10:25:01,013 [prior] Evaluating prior at array([0.35597248])
 2023-07-02 10:25:01,014 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,014 [model] Got input parameters: {'Omega_m': 0.35597247926532155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,014 [classy] Got parameters {'Omega_m': 0.35597247926532155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,014 [classy] Computing new state
 2023-07-02 10:25:01,014 [classy] Setting parameters: {'Omega_m': 0.35597247926532155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.3285272358097}
 2023-07-02 10:25:01,061 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,063 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.104727
 2023-07-02 10:25:01,063 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,063 [mcmc] New sample, #515:
   Omega_m:0.33029
 2023-07-02 10:25:01,063 [model] Posterior to be computed for parameters {'Omega_m': 0.27422339025415715}
 2023-07-02 10:25:01,063 [prior] Evaluating prior at array([0.27422339])
 2023-07-02 10:25:01,063 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,063 [model] Got input parameters: {'Omega_m': 0.27422339025415715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,063 [classy] Got parameters {'Omega_m': 0.27422339025415715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,064 [classy] Computing new state
 2023-07-02 10:25:01,064 [classy] Setting parameters: {'Omega_m': 0.27422339025415715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,111 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13134627187068}
 2023-07-02 10:25:01,111 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,113 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0992979
 2023-07-02 10:25:01,113 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,113 [mcmc] New sample, #516:
   Omega_m:0.3559725
 2023-07-02 10:25:01,113 [model] Posterior to be computed for parameters {'Omega_m': 0.14450886018958956}
 2023-07-02 10:25:01,113 [prior] Evaluating prior at array([0.14450886])
 2023-07-02 10:25:01,113 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,113 [model] Got input parameters: {'Omega_m': 0.14450886018958956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,113 [classy] Got parameters {'Omega_m': 0.14450886018958956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,113 [classy] Computing new state
 2023-07-02 10:25:01,114 [classy] Setting parameters: {'Omega_m': 0.14450886018958956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,161 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.2905413393162}
 2023-07-02 10:25:01,161 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,163 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.87402
 2023-07-02 10:25:01,163 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,163 [model] Posterior to be computed for parameters {'Omega_m': 0.41123568781668945}
 2023-07-02 10:25:01,163 [prior] Evaluating prior at array([0.41123569])
 2023-07-02 10:25:01,163 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,163 [model] Got input parameters: {'Omega_m': 0.41123568781668945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,163 [classy] Got parameters {'Omega_m': 0.41123568781668945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,163 [classy] Computing new state
 2023-07-02 10:25:01,163 [classy] Setting parameters: {'Omega_m': 0.41123568781668945, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,211 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.80874644997817}
 2023-07-02 10:25:01,211 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,213 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.477686
 2023-07-02 10:25:01,213 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,213 [mcmc] New sample, #517:
   Omega_m:0.2742234
 2023-07-02 10:25:01,213 [model] Posterior to be computed for parameters {'Omega_m': 0.7818493503867618}
 2023-07-02 10:25:01,213 [prior] Evaluating prior at array([0.78184935])
 2023-07-02 10:25:01,213 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,213 [model] Got input parameters: {'Omega_m': 0.7818493503867618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,213 [classy] Got parameters {'Omega_m': 0.7818493503867618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,213 [classy] Computing new state
 2023-07-02 10:25:01,213 [classy] Setting parameters: {'Omega_m': 0.7818493503867618, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,260 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.21715650092754}
 2023-07-02 10:25:01,261 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,262 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.84079
 2023-07-02 10:25:01,262 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,262 [model] Posterior to be computed for parameters {'Omega_m': 0.8116795499514405}
 2023-07-02 10:25:01,262 [prior] Evaluating prior at array([0.81167955])
 2023-07-02 10:25:01,263 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,263 [model] Got input parameters: {'Omega_m': 0.8116795499514405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,263 [classy] Got parameters {'Omega_m': 0.8116795499514405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,263 [classy] Computing new state
 2023-07-02 10:25:01,263 [classy] Setting parameters: {'Omega_m': 0.8116795499514405, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.81303428227075}
 2023-07-02 10:25:01,310 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,312 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.35195
 2023-07-02 10:25:01,312 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,312 [model] Posterior to be computed for parameters {'Omega_m': 0.2884473855225448}
 2023-07-02 10:25:01,312 [prior] Evaluating prior at array([0.28844739])
 2023-07-02 10:25:01,312 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,312 [model] Got input parameters: {'Omega_m': 0.2884473855225448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,312 [classy] Got parameters {'Omega_m': 0.2884473855225448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,312 [classy] Computing new state
 2023-07-02 10:25:01,312 [classy] Setting parameters: {'Omega_m': 0.2884473855225448, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.25525320207984}
 2023-07-02 10:25:01,361 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0378677
 2023-07-02 10:25:01,362 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,362 [mcmc] New sample, #518:
   Omega_m:0.4112357
 2023-07-02 10:25:01,363 [model] Posterior to be computed for parameters {'Omega_m': 0.26974919374554795}
 2023-07-02 10:25:01,363 [prior] Evaluating prior at array([0.26974919])
 2023-07-02 10:25:01,363 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,363 [model] Got input parameters: {'Omega_m': 0.26974919374554795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,363 [classy] Got parameters {'Omega_m': 0.26974919374554795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,363 [classy] Computing new state
 2023-07-02 10:25:01,363 [classy] Setting parameters: {'Omega_m': 0.26974919374554795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.7386889689358}
 2023-07-02 10:25:01,411 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125333
 2023-07-02 10:25:01,413 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,413 [mcmc] New sample, #519:
   Omega_m:0.2884474
 2023-07-02 10:25:01,413 [model] Posterior to be computed for parameters {'Omega_m': 0.330175272371908}
 2023-07-02 10:25:01,413 [prior] Evaluating prior at array([0.33017527])
 2023-07-02 10:25:01,413 [prior] Got logpriors (internal) = 0.10536051565782628
 2023-07-02 10:25:01,413 [model] Got input parameters: {'Omega_m': 0.330175272371908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,413 [classy] Got parameters {'Omega_m': 0.330175272371908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:25:01,413 [classy] Computing new state
 2023-07-02 10:25:01,413 [classy] Setting parameters: {'Omega_m': 0.330175272371908, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:25:01,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.18332575071275}
 2023-07-02 10:25:01,461 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:25:01,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185819
 2023-07-02 10:25:01,462 [model] Computed derived parameters: {}
 2023-07-02 10:25:01,463 [mcmc] New sample, #520:
   Omega_m:0.2697492
 2023-07-02 10:25:01,463 [mcmc] Learn + convergence test @ 520 samples accepted.
 2023-07-02 10:25:01,463 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:25:01,467 [mcmc]  - Acceptance rate: 0.411
 2023-07-02 10:25:01,468 [mcmc]  - Condition number = 1
 2023-07-02 10:25:01,468 [mcmc]  - Eigenvalues = array([0.01206916])
 2023-07-02 10:25:01,468 [mcmc]  - Convergence of means: R-1 = 0.012069 after 416 accepted steps
 2023-07-02 10:25:01,473 [mcmc]  - normalized std's of bounds = array([[0.13696813],
       [0.18262798]])
 2023-07-02 10:25:01,473 [mcmc]  - Convergence of bounds: R-1 = 0.182628 after 520 accepted steps
 2023-07-02 10:25:01,474 [mcmc] The run has converged!
 2023-07-02 10:25:01,483 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:25:01,485 [mcmc] Sampling complete after 520 accepted steps.
In [22]:
# To load Cobaya samples from disk
from getdist.mcsamples import loadMCSamples
samples_bao_cobaya = loadMCSamples('_tests/chains_bao_cobaya/chain', settings={'ignore_rows': 0.5}).copy(label='cobaya')

g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike],
                 params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
[000150.02] [0/1] 07-02 10:25  root                      WARNING  outlier fraction 0.11923076923076924

CosmoSIS¶

Let's apply the static bindings to CosmoSIS. The BAOLikelihood definition is exactly the same, we just need to generate new files with a simple CosmoSISLikelihoodGenerator call.

In [23]:
%%file _tests/bao_likelihood.py

dirname = '.'

# The same as for Cobaya!
def BAOLikelihood(cosmo='external'):
    import numpy as np
    from desilike.observables.galaxy_clustering import BAOCompressionObservable
    from desilike.likelihoods import ObservablesGaussianLikelihood
    # cosmo = 'external' to tell desilike that cosmo will be provided externally
    observable1 = BAOCompressionObservable(data=[1., 1.], quantities=['qpar', 'qper'], z=0.5, cosmo=cosmo)
    observable2 = BAOCompressionObservable(data=[1.], quantities=['qiso'], z=1., cosmo=cosmo)
    likelihood = ObservablesGaussianLikelihood([observable1, observable2],
                                               covariance=np.diag([0.002, 0.002, 0.005]))
    return likelihood

if __name__ == '__main__':
    from desilike.bindings import CobayaLikelihoodGenerator, CosmoSISLikelihoodGenerator, MontePythonLikelihoodGenerator
    CobayaLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
    # The only change!
    CosmoSISLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
    # Let's directly generate the bindings for MontePython
    MontePythonLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
Overwriting _tests/bao_likelihood.py

Let's generate the static bindings by calling the above Python script

In [24]:
%%bash
cd _tests
python bao_likelihood.py
bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by bash)
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)

Let's take a look at the generated files:

  • the likelihood module: BAOLikelihood.py
  • the *values.ini file containing the values / ranges of nuisance parameters (none in this case), to be copy-pasted in the input *values.ini (see below)
  • the *priors.ini file containing the optional priors of nuisance parameters, to be copy-pasted in the input *priors.ini file
In [25]:
ls -la _tests/cosmosis
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 20
drwxr-xr-x 2 adematti idphp 4096 juil.  2 10:25 ./
drwxr-xr-x 7 adematti idphp 4096 juil.  2 10:25 ../
-rw-r--r-- 1 adematti idphp    7 juil.  2 10:25 BAOLikelihood_priors.ini
-rw-r--r-- 1 adematti idphp  543 juil.  2 10:25 BAOLikelihood.py
-rw-r--r-- 1 adematti idphp    7 juil.  2 10:25 BAOLikelihood_values.ini

Now let's write the config file to run inference. This is pure CosmoSIS.

In [26]:
%%file _tests/config_bao.ini

[DEFAULT]
fatal_errors = T

[runtime]
sampler = emcee

[output]
filename = _tests/chains_bao_cosmosis/chain.txt
format = text
verbosity = 0

[pipeline]
modules = consistency camb bao
values = _tests/values_bao.ini
likelihoods = BAOLikelihood  ; notice the name of the liklelihood: the same as the *.py file
quiet = T
debug = F
timing = F

[consistency]
file = ${COSMOSIS_STD_DIR}/utility/consistency/consistency_interface.py

[camb]
file = ${COSMOSIS_STD_DIR}/boltzmann/camb/camb_interface.py
mode = background
feedback = 0
nz = 901

[bao]
file = _tests/cosmosis/BAOLikelihood.py

[emcee]
walkers = 6
samples = 600
nsteps = 20
Writing _tests/config_bao.ini

The *values.ini file containing parameter values and ranges

In [27]:
%%file _tests/values_bao.ini

[cosmological_parameters]

; This is the only parameter being varied.
omega_m = 0.1 0.3 0.9
ombh2 = 0.02237
h0 = 0.6736
A_s = 2.083e-09
n_s = 0.9649
tau = 0.0544

mnu = 0.06
nnu = 3.046
num_massive_neutrinos = 1
omega_k = 0.0
w = -1.0
wa = 0.0
Writing _tests/values_bao.ini

Let's sample!

In [28]:
!cosmosis _tests/config_bao.ini
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)

Parameter Priors
----------------
cosmological_parameters--omega_m                ~ U(0.1, 0.9)
cosmological_parameters--ombh2                  ~ delta(0.02237)
cosmological_parameters--h0                     ~ delta(0.6736)
cosmological_parameters--a_s                    ~ delta(2.083e-09)
cosmological_parameters--n_s                    ~ delta(0.9649)
cosmological_parameters--tau                    ~ delta(0.0544)
cosmological_parameters--mnu                    ~ delta(0.06)
cosmological_parameters--nnu                    ~ delta(3.046)
cosmological_parameters--num_massive_neutrinos  ~ delta(1)
cosmological_parameters--omega_k                ~ delta(0.0)
cosmological_parameters--w                      ~ delta(-1.0)
cosmological_parameters--wa                     ~ delta(0.0)

****************************
* Running sampler 1/1: emcee
* Saving output -> _tests/chains_bao_cosmosis/chain.txt
****************************
Begun sampling
Done 20 iterations of emcee. Acceptance fraction 0.958
Done 40 iterations of emcee. Acceptance fraction 0.904
Done 60 iterations of emcee. Acceptance fraction 0.856
Done 80 iterations of emcee. Acceptance fraction 0.844
Done 100 iterations of emcee. Acceptance fraction 0.835
Done 120 iterations of emcee. Acceptance fraction 0.835
Done 140 iterations of emcee. Acceptance fraction 0.820
Done 160 iterations of emcee. Acceptance fraction 0.806
Done 180 iterations of emcee. Acceptance fraction 0.804
Done 200 iterations of emcee. Acceptance fraction 0.817
Done 220 iterations of emcee. Acceptance fraction 0.809
Done 240 iterations of emcee. Acceptance fraction 0.806
Done 260 iterations of emcee. Acceptance fraction 0.805
Done 280 iterations of emcee. Acceptance fraction 0.807
Done 300 iterations of emcee. Acceptance fraction 0.806
Done 320 iterations of emcee. Acceptance fraction 0.801
Done 340 iterations of emcee. Acceptance fraction 0.801
Done 360 iterations of emcee. Acceptance fraction 0.807
Done 380 iterations of emcee. Acceptance fraction 0.804
Done 400 iterations of emcee. Acceptance fraction 0.806
Done 420 iterations of emcee. Acceptance fraction 0.806
Done 440 iterations of emcee. Acceptance fraction 0.805
Done 460 iterations of emcee. Acceptance fraction 0.808
Done 480 iterations of emcee. Acceptance fraction 0.808
Done 500 iterations of emcee. Acceptance fraction 0.810
Done 520 iterations of emcee. Acceptance fraction 0.808
Done 540 iterations of emcee. Acceptance fraction 0.807
Done 560 iterations of emcee. Acceptance fraction 0.808
Done 580 iterations of emcee. Acceptance fraction 0.808
Done 600 iterations of emcee. Acceptance fraction 0.806
In [29]:
# To load CosmoSIS samples from disk
from cosmosis import Inifile
from cosmosis.output import input_from_options
from getdist import MCSamples

ini = Inifile('_tests/config_bao.ini')
options = dict(ini.items('output'))
options['filename'] = '_tests/chains_bao_cosmosis/chain.txt'
column_names, data = input_from_options(options)[:2]
#print(column_names)
data = data[0].T
data = data[..., data.shape[-1] // 2:]  # removing burnin
samples_bao_cosmosis = MCSamples(samples=[data[0]], weights=None, loglikes=-data[-1],
                                 names=['Omega_m'], label='cosmosis')

g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike, samples_bao_cosmosis],
                 params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
LOADING CHAIN FROM FILE:  _tests/chains_bao_cosmosis/chain.txt

MontePython¶

MontePython is not a Python package, so is not installed in the cosmodesi environment.

Let's install it locally! (it may take some time to download, because of the data sets).

In [30]:
%%bash
cd _tests/
git clone https://github.com/brinckmann/montepython_public.git
bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by bash)
Cloning into 'montepython_public'...
Updating files: 100% (1492/1492), done.

We write the .conf file that specifies the path to the Boltzman code Class and Planck likelihoods.

In [31]:
%%file _tests/montepython_public/default.conf

import os
path['cosmo'] = os.getenv('CLASS_STD_DIR')
path['clik'] = os.path.join(os.getenv('PLANCK_SRC_DIR'), 'code', 'plc_3.0', 'plc-3.1')
Writing _tests/montepython_public/default.conf

Let's take a look at the files previously generated by the static bindings:

  • the package: BAOLikelihood
  • with a (mandatory) *.data file specifying the likelihood name and nuisance parameter priors
  • with *.param file specifying parameter ranges, to be copy-pasted in the input .param file (see below)
  • with the __init__.py file containing the likelihood definition

As required by MontePython, we copy all this to the montepython/likelihoods directory.

In [32]:
!ls -la _tests/montepython/BAOLikelihood
!cp -r _tests/montepython/BAOLikelihood _tests/montepython_public/montepython/likelihoods/
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 20
drwxr-xr-x 2 adematti idphp 4096 juil.  2 10:25 .
drwxr-xr-x 3 adematti idphp 4096 juil.  2 10:25 ..
-rw-r--r-- 1 adematti idphp   35 juil.  2 10:25 BAOLikelihood.data
-rw-r--r-- 1 adematti idphp   52 juil.  2 10:25 BAOLikelihood.param
-rw-r--r-- 1 adematti idphp  502 juil.  2 10:25 __init__.py
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)

Now let's write the config file to run inference. This is pure MontePython.

In [33]:
%%file _tests/conf_bao.param

data.experiments = ['BAOLikelihood']

#------ Parameter list -------
# data.parameters[class name] = [mean, min, max, 1-sigma, scale, role]

# Cosmological parameters list
data.parameters['Omega_m'] = [0.3, 0.1, 0.9, 0.1, 1., 'cosmo']
# Fixed parameters
data.parameters['omega_b'] = [0.02237, 0.001, 0.1, 0., 1., 'cosmo']
data.parameters['H0'] = [67.36, 0.1, 0.9, 0., 1., 'cosmo']
data.parameters['A_s'] = [2.083e-09, 1e-09, 3e-09, 0., 1., 'cosmo']
data.parameters['n_s'] = [0.9649, 0.9, 1.0, 0., 1., 'cosmo']
data.parameters['tau_reio'] = [0.0544, 0.02, 0.1, 0., 1., 'cosmo']

# Cosmo arguments
data.cosmo_arguments['k_pivot'] = 0.05
data.cosmo_arguments['N_ur'] = 2.0328
data.cosmo_arguments['N_ncdm'] = 1
data.cosmo_arguments['m_ncdm'] = 0.06
data.cosmo_arguments['T_ncdm'] = 0.71611

#------ MCMC parameters ----
data.N = 3000
data.write_step = 5
Writing _tests/conf_bao.param

Let's sample!

In [34]:
!python _tests/montepython_public/montepython/MontePython.py run --conf _tests/montepython_public/default.conf -p _tests/conf_bao.param -o _tests/chains_bao_montepython
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
 /!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
     safely ignore this if not running with option -m NS
Running Monte Python v3.6.0

with CLASS v3.2.0

Testing likelihoods for:
 ->BAOLikelihood

WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Creating _tests/chains_bao_montepython/2023-07-02_3000__1.txt


Deduced starting covariance matrix:

['Omega_m']
[[0.01]]
Update routine is enabled with value 50 (recommended: 50)
This number is rescaled by cycle length 1 (N_slow + f_fast * N_fast) to 50

#  -LogLkl	Omega_m
 /!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
     safely ignore this if not running with option -m NS
1  0.474813	4.139400e-01
6  0.0393078	3.415106e-01
1  0.0795065	3.530712e-01
1  0.299953	3.918899e-01
1  0.28913	3.903726e-01
1  1.88732	5.363267e-01
3  1.75998	5.269886e-01
1  0.353307	2.459891e-01
1  0.00723461	3.045927e-01
2  0.156011	3.691783e-01
1  0.207845	2.610078e-01
1  0.743891	4.424003e-01
9  0.099125	2.769897e-01
1  1.45946e-05	3.148490e-01
5  0.390573	2.427618e-01
2  0.322765	3.950166e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 8 steps
 /!\ Convergence computed for a single file
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.023861 	for  Omega_m
--> Not computing covariance matrix
3  0.00225593	3.092987e-01
 /!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
     safely ignore this if not running with option -m NS
2  0.178771	3.732351e-01
2  1.05338	2.030995e-01
2  0.0636985	2.842953e-01
4  0.00297849	3.223716e-01
2  0.325495	2.485320e-01
1  0.692487	4.373065e-01
2  0.346225	3.981394e-01
1  1.82164	5.315325e-01
4  2.01188	5.452945e-01
1  3.12612	6.203877e-01
1  0.0593596	2.853300e-01
1  0.183125	3.739850e-01
2  0.0197739	2.977335e-01
9  0.133208	2.712282e-01
1  0.72976	4.410130e-01
1  0.458166	4.119994e-01
1  2.89561	1.464973e-01
1  0.025582	3.363208e-01
7  0.343765	2.468476e-01
1  0.34691	3.982291e-01
1  0.494095	4.161551e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 18 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.588647 	for  Omega_m
--> Computing covariance matrix
3  0.100762	2.766899e-01
1  0.188175	2.634665e-01
1  0.0875733	2.791871e-01
3  0.000951407	3.114031e-01
After 42 accepted steps: update proposal with max(R-1) = 0.588647 and jumping factor = 2.400000

3  1.25691	4.879438e-01
1  0.0289588	3.377001e-01
5  0.117842	2.737100e-01
3  0.468053	4.131552e-01
2  0.170546	2.657972e-01
4  0.181677	3.737364e-01
1  0.500153	4.168440e-01
1  0.586944	2.282463e-01
7  0.00574804	3.251461e-01
1  0.24628	3.841182e-01
4  1.13643	4.779182e-01
2  1.08646	2.016194e-01
1  0.364993	2.449561e-01
1  1.3481	4.953290e-01
1  0.129411	2.718260e-01
2  1.47855	5.056334e-01
1  2.73758	1.500770e-01
4  2.57229	5.840266e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 31 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.022824 	for  Omega_m
--> Not computing covariance matrix
3  3.5438	6.469228e-01
1  4.1455	6.841766e-01
3  3.76552	6.607680e-01
1  4.56484	7.096253e-01
5  0.00827158	3.271341e-01
2  0.501024	2.341626e-01
1  0.576046	4.252202e-01
1  0.317311	3.942774e-01
1  0.857011	2.125812e-01
1  0.256071	2.554962e-01
1  0.0980799	3.574608e-01
7  0.349695	3.985939e-01
3  0.0267513	3.368077e-01
4  1.1034	4.751108e-01
1  2.50396	5.794242e-01
1  5.05559	7.390040e-01
2  1.11115	4.757719e-01
3  0.369159	2.445927e-01
8  0.145495	2.693563e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 38 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.057315 	for  Omega_m
--> Not computing covariance matrix
3  0.312185	3.935780e-01
4  0.852413	4.527595e-01
1  0.358453	3.997328e-01
1  0.0515435	3.454487e-01
1  0.000254286	3.132960e-01
7  0.221287	3.802581e-01
1  0.786015	4.464814e-01
1  0.00922449	3.032265e-01
20  0.013582	3.305179e-01
10  0.571653	4.247473e-01
1  0.477118	4.142066e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 46 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.014075 	for  Omega_m
--> Not computing covariance matrix
4  0.183305	2.640975e-01
1  0.209575	2.607980e-01
1  0.356327	3.994574e-01
2  0.00308832	3.082821e-01
5  0.0821669	2.802700e-01
7  1.25136	1.946550e-01
1  0.00122202	3.108823e-01
2  1.47679	5.054965e-01
1  0.124357	3.630752e-01
6  2.48395	5.780714e-01
3  2.29763	5.653394e-01
1  1.95267	5.410507e-01
2  0.521699	4.192688e-01
7  0.451156	2.378865e-01
6  0.337461	2.474226e-01
1  0.0491255	3.447082e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 53 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.008688 	for  Omega_m
--> Not computing covariance matrix
5  0.0133081	3.303611e-01
1  0.012032	3.015364e-01
3  0.0910879	3.558566e-01
10  0.0807114	3.533692e-01
3  0.0107104	3.023033e-01
1  1.18699	4.821654e-01
1  0.721041	4.401523e-01
4  0.626034	4.305109e-01
1  0.27161	3.878657e-01
1  0.375147	4.018733e-01
1  0.132493	2.713401e-01
3  0.0113417	3.019312e-01
4  0.0607866	2.849854e-01
1  0.161704	3.702159e-01
1  6.98359e-07	3.153832e-01
4  0.204936	3.776317e-01
5  0.05585	2.861970e-01
2  0.0227956	3.351161e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 61 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.012612 	for  Omega_m
--> Not computing covariance matrix
4  0.000320701	3.130461e-01
3  0.439463	4.097857e-01
1  0.92247	4.592000e-01
2  0.172153	3.720798e-01
6  0.0789282	3.529274e-01
1  1.05787	2.028968e-01
7  0.151481	2.684763e-01
3  0.280092	3.890875e-01
7  0.323614	3.951311e-01
1  0.467371	4.130758e-01
1  0.39934	2.420294e-01
1  2.41574	5.734377e-01
2  1.35641	4.959945e-01
2  0.0100308	3.283481e-01
6  0.0257057	2.953291e-01
2  1.36662	1.901459e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 71 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.013018 	for  Omega_m
--> Not computing covariance matrix
2  0.807091	4.484939e-01
1  0.694389	4.374973e-01
4  0.146348	2.692298e-01
6  0.297834	3.915947e-01
1  0.0001866	3.170777e-01
5  0.209697	3.784055e-01
1  0.019251	2.979625e-01
2  0.15927	3.697743e-01
1  0.341062	3.974596e-01
2  0.0407708	2.903046e-01
3  0.988732	4.651398e-01
1  0.873229	4.546918e-01
1  1.22114	4.850004e-01
2  0.200939	3.769762e-01
1  0.050699	2.875244e-01
3  0.134565	3.651112e-01
7  0.0340365	2.924023e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 78 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.010444 	for  Omega_m
--> Not computing covariance matrix
10  0.00204349	3.095876e-01
4  0.325655	3.954061e-01
1  0.0650389	2.839835e-01
4  0.000180561	3.136159e-01
3  0.0223833	3.349320e-01
1  0.262539	3.865413e-01
2  0.345941	3.981021e-01
4  0.0595406	3.477901e-01
1  0.382878	2.434126e-01
5  1.32151	1.918790e-01
1  0.0442547	2.892916e-01
1  1.2614	1.942512e-01
3  1.78489	5.288293e-01
1  0.0753482	3.520266e-01
2  0.649254	2.242833e-01
1  0.309715	3.932392e-01
2  1.03558	4.692578e-01
1  0.0923101	3.561410e-01
4  0.138947	3.659642e-01
1  0.16861	2.660613e-01
2  0.350048	2.462807e-01
1  0.209048	2.608618e-01
3  0.0570426	2.858992e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 91 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.014294 	for  Omega_m
--> Not computing covariance matrix
1  1.3972	4.992421e-01
1  0.00125824	3.198919e-01
4  0.4439	4.103141e-01
2  0.262001	3.864621e-01
6  0.0181291	3.329285e-01
1  0.504431	4.173286e-01
4  0.839287	4.515325e-01
1  0.542182	2.312567e-01
2  0.0980431	3.574525e-01
2  2.72639	5.943039e-01
3  0.26165	3.864104e-01
1  0.551642	2.306081e-01
1  0.245633	2.566347e-01
1  0.354891	3.992710e-01
1  0.00279075	3.221441e-01
2  0.0587136	3.475550e-01
2  0.0849594	3.544041e-01
1  0.0491583	3.447184e-01
1  0.0148282	3.000466e-01
6  0.491544	4.158640e-01
2  0.33222	3.962859e-01
2  0.0432573	3.428373e-01
1  0.197561	2.622759e-01
1  0.647921	2.243656e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 101 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.012042 	for  Omega_m
--> Not computing covariance matrix
2  0.513264	4.183243e-01
2  0.181015	2.643975e-01
1  0.625637	4.304696e-01
2  0.0369121	2.914818e-01
1  0.147983	3.676866e-01
2  0.0180662	3.328973e-01
1  0.0252194	3.361677e-01
3  0.253706	2.557518e-01
2  0.46576	2.367712e-01
4  0.00408146	3.072383e-01
1  2.35757	5.694613e-01
1  0.596201	4.273733e-01
1  2.47329	5.773491e-01
3  2.36459	5.699424e-01
6  0.00751828	3.265761e-01
3  0.351308	3.988044e-01
2  0.0146861	3.311350e-01
4  0.0159122	2.995088e-01
3  0.0733397	3.515126e-01
3  1.01977	4.678749e-01
1  2.06882	1.671894e-01
1  3.13412	1.413653e-01
1  0.206706	3.779203e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 113 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.003573 	for  Omega_m
--> Not computing covariance matrix
3  1.18644	4.821194e-01
4  0.188993	2.633614e-01
2  0.0800009	2.807147e-01
4  0.0501528	3.450249e-01
1  0.844495	2.132314e-01
4  1.43926	5.025606e-01
4  2.70493	5.928809e-01
1  3.24256	6.278513e-01
1  1.91245	5.381489e-01
1  1.25135	4.874881e-01
4  0.427701	4.083747e-01
1  0.424557	2.399752e-01
1  0.77294	2.170724e-01
1  0.226588	3.810916e-01
1  0.1057	3.591515e-01
1  0.243631	3.837174e-01
2  0.388765	4.035911e-01
1  0.499568	2.342681e-01
1  0.14421	3.669733e-01
1  0.0014393	3.105053e-01
1  1.59888	1.817924e-01
3  3.62302	6.518870e-01
3  6.90786	8.475028e-01
1  5.86501	7.867665e-01
1  4.11186	6.821189e-01
2  1.54258	5.105893e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 126 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.012110 	for  Omega_m
--> Not computing covariance matrix
2  2.26425	5.630319e-01
2  1.30822	4.921189e-01
8  0.00751576	3.265742e-01
1  0.277417	3.887039e-01
5  0.523544	4.194746e-01
1  0.034429	3.397820e-01
1  0.114689	2.742411e-01
4  0.419521	2.403796e-01
5  2.05249	5.481861e-01
1  0.383385	2.433696e-01
1  0.314184	3.938514e-01
5  0.200438	2.619174e-01
4  0.613286	4.291772e-01
1  0.0614054	3.483147e-01
1  0.49288	2.347549e-01
1  7.18536e-05	3.142497e-01
1  0.360819	4.000386e-01
2  0.163498	2.667670e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 136 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002955 	for  Omega_m
--> Not computing covariance matrix
9  0.029568	2.939182e-01
4  0.254147	3.852988e-01
1  0.494946	2.346040e-01
2  1.1046	4.752128e-01
2  1.34156	4.948048e-01
1  2.82246	6.006443e-01
3  2.52693	5.809749e-01
3  3.92687	6.707538e-01
2  0.719968	4.400461e-01
3  2.28468	1.612714e-01
4  0.130856	3.643796e-01
2  0.446371	2.382566e-01
2  0.0270846	3.369446e-01
1  1.35048	4.955198e-01
1  0.7865	4.465279e-01
6  0.896316	4.568163e-01
1  0.811587	4.489208e-01
5  0.0976615	3.573663e-01
1  0.00350047	3.078308e-01
1  0.260144	2.550592e-01
1  0.999515	2.055769e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 146 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.006254 	for  Omega_m
--> Not computing covariance matrix
5  0.786336	4.465122e-01
2  0.595072	2.277150e-01
3  0.342118	3.975991e-01
1  0.937114	4.605250e-01
1  0.823419	4.500402e-01
3  0.0897097	3.555339e-01
1  0.403261	2.417051e-01
1  0.149011	2.688371e-01
4  0.0237775	3.355482e-01
1  0.0709773	2.826418e-01
8  0.00111676	3.196262e-01
4  0.105656	2.758093e-01
1  0.105236	2.758840e-01
1  0.128951	2.718991e-01
2  1.26844	4.888870e-01
1  0.47164	4.135722e-01
1  0.0975079	3.573316e-01
2  0.388047	4.035011e-01
3  0.458669	2.373100e-01
1  0.556858	2.302534e-01
2  0.517735	4.188256e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 156 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002632 	for  Omega_m
--> Not computing covariance matrix
10  0.4411	4.099810e-01
1  1.26001	1.943070e-01
1  1.22405	4.852409e-01
4  0.398659	4.048241e-01
2  0.0404754	3.419090e-01
1  0.00808812	3.039856e-01
2  0.462908	2.369872e-01
2  1.11761	4.763210e-01
2  2.08752	5.506684e-01
2  3.66558	6.545463e-01
1  1.34202	4.948415e-01
2  0.517139	4.187588e-01
2  0.259771	2.550991e-01
2  1.12777	4.771846e-01
5  0.0163229	2.993100e-01
1  3.101	6.187709e-01
1  2.28368	5.643761e-01
2  0.680392	4.360882e-01
3  0.00751917	3.043864e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 166 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001434 	for  Omega_m
--> Not computing covariance matrix
10  0.0075292	3.043792e-01
1  2.76192	5.966550e-01
1  0.914857	4.585086e-01
1  0.00806588	3.269843e-01
1  0.192076	2.629676e-01
2  0.69958	4.380174e-01
2  1.44488	5.030014e-01
11  0.0172833	3.325043e-01
1  0.421314	4.076023e-01
1  0.0987157	2.770651e-01
1  0.537941	4.210713e-01
7  0.774483	4.453722e-01
1  1.9055	1.719697e-01
1  0.245642	2.566338e-01
1  0.498224	4.166250e-01
2  0.682567	4.363078e-01
3  0.711594	2.205497e-01
1  0.196399	3.762251e-01
2  0.117776	2.737210e-01
5  0.0466395	3.439291e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 176 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002016 	for  Omega_m
--> Not computing covariance matrix
2  0.508603	2.336168e-01
2  0.570257	2.293514e-01
2  0.348892	2.463845e-01
1  0.395678	2.423342e-01
1  1.29402	4.909693e-01
3  1.12205	4.766986e-01
1  2.16659	5.562321e-01
5  0.188586	3.749147e-01
7  0.111062	3.603086e-01
6  0.030132	3.381613e-01
5  0.0230212	3.352162e-01
5  1.23766	1.952094e-01
4  0.00277572	3.086453e-01
5  0.351776	3.988656e-01
1  0.816069	4.493454e-01
1  0.603415	4.281373e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 183 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002785 	for  Omega_m
--> Not computing covariance matrix
1  0.776958	4.456107e-01
5  0.37336	4.016460e-01
1  1.19235	4.826120e-01
1  1.09345	4.742592e-01
1  5.53162	7.671793e-01
1  0.405279	4.056423e-01
1  0.156564	2.677443e-01
7  0.224149	3.807091e-01
2  0.198556	3.765828e-01
1  0.00469089	3.241871e-01
1  0.240375	3.832218e-01
2  4.77555	7.222868e-01
1  0.327396	3.956401e-01
5  0.00412346	3.236284e-01
2  1.44871	5.033016e-01
2  0.424143	4.079450e-01
3  3.81524	6.638524e-01
5  0.127442	3.636981e-01
6  0.617053	4.295724e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 193 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.005483 	for  Omega_m
--> Not computing covariance matrix
6  0.653698	4.333708e-01
3  0.752894	4.432794e-01
1  4.91985	7.309147e-01
1  4.5912	7.112135e-01
1  4.42611	7.012458e-01
1  4.23959	6.899186e-01
1  4.8337	7.257677e-01
2  2.13213	5.538138e-01
5  0.0117547	3.016935e-01
2  1.24867	4.872684e-01
3  0.0474251	2.884061e-01
1  0.339824	2.472063e-01
1  1.03037	2.041473e-01
2  0.460249	2.371895e-01
1  0.203203	2.615757e-01
1  0.887963	4.560499e-01
1  0.917637	2.095151e-01
2  0.0141659	3.003853e-01
1  1.00072	4.662000e-01
1  2.0052	5.448179e-01
4  0.0112167	3.291087e-01
2  0.108154	2.753685e-01
3  2.1695e-05	3.147404e-01
1  3.11629	6.197556e-01
1  1.52218	5.090173e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 206 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002215 	for  Omega_m
--> Not computing covariance matrix
7  0.203942	3.774691e-01
2  0.233189	2.580292e-01
9  0.0163438	3.320212e-01
2  0.0968059	2.774191e-01
5  0.428725	2.396429e-01
2  0.360754	4.000302e-01
4  1.70509	1.782511e-01
4  0.687794	2.219497e-01
4  0.0452537	3.434864e-01
3  0.197286	3.763724e-01
1  0.397479	4.046777e-01
2  0.232068	3.819447e-01
1  1.27041	1.938909e-01
2  0.0150196	3.313170e-01
1  0.0141672	3.308479e-01
2  0.75807	4.437830e-01
2  0.269964	3.876268e-01
1  0.570635	2.293262e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 216 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001961 	for  Omega_m
--> Not computing covariance matrix
7  0.539663	4.212611e-01
2  0.649545	4.329443e-01
3  0.00163021	3.205271e-01
1  0.0900658	3.556175e-01
2  0.872713	2.117740e-01
1  1.83671	5.326370e-01
2  0.668862	4.349193e-01
2  1.02095	4.679784e-01
1  0.383577	4.029396e-01
1  0.0156544	2.996350e-01
1  0.333283	2.478072e-01
1  0.39869	4.048280e-01
1  1.09513	4.744030e-01
2  0.752792	4.432694e-01
3  0.133339	2.712077e-01
3  1.35051	4.955224e-01
1  1.39073	4.987287e-01
2  0.728477	4.408866e-01
2  0.611484	4.289878e-01
4  0.119169	2.734889e-01
4  0.0145101	3.310382e-01
2  0.116449	3.614463e-01
1  1.04116	2.036541e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 226 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001718 	for  Omega_m
--> Not computing covariance matrix
4  0.283013	2.526765e-01
1  0.160367	2.672054e-01
1  0.484066	4.150072e-01
2  0.166189	2.663940e-01
1  0.401829	2.418234e-01
2  0.187649	2.635341e-01
1  1.28474	4.902151e-01
1  1.78847	1.755776e-01
1  0.0264516	2.950484e-01
1  0.284722	3.897480e-01
2  0.134574	2.710154e-01
1  2.89332	1.465481e-01
1  1.75971	5.269689e-01
1  1.66519	5.199151e-01
3  0.778512	2.167655e-01
3  0.15017	3.680964e-01
4  0.493265	4.160605e-01
1  1.01481	4.674402e-01
2  1.78427	1.757102e-01
3  0.575363	4.251468e-01
3  0.403042	2.417231e-01
2  0.0249811	3.360665e-01
5  0.38543	4.031726e-01
1  0.441805	4.100649e-01
2  0.977813	2.065997e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 238 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.005638 	for  Omega_m
--> Not computing covariance matrix
5  0.272451	3.879875e-01
3  0.105242	2.758829e-01
2  0.35021	2.462662e-01
1  0.0644234	3.491485e-01
1  0.859044	2.124761e-01
1  1.2312	1.954722e-01
1  0.211289	2.605911e-01
1  0.065296	2.839240e-01
3  0.0228044	3.351200e-01
2  0.0471449	2.884831e-01
1  0.0856935	2.795594e-01
2  0.124526	2.726096e-01
2  0.0738789	2.820083e-01
1  0.127072	2.721991e-01
3  0.00132006	3.107084e-01
6  0.157086	3.693754e-01
4  0.00995749	3.282997e-01
1  1.00883	4.669147e-01
2  0.0286103	2.942586e-01
10  0.364148	2.450302e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 248 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.008176 	for  Omega_m
--> Not computing covariance matrix
8  0.254939	2.556184e-01
1  0.0816166	2.803824e-01
2  0.014372	3.309618e-01
4  0.0849833	3.544098e-01
1  0.0642192	3.490928e-01
1  1.0754	4.727093e-01
1  0.504085	4.172895e-01
1  0.0981403	3.574745e-01
2  2.1483	5.549494e-01
1  0.127738	2.720924e-01
1  0.174966	3.725731e-01
4  0.338054	3.970618e-01
2  1.34311	4.949293e-01
1  2.7658	5.969110e-01
3  3.77924	6.616199e-01
3  3.5434	6.468974e-01
1  3.42058	6.391611e-01
1  0.941397	4.609111e-01
2  1.19273	4.826435e-01
1  0.154451	3.688911e-01
1  0.582787	4.259434e-01
2  0.722639	4.403103e-01
4  0.0758062	3.521429e-01
2  0.17061	3.718078e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 261 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.011500 	for  Omega_m
--> Not computing covariance matrix
3  0.0234621	2.962004e-01
1  1.57602	1.825761e-01
2  1.65856	5.194159e-01
2  1.32299	4.933116e-01
4  1.11826	4.763770e-01
2  0.180835	3.735916e-01
10  0.997893	2.056528e-01
3  0.00140772	3.105582e-01
1  2.14716	5.548701e-01
1  1.83325	5.323833e-01
3  2.04793	5.478620e-01
1  0.778838	4.457918e-01
4  0.669752	4.350098e-01
7  0.264359	2.546112e-01
1  0.213677	2.603045e-01
3  0.00496009	3.064189e-01
1  2.57671	5.843235e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 268 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.010806 	for  Omega_m
--> Not computing covariance matrix
6  1.1216	4.766606e-01
2  0.641362	4.321011e-01
3  0.00511521	3.245836e-01
1  0.355426	3.993405e-01
13  0.0259752	3.364857e-01
1  0.362495	4.002547e-01
8  0.120067	3.621975e-01
12  2.17598e-05	3.147396e-01
2  0.555249	4.229691e-01
2  0.22865	3.814138e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 273 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.010034 	for  Omega_m
--> Not computing covariance matrix
2  0.690802	4.371373e-01
1  0.126787	2.722448e-01
4  0.584171	4.260915e-01
1  0.00244828	3.217088e-01
5  0.677325	4.357780e-01
2  0.610494	4.288837e-01
4  0.71438	2.203878e-01
5  0.072036	2.824091e-01
2  0.313858	3.938068e-01
7  0.671158	2.229467e-01
1  0.261529	2.549116e-01
2  0.56816	4.243704e-01
2  0.194709	2.626342e-01
1  0.174827	2.652191e-01
2  0.486034	2.352573e-01
2  0.390921	4.038608e-01
4  0.401944	4.052308e-01
1  0.0340844	3.396556e-01
3  0.049118	2.879462e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 283 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.014493 	for  Omega_m
--> Not computing covariance matrix
3  0.231344	3.818326e-01
1  0.28055	2.529275e-01
1  0.63823	4.317774e-01
2  0.180386	2.644803e-01
1  0.0428224	2.897027e-01
2  0.0918531	2.783555e-01
4  0.16646	3.710707e-01
4  0.604514	2.271033e-01
3  0.975859	4.639967e-01
3  0.488541	4.155205e-01
1  0.432385	2.393526e-01
1  0.0820321	2.802975e-01
1  0.0819229	3.536668e-01
4  0.0080921	3.039829e-01
1  5.99784e-05	3.163163e-01
1  0.000710996	3.119333e-01
2  0.0752792	2.817075e-01
5  0.637574	4.317095e-01
1  0.444651	4.104033e-01
2  0.574466	2.290709e-01
1  0.427594	4.083617e-01
3  0.0493273	3.447707e-01
3  0.0238615	2.960422e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 296 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.012596 	for  Omega_m
--> Not computing covariance matrix
1  0.13082	3.643725e-01
3  0.0834025	2.800192e-01
3  2.02929	5.465362e-01
4  0.735836	4.416107e-01
1  1.881	5.358670e-01
6  0.00831282	3.271639e-01
5  0.00818463	3.039191e-01
2  0.319395	2.491067e-01
1  0.5905	4.267672e-01
1  0.265024	3.869060e-01
3  0.421209	2.402437e-01
6  0.420132	2.403303e-01
1  0.784703	2.164259e-01
2  0.0306036	3.383442e-01
2  0.368371	2.446612e-01
2  1.13545	4.778347e-01
1  0.315901	2.494388e-01
2  0.301911	3.921619e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 303 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.009642 	for  Omega_m
--> Not computing covariance matrix
5  0.860161	2.124185e-01
7  1.19555	4.828782e-01
3  0.447636	2.381585e-01
1  0.573903	4.249897e-01
5  0.115843	2.740457e-01
5  0.20136	3.770455e-01
3  1.25111	4.874682e-01
1  0.00234534	3.215722e-01
4  0.624055	4.303045e-01
1  0.373214	4.016274e-01
1  3.02819	1.436064e-01
2  0.674731	4.355152e-01
2  0.303496	3.923816e-01
3  0.928913	4.597838e-01
2  3.12428	6.202693e-01
3  3.03516	6.145185e-01
1  0.00583687	3.252226e-01
4  0.325603	3.953991e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 313 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.008670 	for  Omega_m
--> Not computing covariance matrix
2  1.09129	4.740742e-01
2  2.49164	5.785913e-01
1  5.57029	1.014163e-01
1  0.779307	2.167217e-01
1  0.630936	4.310210e-01
3  0.894469	4.566470e-01
7  0.178239	3.731429e-01
1  0.0104888	3.286467e-01
4  0.0785083	2.810250e-01
2  1.09894	4.747291e-01
3  1.11633	4.762122e-01
2  0.0612469	2.848751e-01
2  0.150767	3.682077e-01
1  0.190845	2.631244e-01
5  0.194011	2.627223e-01
1  0.416163	2.406507e-01
2  0.0254246	3.362544e-01
1  0.0830982	3.539537e-01
1  0.0455604	2.889230e-01
1  0.197756	2.622515e-01
7  0.150393	3.681380e-01
1  0.0940731	2.779325e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 323 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.009038 	for  Omega_m
--> Not computing covariance matrix
2  0.5898	2.280590e-01
4  0.414169	2.408124e-01
1  0.113705	2.744086e-01
2  0.0273826	3.370663e-01
1  0.281006	2.528810e-01
8  0.115307	3.612070e-01
3  0.0164922	3.320983e-01
2  0.286358	2.523374e-01
1  0.0872726	3.549578e-01
1  0.31414	3.938454e-01
1  0.0142068	3.308699e-01
2  0.145358	3.671911e-01
2  0.941177	4.608913e-01
1  0.106518	3.593299e-01
2  0.405674	4.056909e-01
3  0.0202212	3.339389e-01
2  4.04071e-05	3.161374e-01
1  0.00644329	3.257303e-01
1  0.00858483	3.273588e-01
5  0.497873	2.343910e-01
1  0.44339	4.102535e-01
2  0.901485	4.572892e-01
2  0.0629134	3.487337e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 336 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.011267 	for  Omega_m
--> Not computing covariance matrix
6  0.668258	4.348580e-01
4  0.000948626	3.192877e-01
3  0.0185938	3.331576e-01
2  0.911329	4.581875e-01
1  0.919847	2.094058e-01
3  0.303446	3.923747e-01
1  0.140602	3.662832e-01
1  0.0534381	2.868100e-01
1  0.16088	3.700667e-01
3  0.0571129	2.858818e-01
5  0.090623	3.557480e-01
1  1.07515	2.021221e-01
2  0.421422	4.076154e-01
2  0.229756	2.584213e-01
3  0.934478	2.086869e-01
1  1.20726	1.964543e-01
3  0.0932904	3.563678e-01
1  0.175563	2.651206e-01
7  0.31415	3.938466e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 346 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.008590 	for  Omega_m
--> Not computing covariance matrix
1  0.465492	4.128567e-01
4  0.0283262	2.943607e-01
1  0.183777	3.740967e-01
2  0.368168	4.009832e-01
1  1.03281	4.690158e-01
3  0.128103	2.720342e-01
5  0.0137038	3.305872e-01
3  0.335778	3.967597e-01
1  0.323749	2.486958e-01
1  0.465998	4.129158e-01
5  1.30602	4.919408e-01
1  1.41379	5.005548e-01
2  1.72051	5.240572e-01
3  2.18994	5.578650e-01
1  1.25356	4.876695e-01
1  3.2571	6.287792e-01
1  0.218132	3.797580e-01
1  0.0684429	3.502317e-01
3  0.127718	3.637533e-01
1  1.28881	4.905460e-01
2  0.0560583	3.467895e-01
1  2.07727	5.499431e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 356 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.006510 	for  Omega_m
--> Not computing covariance matrix
7  3.13474	6.209421e-01
5  1.66049	5.195610e-01
3  0.462587	2.370117e-01
1  0.0995947	2.769034e-01
5  0.433004	4.090127e-01
1  1.14183	4.783741e-01
1  0.110517	3.601922e-01
8  0.0993437	3.577452e-01
10  0.116871	2.738727e-01
2  0.120385	2.732873e-01
4  1.7163	5.237431e-01
3  0.114876	3.611166e-01
1  0.0428087	2.897067e-01
2  0.0132367	3.303201e-01
1  1.2643	4.885484e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 363 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002030 	for  Omega_m
--> Not computing covariance matrix
7  0.130033	3.642160e-01
3  0.0662502	3.496446e-01
6  0.0801564	3.532322e-01
4  0.465617	2.367819e-01
4  0.0795637	3.530854e-01
1  1.54466	1.836637e-01
2  1.07243	4.724532e-01
1  0.308439	3.930638e-01
4  2.04741	5.478251e-01
1  1.80031	1.752051e-01
5  0.0182989	2.983882e-01
6  0.00607355	3.054809e-01
2  0.129833	2.717590e-01
1  0.0890242	3.553726e-01
2  1.87099	5.351387e-01
2  0.656417	4.336494e-01
1  0.206007	3.778063e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 373 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004113 	for  Omega_m
--> Not computing covariance matrix
1  0.331682	2.479553e-01
5  0.135645	3.653227e-01
3  0.0821387	2.802757e-01
1  0.0467547	2.885907e-01
1  1.7498	5.262347e-01
2  1.58179	5.135944e-01
2  0.763527	4.443127e-01
5  0.0108054	3.288496e-01
2  0.320195	2.490309e-01
1  0.534776	2.317695e-01
1  0.154379	2.680573e-01
1  0.487653	2.351381e-01
3  0.43481	4.092292e-01
6  0.0170889	3.324054e-01
6  0.281224	3.892494e-01
7  0.573374	4.249327e-01
2  0.145123	3.671465e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 381 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002988 	for  Omega_m
--> Not computing covariance matrix
3  0.137601	2.705482e-01
4  0.00220777	3.093629e-01
6  0.0198201	3.337493e-01
1  0.545607	4.219147e-01
2  1.67666	1.791837e-01
5  0.0735498	3.515666e-01
2  2.37094	5.703774e-01
1  0.0155316	2.996954e-01
2  1.05048	4.705541e-01
1  0.0112235	3.020000e-01
2  0.754084	2.181221e-01
1  0.104255	3.588352e-01
2  0.159515	2.673256e-01
1  0.44587	4.105481e-01
3  0.269978	3.876287e-01
5  0.554114	4.228454e-01
2  0.562443	4.237514e-01
1  0.0668302	3.498007e-01
2  0.0173124	3.325190e-01
1  0.280876	3.891996e-01
1  0.126283	3.634649e-01
1  0.748312	2.184466e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 391 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002874 	for  Omega_m
--> Not computing covariance matrix
8  0.731079	4.411429e-01
1  0.269192	2.541025e-01
1  0.503442	4.172167e-01
3  0.787248	4.465996e-01
2  0.687458	2.219697e-01
3  0.670163	2.230068e-01
2  0.0857064	3.545836e-01
6  0.198487	2.621601e-01
2  0.3873	4.034075e-01
1  0.34943	3.985591e-01
1  1.02077	4.679633e-01
2  3.81475	6.638224e-01
1  2.96657	6.100672e-01
1  2.00352	5.446980e-01
4  1.9375	5.399581e-01
1  0.344665	3.979344e-01
1  0.261843	3.864389e-01
1  0.305474	2.504430e-01
2  0.331521	3.961926e-01
3  1.57403	5.130008e-01
5  1.70954	1.781063e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 403 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004318 	for  Omega_m
--> Not computing covariance matrix
2  1.29215	4.908169e-01
1  0.58245	2.285420e-01
3  0.0017443	3.100218e-01
1  0.0413529	3.422051e-01
6  0.0511629	3.453332e-01
2  3.23798	1.392241e-01
1  0.242497	3.835451e-01
6  0.0994406	3.577670e-01
2  0.456155	2.375022e-01
1  0.468812	2.365407e-01
1  0.0114305	3.018797e-01
1  0.128661	3.639423e-01
2  0.0596081	3.478092e-01
1  0.24293	3.836108e-01
5  0.0131393	3.302638e-01
2  0.617032	4.295701e-01
3  0.34826	3.984061e-01
2  0.251526	3.849072e-01
4  1.69938	5.224798e-01
1  0.0526227	3.457739e-01
1  0.67346	2.228078e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 413 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.006751 	for  Omega_m
--> Not computing covariance matrix
9  0.115315	3.612088e-01
1  1.32245	4.932675e-01
1  0.582808	4.259457e-01
3  1.48312	5.059889e-01
1  3.43485	6.400628e-01
1  3.14482	6.215901e-01
2  4.19877	6.874300e-01
1  5.38113	7.583013e-01
1  2.38908	5.716183e-01
2  0.919221	2.094368e-01
1  2.59749	5.857166e-01
8  2.51344	5.800647e-01
3  2.32901	5.675002e-01
1  1.0945	4.743497e-01
1  1.11783	4.763399e-01
2  0.503651	4.172405e-01
1  0.26536	3.869551e-01
2  0.677797	4.358258e-01
1  0.292696	2.517014e-01
4  0.22839	2.585783e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 423 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.005784 	for  Omega_m
--> Not computing covariance matrix
9  0.0359682	3.403391e-01
8  0.146831	3.674697e-01
1  0.0167309	3.322218e-01
1  0.122388	3.626739e-01
2  1.55208	1.834048e-01
2  1.95988	5.415696e-01
1  1.67199	5.204262e-01
3  1.54238	5.105736e-01
11  1.10816	2.006643e-01
6  0.275355	3.884070e-01
5  0.43189	4.088788e-01
1  0.162076	2.669656e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 428 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.008281 	for  Omega_m
--> Not computing covariance matrix
9  0.479777	2.357203e-01
5  0.169749	2.659057e-01
1  1.4048	4.998442e-01
2  0.952808	4.619370e-01
4  2.88661	6.048514e-01
1  2.44045	1.572497e-01
1  2.37634	5.707470e-01
1  1.72424	5.243352e-01
1  0.0268611	3.368529e-01
1  0.0793999	2.808393e-01
1  0.702353	2.210897e-01
1  0.0615876	3.483656e-01
2  0.400983	4.051119e-01
1  2.38156	5.711043e-01
8  0.0247191	2.957071e-01
4  0.242821	3.835943e-01
1  0.198833	3.766287e-01
2  0.894487	2.106700e-01
6  0.0198596	3.337680e-01
2  0.119403	3.620603e-01
1  1.17735	4.813600e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 438 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.010329 	for  Omega_m
--> Not computing covariance matrix
4  0.307056	2.502893e-01
1  0.605516	2.270388e-01
3  0.384945	4.031117e-01
2  0.495602	4.163268e-01
1  0.303019	2.506824e-01
5  0.0923693	3.561547e-01
1  0.0471375	2.884851e-01
2  0.232756	2.580784e-01
2  0.853	4.528142e-01
1  1.40472	4.998377e-01
4  0.658924	4.339060e-01
1  0.000580033	3.184206e-01
2  0.00382833	3.233229e-01
1  0.165991	2.664213e-01
5  0.179423	3.733479e-01
2  0.302488	2.507343e-01
3  3.60477e-06	3.151040e-01
2  0.0324616	3.390526e-01
2  0.00464023	3.067079e-01
2  0.162871	3.704268e-01
1  0.917294	4.587301e-01
1  0.304034	2.505832e-01
2  0.00736796	3.044955e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 451 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.007599 	for  Omega_m
--> Not computing covariance matrix
3  1.52834	5.094927e-01
1  0.934907	4.603257e-01
1  0.572071	4.247924e-01
1  1.78599	5.289109e-01
3  1.19849	4.831227e-01
1  1.56336	5.121842e-01
3  0.937709	4.605787e-01
9  0.000838413	3.190494e-01
1  0.138221	2.704534e-01
2  0.236844	2.576153e-01
7  0.0130188	3.009920e-01
2  1.51052	5.081157e-01
3  1.16498	4.803241e-01
4  0.000385819	3.128255e-01
2  1.98179	1.697017e-01
2  0.0775845	2.812187e-01
2  0.260869	2.549818e-01
4  0.39911	2.420486e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 461 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.005235 	for  Omega_m
--> Not computing covariance matrix
8  0.00300775	3.224065e-01
1  0.106084	3.592354e-01
1  0.280308	3.891183e-01
1  0.942164	4.609802e-01
2  1.52762	5.094367e-01
4  2.68023	1.514142e-01
2  0.00359212	3.230699e-01
1  0.921958	4.591536e-01
1  1.10115	4.749185e-01
1  1.22876	4.856303e-01
1  1.2502	4.873934e-01
2  0.836476	4.512689e-01
3  0.00878121	3.274976e-01
4  1.79017	5.292190e-01
1  1.71237	5.234502e-01
9  0.0371894	2.913951e-01
3  0.340138	2.471776e-01
4  0.11043	3.601736e-01
2  0.000304383	3.131049e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 468 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.003889 	for  Omega_m
--> Not computing covariance matrix
5  0.00338899	3.079501e-01
1  1.08684	2.016025e-01
1  1.43827	5.024822e-01
10  0.195391	2.625482e-01
1  0.273632	3.881584e-01
3  0.427459	4.083455e-01
2  0.115041	3.611513e-01
6  0.113097	2.745125e-01
1  1.45504	1.868585e-01
2  2.19999	1.635424e-01
1  2.20634	1.633700e-01
1  1.49985	1.852446e-01
1  2.60425	5.861692e-01
1  0.00737727	3.044888e-01
2  0.0358705	3.403041e-01
1  0.357224	2.456406e-01
4  0.0395208	3.415837e-01
1  0.111476	3.603970e-01
2  0.151554	3.683543e-01
2  0.694104	2.215755e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 478 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002684 	for  Omega_m
--> Not computing covariance matrix
3  0.64408	4.323817e-01
1  1.10285	4.750631e-01
2  0.0333957	3.394014e-01
2  0.413021	2.409057e-01
2  0.895893	4.567775e-01
1  1.09501	4.743933e-01
5  0.12251	2.729379e-01
3  0.101596	2.765382e-01
7  0.679611	4.360092e-01
2  0.0357243	3.402516e-01
2  0.925251	2.091394e-01
1  0.0187263	3.332224e-01
2  2.90194	6.058532e-01
1  3.49017	6.435509e-01
2  4.66406	7.155971e-01
1  4.20397	6.877473e-01
1  2.1506	5.551110e-01
3  1.8069	5.304500e-01
7  1.64515	1.802302e-01
1  1.42441	5.013925e-01
1  0.813194	4.490732e-01
2  0.0775374	3.525797e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 491 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004434 	for  Omega_m
--> Not computing covariance matrix
2  1.4476	5.032147e-01
1  1.81098	5.307495e-01
3  0.140515	3.662665e-01
1  0.205218	2.613282e-01
4  0.589396	4.266495e-01
1  1.42799	5.016742e-01
6  0.683212	4.363730e-01
3  0.0685717	3.502659e-01
2  0.264307	3.868009e-01
1  0.818835	4.496072e-01
2  0.0371768	2.913991e-01
3  0.0532811	3.459709e-01
4  0.018617	3.331690e-01
1  0.829924	4.506532e-01
3  0.431234	4.088001e-01
3  0.296483	2.513251e-01
2  0.0203049	3.339784e-01
7  0.374578	4.018009e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 498 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.003649 	for  Omega_m
--> Not computing covariance matrix
2  1.077	4.728465e-01
4  0.414521	4.067756e-01
2  0.541349	4.214468e-01
2  0.0980107	3.574452e-01
2  1.76335	5.272383e-01
1  3.44083	6.404402e-01
1  5.45746	7.628078e-01
1  1.0348	4.691896e-01
1  1.87161	5.351840e-01
3  0.0649464	3.492912e-01
5  0.0124647	3.298684e-01
5  0.0194306	2.978835e-01
2  0.00115955	3.109969e-01
4  0.00228907	3.092549e-01
6  0.203383	2.615535e-01
3  0.0105547	3.286892e-01
1  1.08176	4.732561e-01
2  0.702222	4.382815e-01
1  1.07344	4.725406e-01
2  0.0286823	2.942328e-01
1  0.0252595	3.361847e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 511 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.003773 	for  Omega_m
--> Not computing covariance matrix
6  0.00499602	3.244739e-01
6  1.058	4.712063e-01
8  0.490426	4.157362e-01
2  0.772179	4.451498e-01
1  0.815441	4.492860e-01
2  1.07426	4.726107e-01
1  0.0177695	2.986299e-01
3  0.0157034	2.996108e-01
3  0.386164	2.431338e-01
1  0.085912	3.546329e-01
4  0.156666	3.692986e-01
12  0.400505	2.419329e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 516 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004775 	for  Omega_m
--> Not computing covariance matrix
3  0.120531	2.732632e-01
12  0.082575	2.801870e-01
2  1.51428	1.847319e-01
1  0.00943874	3.030889e-01
3  0.109892	2.750652e-01
4  0.216629	3.795185e-01
3  0.0479672	2.882579e-01
7  0.000341208	3.176972e-01
2  0.0793434	2.808510e-01
1  0.0600703	3.479399e-01
2  0.296537	2.513197e-01
2  0.00878936	3.035112e-01
3  0.139406	3.660528e-01
5  0.0575374	3.472179e-01
1  1.09924	2.010555e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 523 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004581 	for  Omega_m
--> Not computing covariance matrix
6  0.0273034	3.370341e-01
2  0.374546	4.017969e-01
8  0.141772	2.699139e-01
3  0.014852	3.000346e-01
2  0.194952	2.626035e-01
4  0.00183966	3.098796e-01
5  0.00691739	3.261112e-01
1  2.41611	5.734631e-01
1  1.97824	5.428876e-01
2  0.523484	2.325595e-01
2  0.00897309	3.033901e-01
2  0.0358546	3.402984e-01
1  0.609963	4.288279e-01
1  3.13402	6.208961e-01
4  1.55202	5.113144e-01
2  0.0123548	3.013558e-01
2  0.00645652	3.051790e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 531 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.005869 	for  Omega_m
--> Not computing covariance matrix
3  0.5985	4.276173e-01
10  0.0115618	3.018040e-01
1  0.684264	4.364791e-01
1  0.216791	2.599337e-01
6  0.0745113	3.518131e-01
2  1.25098	4.874579e-01
1  0.977941	4.641819e-01
1  0.105146	3.590306e-01
2  0.0201561	3.339082e-01
3  0.296564	2.513171e-01
2  0.562181	2.298935e-01
2  0.357682	3.996330e-01
3  0.513694	2.332530e-01
4  0.12072	3.623319e-01
4  0.00038331	3.128336e-01
5  0.00368985	3.076325e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 541 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.007463 	for  Omega_m
--> Not computing covariance matrix
4  0.116429	2.739470e-01
1  0.596283	2.276362e-01
7  0.144677	3.670619e-01
1  1.01821	4.677383e-01
3  0.818706	4.495949e-01
1  0.224195	3.807163e-01
4  0.018923	3.333182e-01
1  0.545388	2.310361e-01
2  0.0253506	3.362232e-01
4  0.0350048	2.920879e-01
3  0.0561575	3.468184e-01
1  0.229616	3.815642e-01
5  0.0228616	3.351454e-01
1  0.136693	2.706879e-01
1  0.772559	2.170935e-01
4  6.78781e-07	3.153802e-01
2  0.441783	4.100623e-01
1  1.21985	4.848945e-01
1  0.868752	4.542775e-01
1  0.174562	3.725027e-01
2  0.088581	3.552680e-01
2  0.0742501	3.517463e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 551 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.007356 	for  Omega_m
--> Not computing covariance matrix
2  0.0140685	3.307927e-01
1  0.00613099	3.054351e-01
2  1.43594	1.875567e-01
7  1.13189	1.996340e-01
4  0.842933	4.518740e-01
1  1.63176	5.173929e-01
2  0.793423	4.471910e-01
2  0.122004	2.730209e-01
1  0.0506104	2.875478e-01
1  0.063921	3.490110e-01
2  1.0412	4.697478e-01
1  0.000314596	3.130679e-01
1  0.286251	3.899651e-01
9  0.0775613	3.525857e-01
2  0.14138	2.699731e-01
2  0.131202	2.715428e-01
3  0.0181569	2.984527e-01
4  0.0397953	3.416776e-01
1  0.588454	4.265490e-01
1  2.49827	1.558050e-01
1  1.82749	1.743563e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 561 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.006406 	for  Omega_m
--> Not computing covariance matrix
2  0.642496	4.322183e-01
2  0.75453	4.434387e-01
2  0.399641	4.049458e-01
2  0.857096	4.531957e-01
2  0.058389	3.474623e-01
5  0.0489642	2.879876e-01
2  0.155678	2.678710e-01
1  0.141765	2.699150e-01
1  0.0660037	3.495780e-01
1  0.302457	3.922377e-01
1  1.14725	4.788316e-01
1  0.50452	2.339103e-01
2  0.917801	2.095070e-01
2  1.45908	1.867116e-01
2  0.993072	2.058790e-01
1  0.059357	3.477380e-01
2  0.72432	2.198132e-01
3  0.124134	3.630299e-01
1  0.0430428	3.427668e-01
1  1.56904	1.828168e-01
1  0.162437	3.703485e-01
1  0.0786251	2.810006e-01
1  0.806386	2.152500e-01
3  0.0215012	2.969984e-01
4  0.305939	3.927193e-01
1  0.487892	4.154463e-01
1  0.954268	4.620681e-01
1  1.03476	4.691864e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 576 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.006838 	for  Omega_m
--> Not computing covariance matrix
2  2.69051	5.919231e-01
3  0.0633151	2.843853e-01
5  0.349059	2.463696e-01
1  1.31343	4.925399e-01
1  0.165954	2.664264e-01
5  0.439925	2.387591e-01
1  3.21182	6.258860e-01
1  4.02895	6.770359e-01
3  7.03578	8.549145e-01
1  0.19679	3.762899e-01
2  0.836012	2.136756e-01
1  0.0287384	3.376125e-01
1  0.0102042	3.284619e-01
2  0.123004	3.627997e-01
5  0.0130527	3.009737e-01
4  0.0400986	2.905053e-01
3  0.0707835	2.826846e-01
1  1.37445	4.974348e-01
1  0.781505	4.460483e-01
1  1.49503	5.069149e-01
1  2.04118	5.473820e-01
4  0.0446105	2.891906e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 586 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004496 	for  Omega_m
--> Not computing covariance matrix
6  0.213286	3.789837e-01
1  0.150674	3.681904e-01
1  1.77324	5.279693e-01
2  0.304324	3.924961e-01
1  0.697734	4.378327e-01
1  0.740844	2.188690e-01
1  1.47314	1.862023e-01

#  3000 steps done, acceptance rate: 0.393
Traceback (most recent call last):
  File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
Exception ignored in: 'classy.Class.__dealloc__'
Traceback (most recent call last):
  File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
In [35]:
# To load MontePython samples from disk
from datetime import date
from getdist.mcsamples import loadMCSamples
samples_bao_montepython = loadMCSamples('_tests/chains_bao_montepython/{}_3000_'.format(date.today()),
                                    settings={'ignore_rows': 0.5}).copy(label='montepython')

g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike, samples_bao_cosmosis, samples_bao_montepython],
                 params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
[000600.65] [0/1] 07-02 10:32  root                      WARNING  outlier fraction 0.09491525423728814

Interlude: forecasts¶

So far we have input totally ad-hoc covariance matrices. Yet, one can use desilike to produce forecasts.

In [36]:
from desilike.observables.galaxy_clustering import CutskyFootprint
from desilike.theories.galaxy_clustering import BAOPowerSpectrumTemplate, SimpleBAOWigglesTracerPowerSpectrumMultipoles
from desilike.likelihoods.galaxy_clustering import SNWeightedPowerSpectrumLikelihood
from desilike import Fisher

cosmo = DESI()

# Object holding the area and n(z) in (Mpc/h)^(-3)
footprint = CutskyFootprint(area=14000., zrange=np.linspace(0.8, 1.2, 10), nbar=np.full(10, 1e-4), cosmo=cosmo)
z = footprint.zavg

fo = cosmo.get_fourier()
s, s0 = fo.sigma8_z(z, of='delta_cb'), fo.sigma8_z(0., of='delta_cb')
b1 = 0.8 / (s / s0)  # prescription for linear bias
r = 0.5  # reconstruction factor
sigmaper = 9.4 * (s / 0.9)
f = fo.sigma8_z(z, of='theta_cb') / s
params = {'b1': b1, 'sigmapar': r * (1. + f) * sigmaper, 'sigmaper': r * sigmaper}  # fiducial model parameters
covariance_params = {'b1': b1, 'sigmapar': 0., 'sigmaper': 0.}  # fiducial covariance parameters (simple Kaiser model)
template = BAOPowerSpectrumTemplate(z=z, fiducial='DESI', apmode='qparqper')
theory = SimpleBAOWigglesTracerPowerSpectrumMultipoles(template=template) # this BAO model shifts wiggles only
for param in theory.init.params.select(basename='al*'):
    param.update(value=0., fixed=True)  # fixing broadband parameters (the wiggles only shift)

# For klim=(0.01, 0.5), we only use the information from the BAO feature in the power spectrum
likelihood = SNWeightedPowerSpectrumLikelihood(theories=theory, data=params, covariance=covariance_params,
                                               footprints=footprint, klim=(0.01, 0.5))
fisher = Fisher(likelihood)  # initializing Fisher
fisher_bao = fisher(**params).view(params=['qpar', 'qper'])  # computing Fisher prediction at fiducial parameters
[000601.78] [0/1] 07-02 10:32  Differentiation           INFO     Varied parameters: ['qpar', 'qper', 'b1', 'sigmas'].
[000601.83] [0/1] 07-02 10:32  Differentiation           INFO     Varied parameters: ['qpar', 'qper', 'b1', 'sigmas'].
[000602.13] [0/1] 07-02 10:32  Differentiation           INFO     Using finite-differentiation for parameter qpar.
[000602.20] [0/1] 07-02 10:32  Differentiation           INFO     Using finite-differentiation for parameter qper.
[000602.59] [0/1] 07-02 10:32  Differentiation           INFO     Using auto-differentiation for parameter b1.
[000602.80] [0/1] 07-02 10:32  Differentiation           INFO     Using auto-differentiation for parameter sigmas.
[000602.80] [0/1] 07-02 10:32  Differentiation           INFO     qpar grid is [0.998 1.    1.002].
[000602.80] [0/1] 07-02 10:32  Differentiation           INFO     qper grid is [0.998 1.    1.002].
In [37]:
print(fisher_bao.to_stats(tablefmt='pretty'))
+-----+---------+
| FoM | 3601.51 |
+-----+---------+
+------+-------+-------+
|      | qpar  | qper  |
+------+-------+-------+
| mean | 1.000 | 1.000 |
| std  | 0.019 | 0.016 |
+------+-------+-------+
+------+---------+---------+
|      |  qpar   |  qper   |
+------+---------+---------+
| qpar | 3.6e-4  | -1.3e-4 |
| qper | -1.3e-4 | 2.6e-4  |
+------+---------+---------+
In [38]:
# You can directly pass Fisher to BAOCompressionObservable
observable = BAOCompressionObservable(data=fisher_bao, covariance=fisher_bao,
                                      quantities=['qpar', 'qper'], z=z)
# Or...
quantities = ['qpar', 'qper']
observable = BAOCompressionObservable(data=fisher_bao.mean(quantities), covariance=fisher_bao.covariance(quantities),
                                      quantities=quantities, z=z)

This observable can be passed to a likelihood, just as previously, to further run cosmological inference.

ShapeFit likelihood¶

ShapeFit compressed likelihoods are similar to BAO compressed likelihoods.

In [39]:
from desilike.observables.galaxy_clustering import ShapeFitCompressionObservable

observable = ShapeFitCompressionObservable(data=[1., 1., 1., 0.], covariance=np.diag([0.01, 0.01, 0.01, 0.01]),
                                           quantities=['qpar', 'qper', 'df', 'dm'], z=1.)
# Let's define the likelihood from this observable
likelihood = ObservablesGaussianLikelihood(observable)

This observable can be passed to a likelihood, just as previously, to further run cosmological inference.

Full likelihoods¶

Let's write full likelihoods, i.e. with nuisance parameters (bias, stochastic and counterterms not marginalized out).

In [40]:
%%file _tests/fs_likelihood.py
dirname = '_tests'

def FSLikelihood(cosmo='external'):
    from desilike.theories.galaxy_clustering import DirectPowerSpectrumTemplate, KaiserTracerPowerSpectrumMultipoles, LPTVelocileptorsTracerPowerSpectrumMultipoles
    from desilike.observables.galaxy_clustering import BoxFootprint, ObservablesCovarianceMatrix, TracerPowerSpectrumMultipolesObservable
    from desilike.likelihoods import ObservablesGaussianLikelihood
    # Let's define the template = linear power spectrum
    template = DirectPowerSpectrumTemplate(z=1.)
    # For the sake of running time, let us consider a simple linear Kaiser model
    theory = KaiserTracerPowerSpectrumMultipoles(template=template)
    b1 = 0.5
    footprint = BoxFootprint(volume=5e9, nbar=1e-4)  # box with volume of 5 (Gpc/h)^3 and density of 1e-4 (h/Mpc)^3
    observable = TracerPowerSpectrumMultipolesObservable(\
                 data={'b1': b1},  # path to data, *pypower* file, array, or dictionary of parameters
                 covariance=None,  # path to mocks, array (covariance matrix), or None
                 klim={0: [0.01, 0.2, 0.01], 2: [0.01, 0.2, 0.01]},  # k-limits, between 0.01 and 0.2 h/Mpc with 0.005 h/Mpc
                 theory=theory)  # previously defined theory
    covariance = ObservablesCovarianceMatrix(observables=[observable], footprints=[footprint])
    cov = covariance(b1=b1)  # evaluate covariance matrix at this parameter
    likelihood = ObservablesGaussianLikelihood(observables=observable, covariance=cov)
    observable.init.update(data=observable.flatdata)  # fix the data vector
    template.init.update(cosmo=cosmo)  # let's pass the cosmology
    return likelihood

if __name__ == '__main__':
    from desilike.bindings import CobayaLikelihoodGenerator, CosmoSISLikelihoodGenerator, MontePythonLikelihoodGenerator
    CobayaLikelihoodGenerator(dirname=dirname)([FSLikelihood], kw_like={'cosmo': 'external'})
    CosmoSISLikelihoodGenerator(dirname=dirname)([FSLikelihood], kw_like={'cosmo': 'external'})
    MontePythonLikelihoodGenerator(dirname=dirname)([FSLikelihood], kw_like={'cosmo': 'external'})
Writing _tests/fs_likelihood.py

Let's generate the static bindings by calling the above Python script

In [41]:
!python _tests/fs_likelihood.py
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
/home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/numpy/lib/polynomial.py:1337: FutureWarning: In the future extra properties will not be copied across when constructing one poly1d from another
  other = poly1d(other)
WARNING:CosmoSISLikelihoodGenerator:Unbounded prior for parameter sn0; setting to 5-sigma = -50000000.00000001
WARNING:CosmoSISLikelihoodGenerator:Unbounded prior for parameter sn0; setting to 5-sigma = 49999999.99970176
In [42]:
!ls -la _tests/cobaya
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 32
drwxr-xr-x  3 adematti idphp 4096 juil.  2 10:32 .
drwxr-xr-x 10 adematti idphp 4096 juil.  2 10:32 ..
-rw-r--r--  1 adematti idphp  477 juil.  2 10:25 bao_likelihood.py
-rw-r--r--  1 adematti idphp   31 juil.  2 10:25 BAOLikelihood.yaml
-rw-r--r--  1 adematti idphp  471 juil.  2 10:32 fs_likelihood.py
-rw-r--r--  1 adematti idphp  411 juil.  2 10:32 FSLikelihood.yaml
-rw-r--r--  1 adematti idphp   59 juil.  2 10:32 __init__.py
drwxr-xr-x  2 adematti idphp 4096 juil.  2 10:24 __pycache__
In [43]:
!ls -la _tests/cosmosis
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 36
drwxr-xr-x  3 adematti idphp 4096 juil.  2 10:32 .
drwxr-xr-x 10 adematti idphp 4096 juil.  2 10:32 ..
-rw-r--r--  1 adematti idphp    7 juil.  2 10:25 BAOLikelihood_priors.ini
-rw-r--r--  1 adematti idphp  543 juil.  2 10:25 BAOLikelihood.py
-rw-r--r--  1 adematti idphp    7 juil.  2 10:25 BAOLikelihood_values.ini
-rw-r--r--  1 adematti idphp  110 juil.  2 10:32 FSLikelihood_priors.ini
-rw-r--r--  1 adematti idphp  536 juil.  2 10:32 FSLikelihood.py
-rw-r--r--  1 adematti idphp  101 juil.  2 10:32 FSLikelihood_values.ini
drwxr-xr-x  2 adematti idphp 4096 juil.  2 10:25 __pycache__
In [63]:
!ls -la _tests/montepython
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 16
drwxr-xr-x  4 adematti idphp 4096 juil.  2 10:32 .
drwxr-xr-x 13 adematti idphp 4096 juil.  2 10:39 ..
drwxr-xr-x  2 adematti idphp 4096 juil.  2 10:25 BAOLikelihood
drwxr-xr-x  2 adematti idphp 4096 juil.  2 10:32 FSLikelihood

Yet, the above likelihood will take a significant time to evaluate, especially for a 1-loop EFT model. Let's emulate the theory.

In [45]:
likelihood = FSLikelihood(cosmo=None)
theory = likelihood.observables[0].wmatrix.theory

from desilike.emulators import Emulator, TaylorEmulatorEngine, EmulatedCalculator

emulator = Emulator(theory.pt,
                    engine=TaylorEmulatorEngine(order={'*': 1}))
emulator.set_samples()
emulator.fit()  # set Taylor expansion

# Emulator can be saved with:
emulator.save('_tests/emulator.npy')
np.save('_tests/data.npy', likelihood.flatdata)
np.save('_tests/covariance.npy', likelihood.covariance)

theory.init.update(pt=emulator)
[000626.19] [0/1] 07-02 10:32  Emulator                  INFO     Varied parameters: ['h', 'Omega_m', 'omega_b', 'logA'].
[000626.19] [0/1] 07-02 10:32  Emulator                  INFO     Found varying ['pk_dd', 'pk_dt', 'pk_tt', 'pk11'] and fixed ['k', 'z', 'ells', 'names'] outputs.
[000626.71] [0/1] 07-02 10:32  Differentiation           INFO     Varied parameters: ['h', 'Omega_m', 'omega_b', 'logA'].
[000629.76] [0/1] 07-02 10:33  Differentiation           INFO     Using finite-differentiation for parameter h.
[000630.37] [0/1] 07-02 10:33  Differentiation           INFO     Using finite-differentiation for parameter Omega_m.
[000630.91] [0/1] 07-02 10:33  Differentiation           INFO     Using finite-differentiation for parameter omega_b.
[000631.44] [0/1] 07-02 10:33  Differentiation           INFO     Using finite-differentiation for parameter logA.
[000631.44] [0/1] 07-02 10:33  Differentiation           INFO     h grid is [0.6706 0.6736 0.6766].
[000631.44] [0/1] 07-02 10:33  Differentiation           INFO     Omega_m grid is [0.31019172 0.31519172 0.32019172].
[000631.44] [0/1] 07-02 10:33  Differentiation           INFO     omega_b grid is [0.02227 0.02237 0.02247].
[000631.44] [0/1] 07-02 10:33  Differentiation           INFO     logA grid is [3.03499426 3.03639426 3.03779426].
[000636.56] [0/1] 07-02 10:33  Emulator                  INFO     Saving _tests/emulator.npy.
[000636.56] [0/1] 07-02 10:33  BaseConfig                INFO     Saving _tests/emulator.yaml.

Now we can write our likelihood, using the emulated PT!

In [46]:
%%file _tests/fs_likelihood.py
dirname = '_tests'

def FSLikelihood():
    import os
    import numpy as np
    from desilike.theories.galaxy_clustering import DirectPowerSpectrumTemplate
    from desilike.observables.galaxy_clustering import TracerPowerSpectrumMultipolesObservable
    from desilike.likelihoods import ObservablesGaussianLikelihood
    from desilike.emulators import EmulatedCalculator
    # Let's define the template
    template = DirectPowerSpectrumTemplate(z=1.)
    # For the sake of running time, let us consider a simple linear Kaiser model
    theory = KaiserTracerPowerSpectrumMultipoles(template=template, pt=EmulatedCalculator.load(os.path.join(dirname, 'emulator.npy')))
    observable = TracerPowerSpectrumMultipolesObservable(\
                 data=np.load(os.path.join(dirname, 'data.npy')),  # path to data, *pypower* file, array, or dictionary of parameters
                 klim={0: [0.01, 0.2, 0.01], 2: [0.01, 0.2, 0.01]},  # k-limits, between 0.01 and 0.2 h/Mpc with 0.005 h/Mpc
                 theory=theory,
                 covariance=np.load(os.path.join(dirname, 'covariance.npy')))
    likelihood = ObservablesGaussianLikelihood(observables=observable)
    likelihood.all_params['sn0'].update(derived='.auto')
    return likelihood

if __name__ == '__main__':
    from desilike.bindings import CobayaLikelihoodGenerator, CosmoSISLikelihoodGenerator, MontePythonLikelihoodGenerator
    CobayaLikelihoodGenerator(dirname=dirname)(FSLikelihood, kw_like={})
    CosmoSISLikelihoodGenerator(dirname=dirname)(FSLikelihood, kw_like={})
    MontePythonLikelihoodGenerator(dirname=dirname)(FSLikelihood, kw_like={})
Overwriting _tests/fs_likelihood.py

Let's generate the static bindings by calling the above Python script

In [47]:
!python _tests/fs_likelihood.py
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)

Cobaya¶

In [48]:
%%file _tests/config_bao_fs.yaml

theory:
  classy:
    extra_args:
      N_ncdm: 1
      N_ur: 2.0328

likelihood:
  bao_likelihood.BAOLikelihood:
      python_path: _tests/cobaya
  fs_likelihood.FSLikelihood:
      python_path: _tests/cobaya

params:
  Omega_m:
    prior:
      min: 0.1
      max: 1.
    ref:
      dist: norm
      loc: 0.3
      scale: 0.01
    latex: \Omega_{m}
  omega_b: 0.02237
  H0: 67.36
  As: 2.083e-09
  n_s: 0.9649
  tau_reio: 0.0544

sampler:
  mcmc:
    Rminus1_stop: 0.05

debug: True

output: _tests/chains_bao_fs_cobaya/chain
Writing _tests/config_bao_fs.yaml

Let's sample!

In [49]:
!cobaya-run _tests/config_bao_fs.yaml
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
 2023-07-02 10:33:11,778 [output] Creating output folder '_tests/chains_bao_fs_cobaya'
 2023-07-02 10:33:11,778 [output] Output to be read-from/written-into folder '_tests/chains_bao_fs_cobaya', with prefix 'chain'
 2023-07-02 10:33:14,016 [root] Initializing MLIR with module: _mlirRegisterEverything
 2023-07-02 10:33:14,016 [root] Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._mlirRegisterEverything' from '/home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/jaxlib/mlir/_mlir_libs/_mlirRegisterEverything.so'>
 2023-07-02 10:33:14,171 [absl] Finished tracing + transforming prim_fun for jit in 0.0002155303955078125 sec
 2023-07-02 10:33:14,171 [absl] Initializing backend 'interpreter'
 2023-07-02 10:33:14,172 [absl] Backend 'interpreter' initialized
 2023-07-02 10:33:14,172 [absl] Initializing backend 'cpu'
 2023-07-02 10:33:14,173 [absl] Backend 'cpu' initialized
 2023-07-02 10:33:14,173 [absl] Initializing backend 'tpu_driver'
 2023-07-02 10:33:14,173 [absl] Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker:
 2023-07-02 10:33:14,173 [absl] Initializing backend 'cuda'
 2023-07-02 10:33:14,173 [absl] Unable to initialize backend 'cuda': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
 2023-07-02 10:33:14,173 [absl] Initializing backend 'rocm'
 2023-07-02 10:33:14,173 [absl] Unable to initialize backend 'rocm': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
 2023-07-02 10:33:14,173 [absl] Initializing backend 'tpu'
 2023-07-02 10:33:14,174 [absl] Unable to initialize backend 'tpu': INVALID_ARGUMENT: TpuPlatform is not available.
 2023-07-02 10:33:14,174 [absl] *WARNING* No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
 2023-07-02 10:33:14,174 [absl] Compiling prim_fun (140345258472048 for args (ShapedArray(int64[]),).
 2023-07-02 10:33:14,185 [absl] Finished XLA compilation of convert_element_type in 0.007681846618652344 sec
 2023-07-02 10:33:14,444 [classy] Attempting global import (no `path` or Cobaya installation path given).
 2023-07-02 10:33:14,446 [classy] `classy` module loaded successfully from /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/classy-3.2.0-py3.9-linux-x86_64.egg
 2023-07-02 10:33:14,503 [BAOCompressionObservable] Found quantities ['qpar', 'qper'].
 2023-07-02 10:33:14,551 [BAOCompressionObservable] Found quantities ['qiso'].
 2023-07-02 10:33:14,745 [Emulator] Loading _tests/emulator.npy.
 2023-07-02 10:33:14,750 [absl] Finished tracing + transforming prim_fun for jit in 0.00023412704467773438 sec
 2023-07-02 10:33:14,750 [absl] Finished tracing + transforming <lambda> for jit in 0.0002548694610595703 sec
 2023-07-02 10:33:14,751 [absl] Compiling <lambda> (140345237477792 for args (ShapedArray(float64[4]), ShapedArray(float64[4])).
 2023-07-02 10:33:14,760 [absl] Finished XLA compilation of <lambda> in 0.0066030025482177734 sec
 2023-07-02 10:33:14,761 [absl] Finished tracing + transforming prim_fun for jit in 0.0001995563507080078 sec
 2023-07-02 10:33:14,761 [absl] Compiling prim_fun (140345237696320 for args (ShapedArray(float64[4]),).
 2023-07-02 10:33:14,769 [absl] Finished XLA compilation of copy in 0.005262851715087891 sec
 2023-07-02 10:33:14,771 [absl] Finished tracing + transforming _power for jit in 0.0007116794586181641 sec
 2023-07-02 10:33:14,771 [absl] Compiling _power (140345279968496 for args (ShapedArray(float64[4]), ShapedArray(int32[5,4])).
 2023-07-02 10:33:14,782 [absl] Finished XLA compilation of _power in 0.00912618637084961 sec
 2023-07-02 10:33:14,784 [absl] Finished tracing + transforming _where for jit in 0.0010313987731933594 sec
 2023-07-02 10:33:14,784 [absl] Compiling _where (140345279969216 for args (ShapedArray(bool[5,4]), ShapedArray(float64[5,4]), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:33:14,795 [absl] Finished XLA compilation of _where in 0.00801229476928711 sec
 2023-07-02 10:33:14,796 [absl] Finished tracing + transforming _reduce_prod for jit in 0.0004315376281738281 sec
 2023-07-02 10:33:14,796 [absl] Compiling _reduce_prod (140345279968336 for args (ShapedArray(float64[5,4]),).
 2023-07-02 10:33:14,807 [absl] Finished XLA compilation of _reduce_prod in 0.008159160614013672 sec
 2023-07-02 10:33:14,808 [absl] Finished tracing + transforming prim_fun for jit in 0.00019240379333496094 sec
 2023-07-02 10:33:14,809 [absl] Finished tracing + transforming prim_fun for jit in 0.0002732276916503906 sec
 2023-07-02 10:33:14,809 [absl] Compiling prim_fun (140345279968896 for args (ShapedArray(float64[5,38]), ShapedArray(float64[5])).
 2023-07-02 10:33:14,823 [absl] Finished XLA compilation of dot_general in 0.011621475219726562 sec
 2023-07-02 10:33:14,824 [absl] Finished tracing + transforming prim_fun for jit in 0.00026917457580566406 sec
 2023-07-02 10:33:14,824 [absl] Compiling prim_fun (140345279969696 for args (ShapedArray(float64[38]),).
 2023-07-02 10:33:14,832 [absl] Finished XLA compilation of reshape in 0.0055561065673828125 sec
 2023-07-02 10:33:14,946 [model] Parameters were assigned as follows:
 2023-07-02 10:33:14,946 [model] - bao_likelihood.BAOLikelihood:
 2023-07-02 10:33:14,946 [model]      Input:  []
 2023-07-02 10:33:14,946 [model]      Output: []
 2023-07-02 10:33:14,946 [model] - fs_likelihood.FSLikelihood:
 2023-07-02 10:33:14,946 [model]      Input:  ['b1', 'sigmapar', 'sigmaper']
 2023-07-02 10:33:14,946 [model]      Output: []
 2023-07-02 10:33:14,946 [model] - classy:
 2023-07-02 10:33:14,946 [model]      Input:  ['Omega_m', 'omega_b', 'H0', 'As', 'n_s', 'tau_reio']
 2023-07-02 10:33:14,946 [model]      Output: []
 2023-07-02 10:33:14,948 [model] Components will be computed in the order:
 2023-07-02 10:33:14,948 [model]  - [classy, bao_likelihood.BAOLikelihood, fs_likelihood.FSLikelihood]
 2023-07-02 10:33:14,948 [model] Requirements will be calculated by these components:
 2023-07-02 10:33:14,948 [model] - rdrag: classy
 2023-07-02 10:33:14,949 [model] - Hubble: classy
 2023-07-02 10:33:14,949 [model] - angular_diameter_distance: classy
 2023-07-02 10:33:14,967 [mcmc] Initializing
 2023-07-02 10:33:14,971 [mcmc] Getting initial point... (this may take a few seconds)
 2023-07-02 10:33:14,971 [prior] Evaluating prior at array([0.28996824, 1.63228392])
 2023-07-02 10:33:14,971 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:14,972 [model] Posterior to be computed for parameters {'Omega_m': 0.2899682376349314, 'b1': 1.6322839223318795}
 2023-07-02 10:33:14,972 [prior] Evaluating prior at array([0.28996824, 1.63228392])
 2023-07-02 10:33:14,972 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:14,972 [model] Got input parameters: {'Omega_m': 0.2899682376349314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:14,972 [classy] Got parameters {'Omega_m': 0.2899682376349314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:14,972 [classy] Computing new state
 2023-07-02 10:33:14,972 [classy] Setting parameters: {'Omega_m': 0.2899682376349314, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:15,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05941093030333}
 2023-07-02 10:33:15,043 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:15,044 [absl] Finished tracing + transforming prim_fun for jit in 0.00022792816162109375 sec
 2023-07-02 10:33:15,045 [absl] Finished tracing + transforming prim_fun for jit in 0.00015974044799804688 sec
 2023-07-02 10:33:15,045 [absl] Finished tracing + transforming prim_fun for jit in 0.00018644332885742188 sec
 2023-07-02 10:33:15,045 [absl] Compiling prim_fun (140344366076848 for args (ShapedArray(float64[2]), ShapedArray(float64[1])).
 2023-07-02 10:33:15,054 [absl] Finished XLA compilation of concatenate in 0.006158351898193359 sec
 2023-07-02 10:33:15,055 [absl] Finished tracing + transforming <lambda> for jit in 0.0003414154052734375 sec
 2023-07-02 10:33:15,056 [absl] Compiling <lambda> (140344366077168 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
 2023-07-02 10:33:15,065 [absl] Finished XLA compilation of <lambda> in 0.007318973541259766 sec
 2023-07-02 10:33:15,067 [absl] Finished tracing + transforming dot for jit in 0.00047278404235839844 sec
 2023-07-02 10:33:15,067 [absl] Compiling dot (140344366077408 for args (ShapedArray(float64[3]), ShapedArray(float64[3,3])).
 2023-07-02 10:33:15,081 [absl] Finished XLA compilation of dot in 0.010323524475097656 sec
 2023-07-02 10:33:15,082 [absl] Finished tracing + transforming dot for jit in 0.0004627704620361328 sec
 2023-07-02 10:33:15,082 [absl] Compiling dot (140344366077168 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
 2023-07-02 10:33:15,093 [absl] Finished XLA compilation of dot in 0.008072137832641602 sec
 2023-07-02 10:33:15,094 [absl] Finished tracing + transforming fn for jit in 0.00041294097900390625 sec
 2023-07-02 10:33:15,095 [absl] Compiling fn (140344366077008 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[])).
 2023-07-02 10:33:15,103 [absl] Finished XLA compilation of fn in 0.005791187286376953 sec
 2023-07-02 10:33:15,105 [absl] Finished tracing + transforming fn for jit in 0.0004019737243652344 sec
 2023-07-02 10:33:15,105 [absl] Compiling fn (140344366077408 for args (ShapedArray(float64[]), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:33:15,113 [absl] Finished XLA compilation of fn in 0.005861043930053711 sec
 2023-07-02 10:33:15,115 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0331218
 2023-07-02 10:33:15,115 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,115 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:15,136 [absl] Finished tracing + transforming fn for jit in 0.00031185150146484375 sec
 2023-07-02 10:33:15,136 [absl] Compiling fn (140344366079328 for args (ShapedArray(float64[]), ShapedArray(float64[2,19])).
 2023-07-02 10:33:15,148 [absl] Finished XLA compilation of fn in 0.008717060089111328 sec
 2023-07-02 10:33:15,149 [absl] Finished tracing + transforming fn for jit in 0.0003635883331298828 sec
 2023-07-02 10:33:15,150 [absl] Compiling fn (140344366078208 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,19])).
 2023-07-02 10:33:15,161 [absl] Finished XLA compilation of fn in 0.008719205856323242 sec
 2023-07-02 10:33:15,162 [absl] Finished tracing + transforming fn for jit in 0.00034308433532714844 sec
 2023-07-02 10:33:15,163 [absl] Compiling fn (140344366077328 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,1])).
 2023-07-02 10:33:15,174 [absl] Finished XLA compilation of fn in 0.008681535720825195 sec
 2023-07-02 10:33:15,175 [absl] Finished tracing + transforming ravel for jit in 0.0003216266632080078 sec
 2023-07-02 10:33:15,176 [absl] Compiling ravel (140344366077168 for args (ShapedArray(float64[2,19]),).
 2023-07-02 10:33:15,184 [absl] Finished XLA compilation of ravel in 0.005652427673339844 sec
 2023-07-02 10:33:15,185 [absl] Finished tracing + transforming <lambda> for jit in 0.00035071372985839844 sec
 2023-07-02 10:33:15,185 [absl] Compiling <lambda> (140344366078688 for args (ShapedArray(float64[38]), ShapedArray(float64[38])).
 2023-07-02 10:33:15,195 [absl] Finished XLA compilation of <lambda> in 0.007729291915893555 sec
 2023-07-02 10:33:15,197 [absl] Finished tracing + transforming dot for jit in 0.0004360675811767578 sec
 2023-07-02 10:33:15,197 [absl] Compiling dot (140344366077168 for args (ShapedArray(float64[38]), ShapedArray(float64[38,38])).
 2023-07-02 10:33:15,224 [absl] Finished XLA compilation of dot in 0.024365901947021484 sec
 2023-07-02 10:33:15,226 [absl] Finished tracing + transforming dot for jit in 0.00043487548828125 sec
 2023-07-02 10:33:15,226 [absl] Compiling dot (140344366077168 for args (ShapedArray(float64[38]), ShapedArray(float64[38])).
 2023-07-02 10:33:15,241 [absl] Finished XLA compilation of dot in 0.012979745864868164 sec
 2023-07-02 10:33:15,243 [absl] Finished tracing + transforming prim_fun for jit in 0.00019621849060058594 sec
 2023-07-02 10:33:15,243 [absl] Compiling prim_fun (140344366078688 for args (ShapedArray(float64[]),).
 2023-07-02 10:33:15,251 [absl] Finished XLA compilation of convert_element_type in 0.0054781436920166016 sec
 2023-07-02 10:33:15,252 [absl] Finished tracing + transforming prim_fun for jit in 0.00020360946655273438 sec
 2023-07-02 10:33:15,253 [absl] Finished tracing + transforming prim_fun for jit in 0.0001926422119140625 sec
 2023-07-02 10:33:15,253 [absl] Compiling prim_fun (140344366078448 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:33:15,261 [absl] Finished XLA compilation of gt in 0.005736351013183594 sec
 2023-07-02 10:33:15,263 [absl] Finished tracing + transforming prim_fun for jit in 0.000308990478515625 sec
 2023-07-02 10:33:15,263 [absl] Compiling prim_fun (140344366078448 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:33:15,271 [absl] Finished XLA compilation of lt in 0.0058135986328125 sec
 2023-07-02 10:33:15,273 [absl] Finished tracing + transforming <lambda> for jit in 0.00043010711669921875 sec
 2023-07-02 10:33:15,273 [absl] Compiling <lambda> (140344366140208 for args (ShapedArray(bool[], weak_type=True), ShapedArray(bool[], weak_type=True)).
 2023-07-02 10:33:15,282 [absl] Finished XLA compilation of <lambda> in 0.005909442901611328 sec
 2023-07-02 10:33:15,284 [absl] Finished tracing + transforming _where for jit in 0.0005702972412109375 sec
 2023-07-02 10:33:15,284 [absl] Compiling _where (140344366138608 for args (ShapedArray(bool[]), ShapedArray(int64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:33:15,293 [absl] Finished XLA compilation of _where in 0.006242990493774414 sec
 2023-07-02 10:33:15,294 [absl] Finished tracing + transforming fn for jit in 0.0003616809844970703 sec
 2023-07-02 10:33:15,294 [absl] Compiling fn (140344366138608 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
 2023-07-02 10:33:15,303 [absl] Finished XLA compilation of fn in 0.005687713623046875 sec
 2023-07-02 10:33:15,305 [absl] Finished tracing + transforming prim_fun for jit in 0.0001952648162841797 sec
 2023-07-02 10:33:15,306 [absl] Finished tracing + transforming prim_fun for jit in 0.00014662742614746094 sec
 2023-07-02 10:33:15,306 [absl] Compiling prim_fun (140344366140848 for args (ShapedArray(float64[], weak_type=True),).
 2023-07-02 10:33:15,314 [absl] Finished XLA compilation of convert_element_type in 0.0054814815521240234 sec
 2023-07-02 10:33:15,315 [absl] Finished tracing + transforming prim_fun for jit in 0.00024247169494628906 sec
 2023-07-02 10:33:15,315 [absl] Compiling prim_fun (140344366139568 for args (ShapedArray(float64[]), ShapedArray(float64[])).
 2023-07-02 10:33:15,323 [absl] Finished XLA compilation of gt in 0.005784273147583008 sec
 2023-07-02 10:33:15,324 [absl] Finished tracing + transforming prim_fun for jit in 0.00024390220642089844 sec
 2023-07-02 10:33:15,325 [absl] Compiling prim_fun (140344366139008 for args (ShapedArray(float64[]), ShapedArray(float64[])).
 2023-07-02 10:33:15,333 [absl] Finished XLA compilation of lt in 0.00564265251159668 sec
 2023-07-02 10:33:15,334 [absl] Finished tracing + transforming <lambda> for jit in 0.0003275871276855469 sec
 2023-07-02 10:33:15,334 [absl] Compiling <lambda> (140344365712224 for args (ShapedArray(bool[]), ShapedArray(bool[])).
 2023-07-02 10:33:15,342 [absl] Finished XLA compilation of <lambda> in 0.005549430847167969 sec
 2023-07-02 10:33:15,350 [Differentiation] Varied parameters: ['sn0'].
 2023-07-02 10:33:15,351 [Differentiation] Varied parameters: ['sn0'].
 2023-07-02 10:33:15,352 [absl] Finished tracing + transforming prim_fun for jit in 0.0001964569091796875 sec
 2023-07-02 10:33:15,352 [absl] Compiling prim_fun (140344365712544 for args ().
 2023-07-02 10:33:15,360 [absl] Finished XLA compilation of iota in 0.005384683609008789 sec
 2023-07-02 10:33:15,361 [absl] Finished tracing + transforming prim_fun for jit in 0.00026345252990722656 sec
 2023-07-02 10:33:15,361 [absl] Compiling prim_fun (140344365712784 for args (ShapedArray(int32[1,1]), ShapedArray(int32[])).
 2023-07-02 10:33:15,370 [absl] Finished XLA compilation of add in 0.006165981292724609 sec
 2023-07-02 10:33:15,371 [absl] Finished tracing + transforming prim_fun for jit in 0.00022459030151367188 sec
 2023-07-02 10:33:15,371 [absl] Compiling prim_fun (140344365712384 for args ().
 2023-07-02 10:33:15,379 [absl] Finished XLA compilation of iota in 0.0053822994232177734 sec
 2023-07-02 10:33:15,380 [absl] Finished tracing + transforming prim_fun for jit in 0.0002541542053222656 sec
 2023-07-02 10:33:15,380 [absl] Compiling prim_fun (140344365712784 for args (ShapedArray(int32[1,1]), ShapedArray(int32[1,1])).
 2023-07-02 10:33:15,389 [absl] Finished XLA compilation of eq in 0.005829811096191406 sec
 2023-07-02 10:33:15,390 [absl] Finished tracing + transforming prim_fun for jit in 0.00021886825561523438 sec
 2023-07-02 10:33:15,390 [absl] Compiling prim_fun (140344365712224 for args (ShapedArray(bool[1,1]),).
 2023-07-02 10:33:15,398 [absl] Finished XLA compilation of convert_element_type in 0.00564122200012207 sec
 2023-07-02 10:33:15,400 [absl] Finished tracing + transforming prim_fun for jit in 0.0002770423889160156 sec
 2023-07-02 10:33:15,400 [absl] Compiling prim_fun (140344365711824 for args (ShapedArray(float64[1,1]),).
 2023-07-02 10:33:15,408 [absl] Finished XLA compilation of slice in 0.005150794982910156 sec
 2023-07-02 10:33:15,409 [absl] Finished tracing + transforming prim_fun for jit in 0.0002753734588623047 sec
 2023-07-02 10:33:15,409 [absl] Compiling prim_fun (140344365715024 for args (ShapedArray(float64[1,1]),).
 2023-07-02 10:33:15,417 [absl] Finished XLA compilation of reshape in 0.005318403244018555 sec
 2023-07-02 10:33:15,418 [absl] Finished tracing + transforming prim_fun for jit in 0.0002167224884033203 sec
 2023-07-02 10:33:15,418 [absl] Compiling prim_fun (140344365711824 for args (ShapedArray(float64[1]),).
 2023-07-02 10:33:15,426 [absl] Finished XLA compilation of convert_element_type in 0.0054662227630615234 sec
 2023-07-02 10:33:15,429 [absl] Finished tracing + transforming fn for jit in 0.0014188289642333984 sec
 2023-07-02 10:33:15,430 [absl] Compiling fn (140344365906176 for args (ShapedArray(float64[2,1]), ShapedArray(float64[], weak_type=True), ShapedArray(float64[1], weak_type=True)).
 2023-07-02 10:33:15,441 [absl] Finished XLA compilation of fn in 0.007873296737670898 sec
 2023-07-02 10:33:15,443 [absl] Finished tracing + transforming fn for jit in 0.0011246204376220703 sec
 2023-07-02 10:33:15,443 [absl] Compiling fn (140344365906896 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,1]), ShapedArray(float64[1,2,1])).
 2023-07-02 10:33:15,456 [absl] Finished XLA compilation of fn in 0.009931325912475586 sec
 2023-07-02 10:33:15,458 [absl] Finished tracing + transforming fn for jit in 0.0006442070007324219 sec
 2023-07-02 10:33:15,458 [absl] Compiling fn (140344365906256 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,1]), ShapedArray(float64[1,2,19])).
 2023-07-02 10:33:15,469 [absl] Finished XLA compilation of fn in 0.00915670394897461 sec
 2023-07-02 10:33:15,472 [absl] Finished tracing + transforming ravel for jit in 0.0008857250213623047 sec
 2023-07-02 10:33:15,472 [absl] Compiling ravel (140344365499152 for args (ShapedArray(float64[2,19]), ShapedArray(float64[1,2,19])).
 2023-07-02 10:33:15,480 [absl] Finished XLA compilation of ravel in 0.006064891815185547 sec
 2023-07-02 10:33:15,482 [absl] Finished tracing + transforming <lambda> for jit in 0.0006434917449951172 sec
 2023-07-02 10:33:15,482 [absl] Compiling <lambda> (140344365712544 for args (ShapedArray(float64[38]), ShapedArray(float64[38]), ShapedArray(float64[1,38])).
 2023-07-02 10:33:15,493 [absl] Finished XLA compilation of <lambda> in 0.00842595100402832 sec
 2023-07-02 10:33:15,496 [absl] Finished tracing + transforming dot for jit in 0.0009377002716064453 sec
 2023-07-02 10:33:15,496 [absl] Compiling dot (140344365499632 for args (ShapedArray(float64[38]), ShapedArray(float64[38,38]), ShapedArray(float64[1,38])).
 2023-07-02 10:33:15,519 [absl] Finished XLA compilation of dot in 0.020000696182250977 sec
 2023-07-02 10:33:15,521 [absl] Finished tracing + transforming dot for jit in 0.0014214515686035156 sec
 2023-07-02 10:33:15,522 [absl] Compiling dot (140344365500752 for args (ShapedArray(float64[38]), ShapedArray(float64[38]), ShapedArray(float64[1,38]), ShapedArray(float64[1,38])).
 2023-07-02 10:33:15,547 [absl] Finished XLA compilation of dot in 0.022290706634521484 sec
 2023-07-02 10:33:15,549 [absl] Finished tracing + transforming fn for jit in 0.0008902549743652344 sec
 2023-07-02 10:33:15,549 [absl] Compiling fn (140344365499952 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[]), ShapedArray(float64[1])).
 2023-07-02 10:33:15,558 [absl] Finished XLA compilation of fn in 0.006411552429199219 sec
 2023-07-02 10:33:15,561 [absl] Finished tracing + transforming fn for jit in 0.0005729198455810547 sec
 2023-07-02 10:33:15,561 [absl] Compiling fn (140344365499552 for args (ShapedArray(float64[]), ShapedArray(float64[], weak_type=True), ShapedArray(float64[1])).
 2023-07-02 10:33:15,570 [absl] Finished XLA compilation of fn in 0.0061798095703125 sec
 2023-07-02 10:33:15,572 [absl] Finished tracing + transforming prim_fun for jit in 0.00020003318786621094 sec
 2023-07-02 10:33:15,572 [absl] Compiling prim_fun (140344365904976 for args (ShapedArray(float64[1,38]),).
 2023-07-02 10:33:15,580 [absl] Finished XLA compilation of transpose in 0.0054399967193603516 sec
 2023-07-02 10:33:15,582 [absl] Finished tracing + transforming prim_fun for jit in 0.0002522468566894531 sec
 2023-07-02 10:33:15,582 [absl] Compiling prim_fun (140344365715104 for args (ShapedArray(float64[38,1]),).
 2023-07-02 10:33:15,590 [absl] Finished XLA compilation of slice in 0.005415439605712891 sec
 2023-07-02 10:33:15,591 [absl] Finished tracing + transforming prim_fun for jit in 0.00025463104248046875 sec
 2023-07-02 10:33:15,592 [absl] Compiling prim_fun (140344365712544 for args (ShapedArray(float64[38,1]),).
 2023-07-02 10:33:15,599 [absl] Finished XLA compilation of reshape in 0.005372047424316406 sec
 2023-07-02 10:33:15,608 [absl] Finished tracing + transforming fn for jit in 0.0007321834564208984 sec
 2023-07-02 10:33:15,608 [absl] Compiling fn (140344365615520 for args (ShapedArray(float64[2,1]), ShapedArray(float64[]), ShapedArray(float64[1])).
 2023-07-02 10:33:15,619 [absl] Finished XLA compilation of fn in 0.007681131362915039 sec
 2023-07-02 10:33:15,631 [fs_likelihood.fslikelihood] Computed log-likelihood = -8939.07
 2023-07-02 10:33:15,631 [model] Computed derived parameters: {}
 2023-07-02 10:33:15,631 [model] Measuring speeds... (this may take a few seconds)
 2023-07-02 10:33:15,631 [prior] Evaluating prior at array([0.30468482, 1.9978405 ])
 2023-07-02 10:33:15,631 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:15,632 [model] Got input parameters: {'Omega_m': 0.30468481980267054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.9978405048140404, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,632 [classy] Got parameters {'Omega_m': 0.30468481980267054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:15,632 [classy] Computing new state
 2023-07-02 10:33:15,632 [classy] Setting parameters: {'Omega_m': 0.30468481980267054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:15,677 [classy] First evaluation time: 0.0449889 s
 2023-07-02 10:33:15,677 [classy] Average evaluation time: 0.0449889 s
 2023-07-02 10:33:15,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20910683340315}
 2023-07-02 10:33:15,677 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:15,679 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00400606
 2023-07-02 10:33:15,679 [bao_likelihood.baolikelihood] First evaluation time: 0.00172929 s
 2023-07-02 10:33:15,679 [bao_likelihood.baolikelihood] Average evaluation time: 0.00172929 s
 2023-07-02 10:33:15,679 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.9978405048140404, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,679 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:15,699 [fs_likelihood.fslikelihood] Computed log-likelihood = -18781.9
 2023-07-02 10:33:15,699 [fs_likelihood.fslikelihood] First evaluation time: 0.0202169 s
 2023-07-02 10:33:15,699 [fs_likelihood.fslikelihood] Average evaluation time: 0.0202169 s
 2023-07-02 10:33:15,699 [model] Computed derived parameters: {}
 2023-07-02 10:33:15,699 [prior] Evaluating prior at array([0.29855374, 1.58274357])
 2023-07-02 10:33:15,699 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:15,699 [model] Got input parameters: {'Omega_m': 0.2985537413973935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5827435664776845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,699 [classy] Got parameters {'Omega_m': 0.2985537413973935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:15,699 [classy] Computing new state
 2023-07-02 10:33:15,700 [classy] Setting parameters: {'Omega_m': 0.2985537413973935, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:15,743 [classy] Average evaluation time: 0.0437982 s
 2023-07-02 10:33:15,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.97024650096066}
 2023-07-02 10:33:15,743 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:15,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.012527
 2023-07-02 10:33:15,745 [bao_likelihood.baolikelihood] Average evaluation time: 0.00174019 s
 2023-07-02 10:33:15,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5827435664776845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,745 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:15,765 [fs_likelihood.fslikelihood] Computed log-likelihood = -7095.09
 2023-07-02 10:33:15,765 [fs_likelihood.fslikelihood] Average evaluation time: 0.0199828 s
 2023-07-02 10:33:15,765 [model] Computed derived parameters: {}
 2023-07-02 10:33:15,766 [prior] Evaluating prior at array([0.31633011, 1.54137877])
 2023-07-02 10:33:15,766 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:15,766 [model] Got input parameters: {'Omega_m': 0.31633010761514957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5413787730443058, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,766 [classy] Got parameters {'Omega_m': 0.31633010761514957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:15,766 [classy] Computing new state
 2023-07-02 10:33:15,766 [classy] Setting parameters: {'Omega_m': 0.31633010761514957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:15,809 [classy] Average evaluation time: 0.0437099 s
 2023-07-02 10:33:15,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7998430455232}
 2023-07-02 10:33:15,810 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:15,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0011009
 2023-07-02 10:33:15,811 [bao_likelihood.baolikelihood] Average evaluation time: 0.00172499 s
 2023-07-02 10:33:15,811 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5413787730443058, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,811 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:15,832 [fs_likelihood.fslikelihood] Computed log-likelihood = -7143.48
 2023-07-02 10:33:15,832 [fs_likelihood.fslikelihood] Average evaluation time: 0.0202939 s
 2023-07-02 10:33:15,832 [model] Computed derived parameters: {}
 2023-07-02 10:33:15,832 [model] Computed 3 points to measure speeds.
 2023-07-02 10:33:15,832 [model] Setting measured speeds (per sec): {bao_likelihood.BAOLikelihood: 580.0, fs_likelihood.FSLikelihood: 49.3, classy: 22.9}
 2023-07-02 10:33:15,832 [mcmc] Initial point: Omega_m:0.2899682, b1:1.632284
 2023-07-02 10:33:15,832 [model] Cost, oversampling factor and parameters per block, in optimal order:
 2023-07-02 10:33:15,833 [model] * 0.0666291 : 1 : ['Omega_m']
 2023-07-02 10:33:15,833 [model] * 0.020594 : 1 : ['b1']
 2023-07-02 10:33:15,833 [mcmc] Cycle length in steps: 2
 2023-07-02 10:33:15,833 [mcmc] Covariance matrix not present. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
 2023-07-02 10:33:15,835 [mcmc] Sampling with covmat:
          Omega_m        b1
Omega_m  0.000025  0.000000
b1       0.000000  0.083333
 2023-07-02 10:33:15,844 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:33:15,849 [mcmc] Sampling!
 2023-07-02 10:33:15,849 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 1.6322839223318795}
 2023-07-02 10:33:15,849 [prior] Evaluating prior at array([0.30159681, 1.63228392])
 2023-07-02 10:33:15,850 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:15,850 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,850 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:15,850 [classy] Computing new state
 2023-07-02 10:33:15,850 [classy] Setting parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:15,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
 2023-07-02 10:33:15,894 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:15,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00767221
 2023-07-02 10:33:15,896 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,896 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:15,917 [fs_likelihood.fslikelihood] Computed log-likelihood = -8209.22
 2023-07-02 10:33:15,917 [model] Computed derived parameters: {}
 2023-07-02 10:33:15,917 [mcmc] Burn-in sample:
   Omega_m:0.2899682, b1:1.632284
 2023-07-02 10:33:15,917 [mcmc] Progress @ 2023-07-02 10:33:15 : 1 steps taken, and 0 accepted.
 2023-07-02 10:33:15,917 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 1.1793575939907832}
 2023-07-02 10:33:15,917 [prior] Evaluating prior at array([0.30159681, 1.17935759])
 2023-07-02 10:33:15,917 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:15,917 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,917 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:15,917 [classy] Re-using computed results
 2023-07-02 10:33:15,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
 2023-07-02 10:33:15,917 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:15,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,917 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:15,938 [fs_likelihood.fslikelihood] Computed log-likelihood = -2045.99
 2023-07-02 10:33:15,938 [model] Computed derived parameters: {}
 2023-07-02 10:33:15,938 [mcmc] New sample, #1:
   Omega_m:0.3015968, b1:1.632284
 2023-07-02 10:33:15,938 [model] Posterior to be computed for parameters {'Omega_m': 0.30675679491331304, 'b1': 1.1793575939907832}
 2023-07-02 10:33:15,938 [prior] Evaluating prior at array([0.30675679, 1.17935759])
 2023-07-02 10:33:15,938 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:15,938 [model] Got input parameters: {'Omega_m': 0.30675679491331304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,938 [classy] Got parameters {'Omega_m': 0.30675679491331304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:15,938 [classy] Computing new state
 2023-07-02 10:33:15,938 [classy] Setting parameters: {'Omega_m': 0.30675679491331304, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:15,984 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.95492952552055}
 2023-07-02 10:33:15,984 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:15,986 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00224291
 2023-07-02 10:33:15,986 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:15,986 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,006 [fs_likelihood.fslikelihood] Computed log-likelihood = -2136.74
 2023-07-02 10:33:16,006 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,006 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,006 [prior] Evaluating prior at array([0.30159681, 0.8182529 ])
 2023-07-02 10:33:16,006 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,006 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,006 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,006 [classy] Re-using computed results
 2023-07-02 10:33:16,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
 2023-07-02 10:33:16,006 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,007 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,026 [fs_likelihood.fslikelihood] Computed log-likelihood = -301.064
 2023-07-02 10:33:16,026 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,026 [mcmc] New sample, #2:
   Omega_m:0.3015968, b1:1.179358
 2023-07-02 10:33:16,026 [model] Posterior to be computed for parameters {'Omega_m': 0.309038032519737, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,026 [prior] Evaluating prior at array([0.30903803, 0.8182529 ])
 2023-07-02 10:33:16,026 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,027 [model] Got input parameters: {'Omega_m': 0.309038032519737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,027 [classy] Got parameters {'Omega_m': 0.309038032519737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,027 [classy] Computing new state
 2023-07-02 10:33:16,027 [classy] Setting parameters: {'Omega_m': 0.309038032519737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,071 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6768183540687}
 2023-07-02 10:33:16,071 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,073 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000936895
 2023-07-02 10:33:16,073 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,073 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,093 [fs_likelihood.fslikelihood] Computed log-likelihood = -335.882
 2023-07-02 10:33:16,093 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,093 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 1.4305969951339712}
 2023-07-02 10:33:16,093 [prior] Evaluating prior at array([0.30159681, 1.430597  ])
 2023-07-02 10:33:16,093 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,093 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4305969951339712, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,093 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,093 [classy] Re-using computed results
 2023-07-02 10:33:16,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
 2023-07-02 10:33:16,093 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4305969951339712, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,093 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,113 [fs_likelihood.fslikelihood] Computed log-likelihood = -4753.93
 2023-07-02 10:33:16,113 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,113 [model] Posterior to be computed for parameters {'Omega_m': 0.2878456715432816, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,113 [prior] Evaluating prior at array([0.28784567, 0.8182529 ])
 2023-07-02 10:33:16,113 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,113 [model] Got input parameters: {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,113 [classy] Got parameters {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,113 [classy] Computing new state
 2023-07-02 10:33:16,113 [classy] Setting parameters: {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3329796495312}
 2023-07-02 10:33:16,160 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,162 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0398389
 2023-07-02 10:33:16,162 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,162 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,182 [fs_likelihood.fslikelihood] Computed log-likelihood = -245.311
 2023-07-02 10:33:16,182 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,182 [mcmc] New sample, #3:
   Omega_m:0.3015968, b1:0.8182529
 2023-07-02 10:33:16,183 [model] Posterior to be computed for parameters {'Omega_m': 0.2878456715432816, 'b1': 0.053800055942150204}
 2023-07-02 10:33:16,183 [prior] Evaluating prior at array([0.28784567, 0.05380006])
 2023-07-02 10:33:16,183 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,183 [model] Got input parameters: {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.053800055942150204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,183 [classy] Got parameters {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,183 [classy] Re-using computed results
 2023-07-02 10:33:16,183 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3329796495312}
 2023-07-02 10:33:16,183 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,183 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.053800055942150204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,183 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,203 [fs_likelihood.fslikelihood] Computed log-likelihood = -381.553
 2023-07-02 10:33:16,203 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,203 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,203 [prior] Evaluating prior at array([0.27261887, 0.8182529 ])
 2023-07-02 10:33:16,203 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,203 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,203 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,203 [classy] Computing new state
 2023-07-02 10:33:16,203 [classy] Setting parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
 2023-07-02 10:33:16,249 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.108248
 2023-07-02 10:33:16,250 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,250 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -196.584
 2023-07-02 10:33:16,270 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,270 [mcmc] New sample, #4:
   Omega_m:0.2878457, b1:0.8182529
 2023-07-02 10:33:16,271 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': -0.09514461076074388}
 2023-07-02 10:33:16,271 [prior] Evaluating prior at array([ 0.27261887, -0.09514461])
 2023-07-02 10:33:16,271 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:16,271 [model] Posterior to be computed for parameters {'Omega_m': 0.28203941896651996, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,271 [prior] Evaluating prior at array([0.28203942, 0.8182529 ])
 2023-07-02 10:33:16,271 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,271 [model] Got input parameters: {'Omega_m': 0.28203941896651996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,271 [classy] Got parameters {'Omega_m': 0.28203941896651996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,271 [classy] Computing new state
 2023-07-02 10:33:16,271 [classy] Setting parameters: {'Omega_m': 0.28203941896651996, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.09038791501067}
 2023-07-02 10:33:16,316 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,317 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0616535
 2023-07-02 10:33:16,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,317 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,338 [fs_likelihood.fslikelihood] Computed log-likelihood = -225.118
 2023-07-02 10:33:16,338 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,338 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 0.9589805399331686}
 2023-07-02 10:33:16,338 [prior] Evaluating prior at array([0.27261887, 0.95898054])
 2023-07-02 10:33:16,338 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,338 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9589805399331686, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,338 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,338 [classy] Re-using computed results
 2023-07-02 10:33:16,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
 2023-07-02 10:33:16,338 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9589805399331686, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,338 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,358 [fs_likelihood.fslikelihood] Computed log-likelihood = -540.713
 2023-07-02 10:33:16,358 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,358 [model] Posterior to be computed for parameters {'Omega_m': 0.2957629172298728, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,358 [prior] Evaluating prior at array([0.29576292, 0.8182529 ])
 2023-07-02 10:33:16,358 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,358 [model] Got input parameters: {'Omega_m': 0.2957629172298728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,358 [classy] Got parameters {'Omega_m': 0.2957629172298728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,358 [classy] Computing new state
 2023-07-02 10:33:16,358 [classy] Setting parameters: {'Omega_m': 0.2957629172298728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3212767904241}
 2023-07-02 10:33:16,403 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0180881
 2023-07-02 10:33:16,405 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,405 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,424 [fs_likelihood.fslikelihood] Computed log-likelihood = -276.049
 2023-07-02 10:33:16,424 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,424 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 1.2858471165446863}
 2023-07-02 10:33:16,424 [prior] Evaluating prior at array([0.27261887, 1.28584712])
 2023-07-02 10:33:16,425 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,425 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2858471165446863, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,425 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,425 [classy] Re-using computed results
 2023-07-02 10:33:16,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
 2023-07-02 10:33:16,425 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2858471165446863, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,425 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,445 [fs_likelihood.fslikelihood] Computed log-likelihood = -2394.92
 2023-07-02 10:33:16,445 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,445 [model] Posterior to be computed for parameters {'Omega_m': 0.28602613176017117, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,445 [prior] Evaluating prior at array([0.28602613, 0.8182529 ])
 2023-07-02 10:33:16,445 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,445 [model] Got input parameters: {'Omega_m': 0.28602613176017117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,445 [classy] Got parameters {'Omega_m': 0.28602613176017117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,445 [classy] Computing new state
 2023-07-02 10:33:16,446 [classy] Setting parameters: {'Omega_m': 0.28602613176017117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.56889102530823}
 2023-07-02 10:33:16,489 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0461272
 2023-07-02 10:33:16,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,491 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,511 [fs_likelihood.fslikelihood] Computed log-likelihood = -238.77
 2023-07-02 10:33:16,511 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,511 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 1.128211509064688}
 2023-07-02 10:33:16,511 [prior] Evaluating prior at array([0.27261887, 1.12821151])
 2023-07-02 10:33:16,511 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,511 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.128211509064688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,511 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,511 [classy] Re-using computed results
 2023-07-02 10:33:16,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
 2023-07-02 10:33:16,511 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.128211509064688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,511 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -1283.4
 2023-07-02 10:33:16,531 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,531 [model] Posterior to be computed for parameters {'Omega_m': 0.27592580202259703, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,531 [prior] Evaluating prior at array([0.2759258, 0.8182529])
 2023-07-02 10:33:16,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,531 [model] Got input parameters: {'Omega_m': 0.27592580202259703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,531 [classy] Got parameters {'Omega_m': 0.27592580202259703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,531 [classy] Computing new state
 2023-07-02 10:33:16,531 [classy] Setting parameters: {'Omega_m': 0.27592580202259703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.9024831105214}
 2023-07-02 10:33:16,575 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0902643
 2023-07-02 10:33:16,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,576 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,596 [fs_likelihood.fslikelihood] Computed log-likelihood = -206.005
 2023-07-02 10:33:16,596 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,597 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 0.944089927588688}
 2023-07-02 10:33:16,597 [prior] Evaluating prior at array([0.27261887, 0.94408993])
 2023-07-02 10:33:16,597 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,597 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.944089927588688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,597 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,597 [classy] Re-using computed results
 2023-07-02 10:33:16,597 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
 2023-07-02 10:33:16,597 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.944089927588688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,597 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,616 [fs_likelihood.fslikelihood] Computed log-likelihood = -493.843
 2023-07-02 10:33:16,617 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,617 [model] Posterior to be computed for parameters {'Omega_m': 0.26225838904316323, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,617 [prior] Evaluating prior at array([0.26225839, 0.8182529 ])
 2023-07-02 10:33:16,617 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,617 [model] Got input parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,617 [classy] Got parameters {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,617 [classy] Computing new state
 2023-07-02 10:33:16,617 [classy] Setting parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,661 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.77484301414668}
 2023-07-02 10:33:16,661 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,663 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.176623
 2023-07-02 10:33:16,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,663 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,683 [fs_likelihood.fslikelihood] Computed log-likelihood = -171.244
 2023-07-02 10:33:16,683 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,683 [mcmc] New sample, #5:
   Omega_m:0.2726189, b1:0.8182529
 2023-07-02 10:33:16,683 [model] Posterior to be computed for parameters {'Omega_m': 0.26225838904316323, 'b1': 1.5625394088617082}
 2023-07-02 10:33:16,683 [prior] Evaluating prior at array([0.26225839, 1.56253941])
 2023-07-02 10:33:16,683 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,683 [model] Got input parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5625394088617082, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,683 [classy] Got parameters {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,683 [classy] Re-using computed results
 2023-07-02 10:33:16,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.77484301414668}
 2023-07-02 10:33:16,683 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5625394088617082, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,683 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,703 [fs_likelihood.fslikelihood] Computed log-likelihood = -5273.7
 2023-07-02 10:33:16,703 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,703 [model] Posterior to be computed for parameters {'Omega_m': 0.27294701790625175, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,704 [prior] Evaluating prior at array([0.27294702, 0.8182529 ])
 2023-07-02 10:33:16,704 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,704 [model] Got input parameters: {'Omega_m': 0.27294701790625175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,704 [classy] Got parameters {'Omega_m': 0.27294701790625175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,704 [classy] Computing new state
 2023-07-02 10:33:16,704 [classy] Setting parameters: {'Omega_m': 0.27294701790625175, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,748 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.30373159833172}
 2023-07-02 10:33:16,748 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,750 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.106383
 2023-07-02 10:33:16,750 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,750 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,769 [fs_likelihood.fslikelihood] Computed log-likelihood = -197.49
 2023-07-02 10:33:16,769 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,769 [model] Posterior to be computed for parameters {'Omega_m': 0.26225838904316323, 'b1': 1.456962531561599}
 2023-07-02 10:33:16,769 [prior] Evaluating prior at array([0.26225839, 1.45696253])
 2023-07-02 10:33:16,770 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,770 [model] Got input parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.456962531561599, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,770 [classy] Got parameters {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,770 [classy] Re-using computed results
 2023-07-02 10:33:16,770 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.77484301414668}
 2023-07-02 10:33:16,770 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,770 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.456962531561599, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,770 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,790 [fs_likelihood.fslikelihood] Computed log-likelihood = -3886.41
 2023-07-02 10:33:16,790 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,790 [model] Posterior to be computed for parameters {'Omega_m': 0.2609899719629662, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,791 [prior] Evaluating prior at array([0.26098997, 0.8182529 ])
 2023-07-02 10:33:16,791 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,791 [model] Got input parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,791 [classy] Got parameters {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,791 [classy] Computing new state
 2023-07-02 10:33:16,791 [classy] Setting parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9527458653329}
 2023-07-02 10:33:16,834 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,836 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.186296
 2023-07-02 10:33:16,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,836 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,857 [fs_likelihood.fslikelihood] Computed log-likelihood = -168.577
 2023-07-02 10:33:16,857 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,857 [mcmc] New sample, #6:
   Omega_m:0.2622584, b1:0.8182529
 2023-07-02 10:33:16,857 [model] Posterior to be computed for parameters {'Omega_m': 0.2609899719629662, 'b1': 1.67375319713257}
 2023-07-02 10:33:16,857 [prior] Evaluating prior at array([0.26098997, 1.6737532 ])
 2023-07-02 10:33:16,857 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,857 [model] Got input parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.67375319713257, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,857 [classy] Got parameters {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,857 [classy] Re-using computed results
 2023-07-02 10:33:16,857 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9527458653329}
 2023-07-02 10:33:16,857 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,857 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.67375319713257, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,857 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,877 [fs_likelihood.fslikelihood] Computed log-likelihood = -7014.08
 2023-07-02 10:33:16,877 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,877 [model] Posterior to be computed for parameters {'Omega_m': 0.27302154852603616, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,877 [prior] Evaluating prior at array([0.27302155, 0.8182529 ])
 2023-07-02 10:33:16,877 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,877 [model] Got input parameters: {'Omega_m': 0.27302154852603616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,877 [classy] Got parameters {'Omega_m': 0.27302154852603616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,877 [classy] Computing new state
 2023-07-02 10:33:16,877 [classy] Setting parameters: {'Omega_m': 0.27302154852603616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:16,921 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.29364377597815}
 2023-07-02 10:33:16,921 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:16,923 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105962
 2023-07-02 10:33:16,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,923 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,943 [fs_likelihood.fslikelihood] Computed log-likelihood = -197.697
 2023-07-02 10:33:16,943 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,943 [model] Posterior to be computed for parameters {'Omega_m': 0.2609899719629662, 'b1': 0.004751808353729903}
 2023-07-02 10:33:16,944 [prior] Evaluating prior at array([0.26098997, 0.00475181])
 2023-07-02 10:33:16,944 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,944 [model] Got input parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.004751808353729903, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,944 [classy] Got parameters {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,944 [classy] Re-using computed results
 2023-07-02 10:33:16,944 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9527458653329}
 2023-07-02 10:33:16,944 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:16,944 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.004751808353729903, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,944 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:16,963 [fs_likelihood.fslikelihood] Computed log-likelihood = -487.921
 2023-07-02 10:33:16,963 [model] Computed derived parameters: {}
 2023-07-02 10:33:16,964 [model] Posterior to be computed for parameters {'Omega_m': 0.25977404455312525, 'b1': 0.8182528959083948}
 2023-07-02 10:33:16,964 [prior] Evaluating prior at array([0.25977404, 0.8182529 ])
 2023-07-02 10:33:16,964 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:16,964 [model] Got input parameters: {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:16,964 [classy] Got parameters {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:16,964 [classy] Computing new state
 2023-07-02 10:33:16,964 [classy] Setting parameters: {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1239605473226}
 2023-07-02 10:33:17,008 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,010 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.195844
 2023-07-02 10:33:17,010 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,010 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -166.109
 2023-07-02 10:33:17,031 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,031 [mcmc] New sample, #7:
   Omega_m:0.26099, b1:0.8182529
 2023-07-02 10:33:17,032 [model] Posterior to be computed for parameters {'Omega_m': 0.25977404455312525, 'b1': 1.2843110112976766}
 2023-07-02 10:33:17,032 [prior] Evaluating prior at array([0.25977404, 1.28431101])
 2023-07-02 10:33:17,032 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,032 [model] Got input parameters: {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2843110112976766, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,032 [classy] Got parameters {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,032 [classy] Re-using computed results
 2023-07-02 10:33:17,032 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1239605473226}
 2023-07-02 10:33:17,032 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2843110112976766, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,032 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,052 [fs_likelihood.fslikelihood] Computed log-likelihood = -2149.11
 2023-07-02 10:33:17,052 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,053 [model] Posterior to be computed for parameters {'Omega_m': 0.2721898618308027, 'b1': 0.8182528959083948}
 2023-07-02 10:33:17,053 [prior] Evaluating prior at array([0.27218986, 0.8182529 ])
 2023-07-02 10:33:17,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,053 [model] Got input parameters: {'Omega_m': 0.2721898618308027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,053 [classy] Got parameters {'Omega_m': 0.2721898618308027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,053 [classy] Computing new state
 2023-07-02 10:33:17,053 [classy] Setting parameters: {'Omega_m': 0.2721898618308027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.40631930126844}
 2023-07-02 10:33:17,098 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,099 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.110714
 2023-07-02 10:33:17,099 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,099 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,120 [fs_likelihood.fslikelihood] Computed log-likelihood = -195.409
 2023-07-02 10:33:17,120 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,120 [model] Posterior to be computed for parameters {'Omega_m': 0.25977404455312525, 'b1': -0.4338354439874048}
 2023-07-02 10:33:17,120 [prior] Evaluating prior at array([ 0.25977404, -0.43383544])
 2023-07-02 10:33:17,120 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:17,121 [model] Posterior to be computed for parameters {'Omega_m': 0.25204277059003577, 'b1': 0.8182528959083948}
 2023-07-02 10:33:17,121 [prior] Evaluating prior at array([0.25204277, 0.8182529 ])
 2023-07-02 10:33:17,121 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,121 [model] Got input parameters: {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,121 [classy] Got parameters {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,121 [classy] Computing new state
 2023-07-02 10:33:17,121 [classy] Setting parameters: {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,174 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.22862410571764}
 2023-07-02 10:33:17,174 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,176 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.26307
 2023-07-02 10:33:17,176 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,176 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,198 [fs_likelihood.fslikelihood] Computed log-likelihood = -152.456
 2023-07-02 10:33:17,198 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,198 [mcmc] New sample, #8:
   Omega_m:0.259774, b1:0.8182529
 2023-07-02 10:33:17,199 [model] Posterior to be computed for parameters {'Omega_m': 0.25204277059003577, 'b1': 2.0700062583797143}
 2023-07-02 10:33:17,199 [prior] Evaluating prior at array([0.25204277, 2.07000626])
 2023-07-02 10:33:17,199 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,199 [model] Got input parameters: {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.0700062583797143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,199 [classy] Got parameters {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,199 [classy] Re-using computed results
 2023-07-02 10:33:17,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.22862410571764}
 2023-07-02 10:33:17,199 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.0700062583797143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,199 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,219 [fs_likelihood.fslikelihood] Computed log-likelihood = -16031.9
 2023-07-02 10:33:17,219 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,219 [model] Posterior to be computed for parameters {'Omega_m': 0.24251082666719687, 'b1': 0.8182528959083948}
 2023-07-02 10:33:17,219 [prior] Evaluating prior at array([0.24251083, 0.8182529 ])
 2023-07-02 10:33:17,219 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,219 [model] Got input parameters: {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,219 [classy] Got parameters {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,219 [classy] Computing new state
 2023-07-02 10:33:17,219 [classy] Setting parameters: {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.62976245517348}
 2023-07-02 10:33:17,265 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.362221
 2023-07-02 10:33:17,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,267 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,286 [fs_likelihood.fslikelihood] Computed log-likelihood = -140.473
 2023-07-02 10:33:17,286 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,286 [mcmc] New sample, #9:
   Omega_m:0.2520428, b1:0.8182529
 2023-07-02 10:33:17,286 [model] Posterior to be computed for parameters {'Omega_m': 0.24251082666719687, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,286 [prior] Evaluating prior at array([0.24251083, 0.60072825])
 2023-07-02 10:33:17,286 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,286 [model] Got input parameters: {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,286 [classy] Got parameters {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,287 [classy] Re-using computed results
 2023-07-02 10:33:17,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.62976245517348}
 2023-07-02 10:33:17,287 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,287 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,306 [fs_likelihood.fslikelihood] Computed log-likelihood = -39.3114
 2023-07-02 10:33:17,306 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,306 [mcmc] New sample, #10:
   Omega_m:0.2425108, b1:0.8182529
 2023-07-02 10:33:17,307 [model] Posterior to be computed for parameters {'Omega_m': 0.24324011743928295, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,307 [prior] Evaluating prior at array([0.24324012, 0.60072825])
 2023-07-02 10:33:17,307 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,307 [model] Got input parameters: {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,307 [classy] Got parameters {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,307 [classy] Computing new state
 2023-07-02 10:33:17,307 [classy] Setting parameters: {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.52097813775873}
 2023-07-02 10:33:17,351 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,353 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.35397
 2023-07-02 10:33:17,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,353 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,373 [fs_likelihood.fslikelihood] Computed log-likelihood = -38.2243
 2023-07-02 10:33:17,373 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,373 [mcmc] New sample, #11:
   Omega_m:0.2425108, b1:0.6007283
 2023-07-02 10:33:17,373 [model] Posterior to be computed for parameters {'Omega_m': 0.24324011743928295, 'b1': 1.7955126374360098}
 2023-07-02 10:33:17,373 [prior] Evaluating prior at array([0.24324012, 1.79551264])
 2023-07-02 10:33:17,373 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,373 [model] Got input parameters: {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7955126374360098, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,373 [classy] Got parameters {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,373 [classy] Re-using computed results
 2023-07-02 10:33:17,373 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.52097813775873}
 2023-07-02 10:33:17,373 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,373 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7955126374360098, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,373 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,392 [fs_likelihood.fslikelihood] Computed log-likelihood = -8425.15
 2023-07-02 10:33:17,393 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,393 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,393 [prior] Evaluating prior at array([0.26799844, 0.60072825])
 2023-07-02 10:33:17,393 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,393 [model] Got input parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,393 [classy] Got parameters {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,393 [classy] Computing new state
 2023-07-02 10:33:17,393 [classy] Setting parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,437 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.97867406055138}
 2023-07-02 10:33:17,437 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.136443
 2023-07-02 10:33:17,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,439 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.9418
 2023-07-02 10:33:17,459 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,459 [mcmc] New sample, #12:
   Omega_m:0.2432401, b1:0.6007283
 2023-07-02 10:33:17,460 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': 0.21654010019951703}
 2023-07-02 10:33:17,460 [prior] Evaluating prior at array([0.26799844, 0.2165401 ])
 2023-07-02 10:33:17,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,460 [model] Got input parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.21654010019951703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,460 [classy] Got parameters {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,460 [classy] Re-using computed results
 2023-07-02 10:33:17,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.97867406055138}
 2023-07-02 10:33:17,460 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.21654010019951703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,479 [fs_likelihood.fslikelihood] Computed log-likelihood = -248.869
 2023-07-02 10:33:17,479 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,479 [model] Posterior to be computed for parameters {'Omega_m': 0.24947118981260316, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,479 [prior] Evaluating prior at array([0.24947119, 0.60072825])
 2023-07-02 10:33:17,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,480 [model] Got input parameters: {'Omega_m': 0.24947118981260316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,480 [classy] Got parameters {'Omega_m': 0.24947118981260316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,480 [classy] Computing new state
 2023-07-02 10:33:17,480 [classy] Setting parameters: {'Omega_m': 0.24947118981260316, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.60227355220965}
 2023-07-02 10:33:17,524 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.287999
 2023-07-02 10:33:17,525 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,525 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,545 [fs_likelihood.fslikelihood] Computed log-likelihood = -29.7348
 2023-07-02 10:33:17,545 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,545 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': -0.06319943150551888}
 2023-07-02 10:33:17,545 [prior] Evaluating prior at array([ 0.26799844, -0.06319943])
 2023-07-02 10:33:17,545 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:17,545 [model] Posterior to be computed for parameters {'Omega_m': 0.2591363027905965, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,545 [prior] Evaluating prior at array([0.2591363 , 0.60072825])
 2023-07-02 10:33:17,546 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,546 [model] Got input parameters: {'Omega_m': 0.2591363027905965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,546 [classy] Got parameters {'Omega_m': 0.2591363027905965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,546 [classy] Computing new state
 2023-07-02 10:33:17,546 [classy] Setting parameters: {'Omega_m': 0.2591363027905965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,589 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.2140316674361}
 2023-07-02 10:33:17,589 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,591 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.200961
 2023-07-02 10:33:17,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,591 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,611 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.3967
 2023-07-02 10:33:17,611 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,611 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': 0.7327582733801161}
 2023-07-02 10:33:17,611 [prior] Evaluating prior at array([0.26799844, 0.73275827])
 2023-07-02 10:33:17,611 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,611 [model] Got input parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7327582733801161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,612 [classy] Got parameters {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,612 [classy] Re-using computed results
 2023-07-02 10:33:17,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.97867406055138}
 2023-07-02 10:33:17,612 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7327582733801161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,612 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,631 [fs_likelihood.fslikelihood] Computed log-likelihood = -76.1298
 2023-07-02 10:33:17,631 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,631 [model] Posterior to be computed for parameters {'Omega_m': 0.2673629437719531, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,632 [prior] Evaluating prior at array([0.26736294, 0.60072825])
 2023-07-02 10:33:17,632 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,632 [model] Got input parameters: {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,632 [classy] Got parameters {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,632 [classy] Computing new state
 2023-07-02 10:33:17,632 [classy] Setting parameters: {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.06611034114562}
 2023-07-02 10:33:17,676 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,677 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140607
 2023-07-02 10:33:17,677 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,677 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,697 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.3083
 2023-07-02 10:33:17,697 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,697 [mcmc] New sample, #13:
   Omega_m:0.2679984, b1:0.6007283
 2023-07-02 10:33:17,697 [model] Posterior to be computed for parameters {'Omega_m': 0.2673629437719531, 'b1': 1.1809589973077994}
 2023-07-02 10:33:17,697 [prior] Evaluating prior at array([0.26736294, 1.180959  ])
 2023-07-02 10:33:17,697 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,697 [model] Got input parameters: {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1809589973077994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,697 [classy] Got parameters {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,698 [classy] Re-using computed results
 2023-07-02 10:33:17,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.06611034114562}
 2023-07-02 10:33:17,698 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1809589973077994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,698 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,717 [fs_likelihood.fslikelihood] Computed log-likelihood = -1533.3
 2023-07-02 10:33:17,717 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,718 [model] Posterior to be computed for parameters {'Omega_m': 0.28501101895354913, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,718 [prior] Evaluating prior at array([0.28501102, 0.60072825])
 2023-07-02 10:33:17,718 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,718 [model] Got input parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,718 [classy] Got parameters {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,718 [classy] Computing new state
 2023-07-02 10:33:17,718 [classy] Setting parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.70108148648268}
 2023-07-02 10:33:17,762 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,764 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0498515
 2023-07-02 10:33:17,764 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,764 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,783 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.65868
 2023-07-02 10:33:17,783 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,783 [mcmc] New sample, #14:
   Omega_m:0.2673629, b1:0.6007283
 2023-07-02 10:33:17,784 [model] Posterior to be computed for parameters {'Omega_m': 0.28501101895354913, 'b1': 0.9471683789005036}
 2023-07-02 10:33:17,784 [prior] Evaluating prior at array([0.28501102, 0.94716838])
 2023-07-02 10:33:17,784 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,784 [model] Got input parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9471683789005036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,784 [classy] Got parameters {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,784 [classy] Re-using computed results
 2023-07-02 10:33:17,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.70108148648268}
 2023-07-02 10:33:17,784 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9471683789005036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,784 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,804 [fs_likelihood.fslikelihood] Computed log-likelihood = -580.106
 2023-07-02 10:33:17,804 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,804 [model] Posterior to be computed for parameters {'Omega_m': 0.2910488232832707, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,804 [prior] Evaluating prior at array([0.29104882, 0.60072825])
 2023-07-02 10:33:17,804 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,804 [model] Got input parameters: {'Omega_m': 0.2910488232832707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,804 [classy] Got parameters {'Omega_m': 0.2910488232832707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,804 [classy] Computing new state
 2023-07-02 10:33:17,804 [classy] Setting parameters: {'Omega_m': 0.2910488232832707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,848 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.92080070373154}
 2023-07-02 10:33:17,848 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,850 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0299544
 2023-07-02 10:33:17,850 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,850 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,870 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.70215
 2023-07-02 10:33:17,870 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,870 [model] Posterior to be computed for parameters {'Omega_m': 0.28501101895354913, 'b1': 0.12874436354977098}
 2023-07-02 10:33:17,870 [prior] Evaluating prior at array([0.28501102, 0.12874436])
 2023-07-02 10:33:17,870 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,870 [model] Got input parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.12874436354977098, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,870 [classy] Got parameters {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,870 [classy] Re-using computed results
 2023-07-02 10:33:17,870 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.70108148648268}
 2023-07-02 10:33:17,870 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,870 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.12874436354977098, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,870 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,890 [fs_likelihood.fslikelihood] Computed log-likelihood = -305.159
 2023-07-02 10:33:17,890 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,890 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,890 [prior] Evaluating prior at array([0.28000247, 0.60072825])
 2023-07-02 10:33:17,890 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,890 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,890 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,890 [classy] Computing new state
 2023-07-02 10:33:17,890 [classy] Setting parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:17,934 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:17,934 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:17,936 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0705304
 2023-07-02 10:33:17,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,936 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,955 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.81218
 2023-07-02 10:33:17,956 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,956 [mcmc] New sample, #15:
   Omega_m:0.285011, b1:0.6007283
 2023-07-02 10:33:17,956 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.5773709427986682}
 2023-07-02 10:33:17,956 [prior] Evaluating prior at array([0.28000247, 1.57737094])
 2023-07-02 10:33:17,956 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,956 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5773709427986682, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,956 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,956 [classy] Re-using computed results
 2023-07-02 10:33:17,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:17,956 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:17,956 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5773709427986682, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,956 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:17,976 [fs_likelihood.fslikelihood] Computed log-likelihood = -6189.92
 2023-07-02 10:33:17,976 [model] Computed derived parameters: {}
 2023-07-02 10:33:17,976 [model] Posterior to be computed for parameters {'Omega_m': 0.2719862039772243, 'b1': 0.600728251405974}
 2023-07-02 10:33:17,976 [prior] Evaluating prior at array([0.2719862 , 0.60072825])
 2023-07-02 10:33:17,976 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:17,976 [model] Got input parameters: {'Omega_m': 0.2719862039772243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:17,976 [classy] Got parameters {'Omega_m': 0.2719862039772243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:17,976 [classy] Computing new state
 2023-07-02 10:33:17,976 [classy] Setting parameters: {'Omega_m': 0.2719862039772243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.43395664695288}
 2023-07-02 10:33:18,020 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,022 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111896
 2023-07-02 10:33:18,022 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,022 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,041 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.9811
 2023-07-02 10:33:18,041 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,042 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.6541951931372925}
 2023-07-02 10:33:18,042 [prior] Evaluating prior at array([0.28000247, 1.65419519])
 2023-07-02 10:33:18,042 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,042 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6541951931372925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,042 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,042 [classy] Re-using computed results
 2023-07-02 10:33:18,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:18,042 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6541951931372925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,042 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,063 [fs_likelihood.fslikelihood] Computed log-likelihood = -7553.62
 2023-07-02 10:33:18,063 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,063 [model] Posterior to be computed for parameters {'Omega_m': 0.29501559010083983, 'b1': 0.600728251405974}
 2023-07-02 10:33:18,063 [prior] Evaluating prior at array([0.29501559, 0.60072825])
 2023-07-02 10:33:18,063 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,063 [model] Got input parameters: {'Omega_m': 0.29501559010083983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,063 [classy] Got parameters {'Omega_m': 0.29501559010083983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,063 [classy] Computing new state
 2023-07-02 10:33:18,063 [classy] Setting parameters: {'Omega_m': 0.29501559010083983, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.41576250430415}
 2023-07-02 10:33:18,107 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,109 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0197601
 2023-07-02 10:33:18,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,109 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,129 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.1187
 2023-07-02 10:33:18,129 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,129 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.1136152282061541}
 2023-07-02 10:33:18,129 [prior] Evaluating prior at array([0.28000247, 0.11361523])
 2023-07-02 10:33:18,130 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,130 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.1136152282061541, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,130 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,130 [classy] Re-using computed results
 2023-07-02 10:33:18,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:18,130 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,130 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.1136152282061541, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,130 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -331.838
 2023-07-02 10:33:18,150 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,150 [model] Posterior to be computed for parameters {'Omega_m': 0.26638360771154507, 'b1': 0.600728251405974}
 2023-07-02 10:33:18,150 [prior] Evaluating prior at array([0.26638361, 0.60072825])
 2023-07-02 10:33:18,150 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,150 [model] Got input parameters: {'Omega_m': 0.26638360771154507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,150 [classy] Got parameters {'Omega_m': 0.26638360771154507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,150 [classy] Computing new state
 2023-07-02 10:33:18,150 [classy] Setting parameters: {'Omega_m': 0.26638360771154507, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.20119947178603}
 2023-07-02 10:33:18,194 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,196 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.14716
 2023-07-02 10:33:18,196 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,196 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,216 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.9024
 2023-07-02 10:33:18,216 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,216 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.1323255545419308}
 2023-07-02 10:33:18,216 [prior] Evaluating prior at array([0.28000247, 1.13232555])
 2023-07-02 10:33:18,216 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,216 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1323255545419308, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,216 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,216 [classy] Re-using computed results
 2023-07-02 10:33:18,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:18,216 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,216 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1323255545419308, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,216 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,235 [fs_likelihood.fslikelihood] Computed log-likelihood = -1397.53
 2023-07-02 10:33:18,236 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,236 [model] Posterior to be computed for parameters {'Omega_m': 0.2717608427172804, 'b1': 0.600728251405974}
 2023-07-02 10:33:18,236 [prior] Evaluating prior at array([0.27176084, 0.60072825])
 2023-07-02 10:33:18,236 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,236 [model] Got input parameters: {'Omega_m': 0.2717608427172804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,236 [classy] Got parameters {'Omega_m': 0.2717608427172804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,236 [classy] Computing new state
 2023-07-02 10:33:18,236 [classy] Setting parameters: {'Omega_m': 0.2717608427172804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,280 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.4645612571393}
 2023-07-02 10:33:18,280 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,282 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113212
 2023-07-02 10:33:18,282 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,282 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,301 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.0763
 2023-07-02 10:33:18,301 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,301 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.4057531596575807}
 2023-07-02 10:33:18,301 [prior] Evaluating prior at array([0.28000247, 1.40575316])
 2023-07-02 10:33:18,302 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,302 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4057531596575807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,302 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,302 [classy] Re-using computed results
 2023-07-02 10:33:18,302 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:18,302 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,302 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4057531596575807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,302 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,322 [fs_likelihood.fslikelihood] Computed log-likelihood = -3777.39
 2023-07-02 10:33:18,322 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,322 [model] Posterior to be computed for parameters {'Omega_m': 0.2689337940628663, 'b1': 0.600728251405974}
 2023-07-02 10:33:18,322 [prior] Evaluating prior at array([0.26893379, 0.60072825])
 2023-07-02 10:33:18,322 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,322 [model] Got input parameters: {'Omega_m': 0.2689337940628663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,322 [classy] Got parameters {'Omega_m': 0.2689337940628663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,322 [classy] Computing new state
 2023-07-02 10:33:18,322 [classy] Setting parameters: {'Omega_m': 0.2689337940628663, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.85029604885995}
 2023-07-02 10:33:18,366 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.130442
 2023-07-02 10:33:18,368 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,368 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,387 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4293
 2023-07-02 10:33:18,387 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,387 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.3696776200111712}
 2023-07-02 10:33:18,387 [prior] Evaluating prior at array([0.28000247, 0.36967762])
 2023-07-02 10:33:18,387 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,387 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3696776200111712, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,387 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,387 [classy] Re-using computed results
 2023-07-02 10:33:18,387 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:18,387 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3696776200111712, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,387 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,407 [fs_likelihood.fslikelihood] Computed log-likelihood = -85.3618
 2023-07-02 10:33:18,407 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,407 [model] Posterior to be computed for parameters {'Omega_m': 0.29901708086262907, 'b1': 0.600728251405974}
 2023-07-02 10:33:18,407 [prior] Evaluating prior at array([0.29901708, 0.60072825])
 2023-07-02 10:33:18,407 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,407 [model] Got input parameters: {'Omega_m': 0.29901708086262907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,407 [classy] Got parameters {'Omega_m': 0.29901708086262907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,407 [classy] Computing new state
 2023-07-02 10:33:18,407 [classy] Setting parameters: {'Omega_m': 0.29901708086262907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9122456701418}
 2023-07-02 10:33:18,452 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117071
 2023-07-02 10:33:18,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,454 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,473 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.135
 2023-07-02 10:33:18,473 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,474 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,474 [prior] Evaluating prior at array([0.28000247, 0.56415425])
 2023-07-02 10:33:18,474 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,474 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,474 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,474 [classy] Re-using computed results
 2023-07-02 10:33:18,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
 2023-07-02 10:33:18,474 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,474 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,493 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.14193
 2023-07-02 10:33:18,493 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,494 [mcmc] New sample, #16:
   Omega_m:0.2800025, b1:0.6007283
 2023-07-02 10:33:18,494 [model] Posterior to be computed for parameters {'Omega_m': 0.28115025895647344, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,494 [prior] Evaluating prior at array([0.28115026, 0.56415425])
 2023-07-02 10:33:18,494 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,494 [model] Got input parameters: {'Omega_m': 0.28115025895647344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,494 [classy] Got parameters {'Omega_m': 0.28115025895647344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,494 [classy] Computing new state
 2023-07-02 10:33:18,494 [classy] Setting parameters: {'Omega_m': 0.28115025895647344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.20755764461194}
 2023-07-02 10:33:18,538 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,539 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0654488
 2023-07-02 10:33:18,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,540 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,559 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.60338
 2023-07-02 10:33:18,559 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,559 [mcmc] New sample, #17:
   Omega_m:0.2800025, b1:0.5641542
 2023-07-02 10:33:18,559 [model] Posterior to be computed for parameters {'Omega_m': 0.28115025895647344, 'b1': -2.012416078758141}
 2023-07-02 10:33:18,559 [prior] Evaluating prior at array([ 0.28115026, -2.01241608])
 2023-07-02 10:33:18,559 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:18,560 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,560 [prior] Evaluating prior at array([0.29063804, 0.56415425])
 2023-07-02 10:33:18,560 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,560 [model] Got input parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,560 [classy] Got parameters {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,560 [classy] Computing new state
 2023-07-02 10:33:18,560 [classy] Setting parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,605 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.97344050117687}
 2023-07-02 10:33:18,605 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,606 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0311386
 2023-07-02 10:33:18,606 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,606 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,626 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.85931
 2023-07-02 10:33:18,626 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,626 [mcmc] New sample, #18:
   Omega_m:0.2811503, b1:0.5641542
 2023-07-02 10:33:18,627 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': 0.11978222459916943}
 2023-07-02 10:33:18,627 [prior] Evaluating prior at array([0.29063804, 0.11978222])
 2023-07-02 10:33:18,627 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,627 [model] Got input parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.11978222459916943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,627 [classy] Got parameters {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,627 [classy] Re-using computed results
 2023-07-02 10:33:18,627 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.97344050117687}
 2023-07-02 10:33:18,627 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,627 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.11978222459916943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,627 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,647 [fs_likelihood.fslikelihood] Computed log-likelihood = -303.604
 2023-07-02 10:33:18,647 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,647 [model] Posterior to be computed for parameters {'Omega_m': 0.2777024260879715, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,647 [prior] Evaluating prior at array([0.27770243, 0.56415425])
 2023-07-02 10:33:18,647 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,647 [model] Got input parameters: {'Omega_m': 0.2777024260879715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,647 [classy] Got parameters {'Omega_m': 0.2777024260879715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,647 [classy] Computing new state
 2023-07-02 10:33:18,647 [classy] Setting parameters: {'Omega_m': 0.2777024260879715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,691 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.66491972708485}
 2023-07-02 10:33:18,691 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0813379
 2023-07-02 10:33:18,693 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,693 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,712 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.3553
 2023-07-02 10:33:18,712 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,712 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': 1.111948483680984}
 2023-07-02 10:33:18,712 [prior] Evaluating prior at array([0.29063804, 1.11194848])
 2023-07-02 10:33:18,713 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,713 [model] Got input parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.111948483680984, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,713 [classy] Got parameters {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,713 [classy] Re-using computed results
 2023-07-02 10:33:18,713 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.97344050117687}
 2023-07-02 10:33:18,713 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,713 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.111948483680984, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,713 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,732 [fs_likelihood.fslikelihood] Computed log-likelihood = -1410.25
 2023-07-02 10:33:18,732 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,732 [model] Posterior to be computed for parameters {'Omega_m': 0.2832057139110705, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,733 [prior] Evaluating prior at array([0.28320571, 0.56415425])
 2023-07-02 10:33:18,733 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,733 [model] Got input parameters: {'Omega_m': 0.2832057139110705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,733 [classy] Got parameters {'Omega_m': 0.2832057139110705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,733 [classy] Computing new state
 2023-07-02 10:33:18,733 [classy] Setting parameters: {'Omega_m': 0.2832057139110705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.93717686683792}
 2023-07-02 10:33:18,777 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,779 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0568605
 2023-07-02 10:33:18,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,779 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,798 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75039
 2023-07-02 10:33:18,798 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,799 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': -1.1661240927395355}
 2023-07-02 10:33:18,799 [prior] Evaluating prior at array([ 0.29063804, -1.16612409])
 2023-07-02 10:33:18,799 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:18,799 [model] Posterior to be computed for parameters {'Omega_m': 0.2964020393345352, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,799 [prior] Evaluating prior at array([0.29640204, 0.56415425])
 2023-07-02 10:33:18,799 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,799 [model] Got input parameters: {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,799 [classy] Got parameters {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,799 [classy] Computing new state
 2023-07-02 10:33:18,799 [classy] Setting parameters: {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.24063190904653}
 2023-07-02 10:33:18,843 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0167196
 2023-07-02 10:33:18,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,845 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.6799
 2023-07-02 10:33:18,865 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,865 [mcmc] New sample, #19:
   Omega_m:0.290638, b1:0.5641542
 2023-07-02 10:33:18,865 [model] Posterior to be computed for parameters {'Omega_m': 0.2964020393345352, 'b1': 0.39815527679972185}
 2023-07-02 10:33:18,865 [prior] Evaluating prior at array([0.29640204, 0.39815528])
 2023-07-02 10:33:18,865 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,865 [model] Got input parameters: {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39815527679972185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,865 [classy] Got parameters {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,865 [classy] Re-using computed results
 2023-07-02 10:33:18,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.24063190904653}
 2023-07-02 10:33:18,865 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39815527679972185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,865 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,885 [fs_likelihood.fslikelihood] Computed log-likelihood = -41.8102
 2023-07-02 10:33:18,885 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,885 [model] Posterior to be computed for parameters {'Omega_m': 0.2939256037104231, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,885 [prior] Evaluating prior at array([0.2939256 , 0.56415425])
 2023-07-02 10:33:18,885 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,885 [model] Got input parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,885 [classy] Got parameters {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,885 [classy] Computing new state
 2023-07-02 10:33:18,885 [classy] Setting parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:18,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55394635761508}
 2023-07-02 10:33:18,929 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:18,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0223391
 2023-07-02 10:33:18,931 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,931 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,950 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61921
 2023-07-02 10:33:18,950 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,950 [mcmc] New sample, #20:
   Omega_m:0.296402, b1:0.5641542
 2023-07-02 10:33:18,951 [model] Posterior to be computed for parameters {'Omega_m': 0.2939256037104231, 'b1': 0.013091685842807177}
 2023-07-02 10:33:18,951 [prior] Evaluating prior at array([0.2939256 , 0.01309169])
 2023-07-02 10:33:18,951 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,951 [model] Got input parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.013091685842807177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,951 [classy] Got parameters {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,951 [classy] Re-using computed results
 2023-07-02 10:33:18,951 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55394635761508}
 2023-07-02 10:33:18,951 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:18,951 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.013091685842807177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,951 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:18,971 [fs_likelihood.fslikelihood] Computed log-likelihood = -415.081
 2023-07-02 10:33:18,971 [model] Computed derived parameters: {}
 2023-07-02 10:33:18,971 [model] Posterior to be computed for parameters {'Omega_m': 0.28103501242931417, 'b1': 0.5641542472169249}
 2023-07-02 10:33:18,971 [prior] Evaluating prior at array([0.28103501, 0.56415425])
 2023-07-02 10:33:18,971 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:18,971 [model] Got input parameters: {'Omega_m': 0.28103501242931417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:18,971 [classy] Got parameters {'Omega_m': 0.28103501242931417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:18,971 [classy] Computing new state
 2023-07-02 10:33:18,971 [classy] Setting parameters: {'Omega_m': 0.28103501242931417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.22277016819226}
 2023-07-02 10:33:19,015 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0659499
 2023-07-02 10:33:19,017 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,017 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,037 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.65544
 2023-07-02 10:33:19,037 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,037 [model] Posterior to be computed for parameters {'Omega_m': 0.2939256037104231, 'b1': 0.4922984444056192}
 2023-07-02 10:33:19,037 [prior] Evaluating prior at array([0.2939256 , 0.49229844])
 2023-07-02 10:33:19,037 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,037 [model] Got input parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4922984444056192, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,037 [classy] Got parameters {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,037 [classy] Re-using computed results
 2023-07-02 10:33:19,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55394635761508}
 2023-07-02 10:33:19,037 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,037 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4922984444056192, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,037 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,057 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.25311
 2023-07-02 10:33:19,057 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,057 [model] Posterior to be computed for parameters {'Omega_m': 0.2907050934637481, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,057 [prior] Evaluating prior at array([0.29070509, 0.56415425])
 2023-07-02 10:33:19,057 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,057 [model] Got input parameters: {'Omega_m': 0.2907050934637481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,058 [classy] Got parameters {'Omega_m': 0.2907050934637481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,058 [classy] Computing new state
 2023-07-02 10:33:19,058 [classy] Setting parameters: {'Omega_m': 0.2907050934637481, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,102 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.96484413873634}
 2023-07-02 10:33:19,102 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,103 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0309436
 2023-07-02 10:33:19,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,103 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,125 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.85076
 2023-07-02 10:33:19,125 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,125 [mcmc] New sample, #21:
   Omega_m:0.2939256, b1:0.5641542
 2023-07-02 10:33:19,125 [model] Posterior to be computed for parameters {'Omega_m': 0.2907050934637481, 'b1': -0.9116768543470722}
 2023-07-02 10:33:19,125 [prior] Evaluating prior at array([ 0.29070509, -0.91167685])
 2023-07-02 10:33:19,126 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:19,126 [model] Posterior to be computed for parameters {'Omega_m': 0.2621977489060774, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,126 [prior] Evaluating prior at array([0.26219775, 0.56415425])
 2023-07-02 10:33:19,126 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,126 [model] Got input parameters: {'Omega_m': 0.2621977489060774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,126 [classy] Got parameters {'Omega_m': 0.2621977489060774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,126 [classy] Computing new state
 2023-07-02 10:33:19,126 [classy] Setting parameters: {'Omega_m': 0.2621977489060774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.7833330260691}
 2023-07-02 10:33:19,171 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.177079
 2023-07-02 10:33:19,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,173 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,193 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.2062
 2023-07-02 10:33:19,193 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,193 [model] Posterior to be computed for parameters {'Omega_m': 0.2907050934637481, 'b1': -0.745652029519498}
 2023-07-02 10:33:19,193 [prior] Evaluating prior at array([ 0.29070509, -0.74565203])
 2023-07-02 10:33:19,193 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:19,193 [model] Posterior to be computed for parameters {'Omega_m': 0.29242131069025074, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,193 [prior] Evaluating prior at array([0.29242131, 0.56415425])
 2023-07-02 10:33:19,193 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,193 [model] Got input parameters: {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,193 [classy] Got parameters {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,193 [classy] Computing new state
 2023-07-02 10:33:19,193 [classy] Setting parameters: {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,237 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.74538977626483}
 2023-07-02 10:33:19,237 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,239 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.026174
 2023-07-02 10:33:19,239 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,239 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,259 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.68368
 2023-07-02 10:33:19,259 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,259 [mcmc] New sample, #22:
   Omega_m:0.2907051, b1:0.5641542
 2023-07-02 10:33:19,259 [model] Posterior to be computed for parameters {'Omega_m': 0.29242131069025074, 'b1': 0.5123966182377673}
 2023-07-02 10:33:19,259 [prior] Evaluating prior at array([0.29242131, 0.51239662])
 2023-07-02 10:33:19,260 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,260 [model] Got input parameters: {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123966182377673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,260 [classy] Got parameters {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,260 [classy] Re-using computed results
 2023-07-02 10:33:19,260 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.74538977626483}
 2023-07-02 10:33:19,260 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,260 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123966182377673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,260 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,280 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.42254
 2023-07-02 10:33:19,280 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,280 [model] Posterior to be computed for parameters {'Omega_m': 0.2784923906684726, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,280 [prior] Evaluating prior at array([0.27849239, 0.56415425])
 2023-07-02 10:33:19,280 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,280 [model] Got input parameters: {'Omega_m': 0.2784923906684726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,280 [classy] Got parameters {'Omega_m': 0.2784923906684726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,281 [classy] Computing new state
 2023-07-02 10:33:19,281 [classy] Setting parameters: {'Omega_m': 0.2784923906684726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.55970275676412}
 2023-07-02 10:33:19,324 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0775313
 2023-07-02 10:33:19,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,326 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,346 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.91837
 2023-07-02 10:33:19,346 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,346 [model] Posterior to be computed for parameters {'Omega_m': 0.29242131069025074, 'b1': -0.2808724116435116}
 2023-07-02 10:33:19,346 [prior] Evaluating prior at array([ 0.29242131, -0.28087241])
 2023-07-02 10:33:19,346 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:19,346 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,346 [prior] Evaluating prior at array([0.29483015, 0.56415425])
 2023-07-02 10:33:19,346 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,346 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,346 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,346 [classy] Computing new state
 2023-07-02 10:33:19,346 [classy] Setting parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
 2023-07-02 10:33:19,391 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,392 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0201871
 2023-07-02 10:33:19,392 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,392 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,412 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61732
 2023-07-02 10:33:19,413 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,413 [mcmc] New sample, #23:
   Omega_m:0.2924213, b1:0.5641542
 2023-07-02 10:33:19,413 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': -0.9085892166087045}
 2023-07-02 10:33:19,413 [prior] Evaluating prior at array([ 0.29483015, -0.90858922])
 2023-07-02 10:33:19,413 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:19,413 [model] Posterior to be computed for parameters {'Omega_m': 0.30607781746448515, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,413 [prior] Evaluating prior at array([0.30607782, 0.56415425])
 2023-07-02 10:33:19,413 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,413 [model] Got input parameters: {'Omega_m': 0.30607781746448515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,413 [classy] Got parameters {'Omega_m': 0.30607781746448515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,413 [classy] Computing new state
 2023-07-02 10:33:19,413 [classy] Setting parameters: {'Omega_m': 0.30607781746448515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.038054614937}
 2023-07-02 10:33:19,458 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,459 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00275973
 2023-07-02 10:33:19,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,480 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.90676
 2023-07-02 10:33:19,480 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,480 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.13587497981547075}
 2023-07-02 10:33:19,480 [prior] Evaluating prior at array([0.29483015, 0.13587498])
 2023-07-02 10:33:19,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,480 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.13587497981547075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,480 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,480 [classy] Re-using computed results
 2023-07-02 10:33:19,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
 2023-07-02 10:33:19,480 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.13587497981547075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,500 [fs_likelihood.fslikelihood] Computed log-likelihood = -277.953
 2023-07-02 10:33:19,500 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,500 [model] Posterior to be computed for parameters {'Omega_m': 0.27439333666368143, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,500 [prior] Evaluating prior at array([0.27439334, 0.56415425])
 2023-07-02 10:33:19,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,500 [model] Got input parameters: {'Omega_m': 0.27439333666368143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,500 [classy] Got parameters {'Omega_m': 0.27439333666368143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,500 [classy] Computing new state
 2023-07-02 10:33:19,501 [classy] Setting parameters: {'Omega_m': 0.27439333666368143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.10844810552507}
 2023-07-02 10:33:19,544 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.098375
 2023-07-02 10:33:19,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,546 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.41509
 2023-07-02 10:33:19,566 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,566 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': -0.37872999904416405}
 2023-07-02 10:33:19,566 [prior] Evaluating prior at array([ 0.29483015, -0.37873   ])
 2023-07-02 10:33:19,566 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:19,567 [model] Posterior to be computed for parameters {'Omega_m': 0.2616583785661771, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,567 [prior] Evaluating prior at array([0.26165838, 0.56415425])
 2023-07-02 10:33:19,567 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,567 [model] Got input parameters: {'Omega_m': 0.2616583785661771, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,567 [classy] Got parameters {'Omega_m': 0.2616583785661771, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,567 [classy] Computing new state
 2023-07-02 10:33:19,567 [classy] Setting parameters: {'Omega_m': 0.2616583785661771, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.8589102645998}
 2023-07-02 10:33:19,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.181162
 2023-07-02 10:33:19,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,612 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.7997
 2023-07-02 10:33:19,632 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,633 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.24683867263038728}
 2023-07-02 10:33:19,633 [prior] Evaluating prior at array([0.29483015, 0.24683867])
 2023-07-02 10:33:19,633 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,633 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24683867263038728, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,633 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,633 [classy] Re-using computed results
 2023-07-02 10:33:19,633 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
 2023-07-02 10:33:19,633 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24683867263038728, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,633 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,653 [fs_likelihood.fslikelihood] Computed log-likelihood = -164.072
 2023-07-02 10:33:19,653 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,653 [model] Posterior to be computed for parameters {'Omega_m': 0.2867979817404427, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,653 [prior] Evaluating prior at array([0.28679798, 0.56415425])
 2023-07-02 10:33:19,653 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,653 [model] Got input parameters: {'Omega_m': 0.2867979817404427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,653 [classy] Got parameters {'Omega_m': 0.2867979817404427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,653 [classy] Computing new state
 2023-07-02 10:33:19,653 [classy] Setting parameters: {'Omega_m': 0.2867979817404427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,697 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.46865684672377}
 2023-07-02 10:33:19,697 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,699 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0433994
 2023-07-02 10:33:19,699 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,699 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,719 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60294
 2023-07-02 10:33:19,719 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,719 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.19366152525108582}
 2023-07-02 10:33:19,719 [prior] Evaluating prior at array([0.29483015, 0.19366153])
 2023-07-02 10:33:19,719 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,719 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.19366152525108582, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,720 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,720 [classy] Re-using computed results
 2023-07-02 10:33:19,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
 2023-07-02 10:33:19,720 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.19366152525108582, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,720 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,740 [fs_likelihood.fslikelihood] Computed log-likelihood = -216.937
 2023-07-02 10:33:19,740 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,740 [model] Posterior to be computed for parameters {'Omega_m': 0.31167255996161713, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,740 [prior] Evaluating prior at array([0.31167256, 0.56415425])
 2023-07-02 10:33:19,740 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,740 [model] Got input parameters: {'Omega_m': 0.31167255996161713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,741 [classy] Got parameters {'Omega_m': 0.31167255996161713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,741 [classy] Computing new state
 2023-07-02 10:33:19,741 [classy] Setting parameters: {'Omega_m': 0.31167255996161713, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35787829275043}
 2023-07-02 10:33:19,790 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000242827
 2023-07-02 10:33:19,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,792 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,812 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.64013
 2023-07-02 10:33:19,812 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,812 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 1.6426111202284543}
 2023-07-02 10:33:19,812 [prior] Evaluating prior at array([0.29483015, 1.64261112])
 2023-07-02 10:33:19,812 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,812 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6426111202284543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,812 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,812 [classy] Re-using computed results
 2023-07-02 10:33:19,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
 2023-07-02 10:33:19,812 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6426111202284543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,812 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,832 [fs_likelihood.fslikelihood] Computed log-likelihood = -8069.5
 2023-07-02 10:33:19,833 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,833 [model] Posterior to be computed for parameters {'Omega_m': 0.2945983862465899, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,833 [prior] Evaluating prior at array([0.29459839, 0.56415425])
 2023-07-02 10:33:19,833 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,833 [model] Got input parameters: {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,833 [classy] Got parameters {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,833 [classy] Computing new state
 2023-07-02 10:33:19,833 [classy] Setting parameters: {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.468603360845}
 2023-07-02 10:33:19,877 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,879 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0207276
 2023-07-02 10:33:19,879 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,879 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61516
 2023-07-02 10:33:19,899 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,899 [mcmc] New sample, #24:
   Omega_m:0.2948301, b1:0.5641542
 2023-07-02 10:33:19,899 [model] Posterior to be computed for parameters {'Omega_m': 0.2945983862465899, 'b1': 0.7746668380209869}
 2023-07-02 10:33:19,899 [prior] Evaluating prior at array([0.29459839, 0.77466684])
 2023-07-02 10:33:19,899 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,899 [model] Got input parameters: {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7746668380209869, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,899 [classy] Got parameters {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,899 [classy] Re-using computed results
 2023-07-02 10:33:19,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.468603360845}
 2023-07-02 10:33:19,899 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:19,899 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7746668380209869, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,900 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,919 [fs_likelihood.fslikelihood] Computed log-likelihood = -186.004
 2023-07-02 10:33:19,919 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,919 [model] Posterior to be computed for parameters {'Omega_m': 0.3005330784593588, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,920 [prior] Evaluating prior at array([0.30053308, 0.56415425])
 2023-07-02 10:33:19,920 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,920 [model] Got input parameters: {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,920 [classy] Got parameters {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,920 [classy] Computing new state
 2023-07-02 10:33:19,920 [classy] Setting parameters: {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:19,964 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72301580729032}
 2023-07-02 10:33:19,964 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:19,965 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00922739
 2023-07-02 10:33:19,965 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,965 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:19,986 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.24304
 2023-07-02 10:33:19,986 [model] Computed derived parameters: {}
 2023-07-02 10:33:19,986 [mcmc] New sample, #25:
   Omega_m:0.2945984, b1:0.5641542
 2023-07-02 10:33:19,986 [model] Posterior to be computed for parameters {'Omega_m': 0.3005330784593588, 'b1': -0.2128396236237371}
 2023-07-02 10:33:19,986 [prior] Evaluating prior at array([ 0.30053308, -0.21283962])
 2023-07-02 10:33:19,986 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:19,986 [model] Posterior to be computed for parameters {'Omega_m': 0.2804668243338576, 'b1': 0.5641542472169249}
 2023-07-02 10:33:19,987 [prior] Evaluating prior at array([0.28046682, 0.56415425])
 2023-07-02 10:33:19,987 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:19,987 [model] Got input parameters: {'Omega_m': 0.2804668243338576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:19,987 [classy] Got parameters {'Omega_m': 0.2804668243338576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:19,987 [classy] Computing new state
 2023-07-02 10:33:19,987 [classy] Setting parameters: {'Omega_m': 0.2804668243338576, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.29783400633306}
 2023-07-02 10:33:20,031 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,033 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684497
 2023-07-02 10:33:20,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,033 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,053 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.91868
 2023-07-02 10:33:20,053 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,053 [model] Posterior to be computed for parameters {'Omega_m': 0.3005330784593588, 'b1': 1.0225938183602998}
 2023-07-02 10:33:20,053 [prior] Evaluating prior at array([0.30053308, 1.02259382])
 2023-07-02 10:33:20,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,053 [model] Got input parameters: {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0225938183602998, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,054 [classy] Got parameters {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,054 [classy] Re-using computed results
 2023-07-02 10:33:20,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72301580729032}
 2023-07-02 10:33:20,054 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,054 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0225938183602998, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,054 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,074 [fs_likelihood.fslikelihood] Computed log-likelihood = -1028.49
 2023-07-02 10:33:20,074 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,074 [model] Posterior to be computed for parameters {'Omega_m': 0.3001152593925499, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,074 [prior] Evaluating prior at array([0.30011526, 0.56415425])
 2023-07-02 10:33:20,074 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,074 [model] Got input parameters: {'Omega_m': 0.3001152593925499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,074 [classy] Got parameters {'Omega_m': 0.3001152593925499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,074 [classy] Computing new state
 2023-07-02 10:33:20,074 [classy] Setting parameters: {'Omega_m': 0.3001152593925499, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.77508512200663}
 2023-07-02 10:33:20,118 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,120 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00987987
 2023-07-02 10:33:20,120 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,120 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,148 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.15983
 2023-07-02 10:33:20,148 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,148 [mcmc] New sample, #26:
   Omega_m:0.3005331, b1:0.5641542
 2023-07-02 10:33:20,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3001152593925499, 'b1': -0.1714778572676373}
 2023-07-02 10:33:20,148 [prior] Evaluating prior at array([ 0.30011526, -0.17147786])
 2023-07-02 10:33:20,148 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:20,149 [model] Posterior to be computed for parameters {'Omega_m': 0.2997795967688109, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,149 [prior] Evaluating prior at array([0.2997796 , 0.56415425])
 2023-07-02 10:33:20,149 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,149 [model] Got input parameters: {'Omega_m': 0.2997795967688109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,149 [classy] Got parameters {'Omega_m': 0.2997795967688109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,149 [classy] Computing new state
 2023-07-02 10:33:20,149 [classy] Setting parameters: {'Omega_m': 0.2997795967688109, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,192 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.81696070230657}
 2023-07-02 10:33:20,193 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,194 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.010421
 2023-07-02 10:33:20,194 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,194 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,214 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.09726
 2023-07-02 10:33:20,214 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,214 [mcmc] New sample, #27:
   Omega_m:0.3001153, b1:0.5641542
 2023-07-02 10:33:20,214 [model] Posterior to be computed for parameters {'Omega_m': 0.2997795967688109, 'b1': -1.1325434295810015}
 2023-07-02 10:33:20,215 [prior] Evaluating prior at array([ 0.2997796 , -1.13254343])
 2023-07-02 10:33:20,215 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:20,215 [model] Posterior to be computed for parameters {'Omega_m': 0.2905610819816365, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,215 [prior] Evaluating prior at array([0.29056108, 0.56415425])
 2023-07-02 10:33:20,215 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,215 [model] Got input parameters: {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,215 [classy] Got parameters {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,215 [classy] Computing new state
 2023-07-02 10:33:20,215 [classy] Setting parameters: {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,259 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.98330711916648}
 2023-07-02 10:33:20,259 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,261 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.031363
 2023-07-02 10:33:20,261 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,261 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,281 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86932
 2023-07-02 10:33:20,281 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,281 [mcmc] New sample, #28:
   Omega_m:0.2997796, b1:0.5641542
 2023-07-02 10:33:20,281 [model] Posterior to be computed for parameters {'Omega_m': 0.2905610819816365, 'b1': 0.8013423566117592}
 2023-07-02 10:33:20,281 [prior] Evaluating prior at array([0.29056108, 0.80134236])
 2023-07-02 10:33:20,281 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,281 [model] Got input parameters: {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8013423566117592, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,281 [classy] Got parameters {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,281 [classy] Re-using computed results
 2023-07-02 10:33:20,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.98330711916648}
 2023-07-02 10:33:20,281 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,281 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8013423566117592, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,281 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,301 [fs_likelihood.fslikelihood] Computed log-likelihood = -221.534
 2023-07-02 10:33:20,301 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,302 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,302 [prior] Evaluating prior at array([0.28944175, 0.56415425])
 2023-07-02 10:33:20,302 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,302 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,302 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,302 [classy] Computing new state
 2023-07-02 10:33:20,302 [classy] Setting parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
 2023-07-02 10:33:20,346 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0347266
 2023-07-02 10:33:20,348 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,348 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,368 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.03746
 2023-07-02 10:33:20,368 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,368 [mcmc] New sample, #29:
   Omega_m:0.2905611, b1:0.5641542
 2023-07-02 10:33:20,368 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 0.8037144210457337}
 2023-07-02 10:33:20,368 [prior] Evaluating prior at array([0.28944175, 0.80371442])
 2023-07-02 10:33:20,368 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,368 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8037144210457337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,368 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,368 [classy] Re-using computed results
 2023-07-02 10:33:20,368 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
 2023-07-02 10:33:20,368 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,368 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8037144210457337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,368 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,388 [fs_likelihood.fslikelihood] Computed log-likelihood = -222.234
 2023-07-02 10:33:20,389 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,389 [model] Posterior to be computed for parameters {'Omega_m': 0.28690029986869875, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,389 [prior] Evaluating prior at array([0.2869003 , 0.56415425])
 2023-07-02 10:33:20,389 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,389 [model] Got input parameters: {'Omega_m': 0.28690029986869875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,389 [classy] Got parameters {'Omega_m': 0.28690029986869875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,389 [classy] Computing new state
 2023-07-02 10:33:20,389 [classy] Setting parameters: {'Omega_m': 0.28690029986869875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.45538929862505}
 2023-07-02 10:33:20,433 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0430445
 2023-07-02 10:33:20,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,434 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,455 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.57665
 2023-07-02 10:33:20,455 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,455 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 1.6742641404200946}
 2023-07-02 10:33:20,455 [prior] Evaluating prior at array([0.28944175, 1.67426414])
 2023-07-02 10:33:20,455 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,455 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6742641404200946, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,455 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,455 [classy] Re-using computed results
 2023-07-02 10:33:20,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
 2023-07-02 10:33:20,455 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,455 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6742641404200946, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,455 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,475 [fs_likelihood.fslikelihood] Computed log-likelihood = -8433.9
 2023-07-02 10:33:20,475 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,475 [model] Posterior to be computed for parameters {'Omega_m': 0.32277554293051863, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,475 [prior] Evaluating prior at array([0.32277554, 0.56415425])
 2023-07-02 10:33:20,476 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,476 [model] Got input parameters: {'Omega_m': 0.32277554293051863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,476 [classy] Got parameters {'Omega_m': 0.32277554293051863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,476 [classy] Computing new state
 2023-07-02 10:33:20,476 [classy] Setting parameters: {'Omega_m': 0.32277554293051863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03958908034917}
 2023-07-02 10:33:20,520 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00653414
 2023-07-02 10:33:20,521 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,521 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,542 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.2019
 2023-07-02 10:33:20,542 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,542 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 1.4340643419224306}
 2023-07-02 10:33:20,542 [prior] Evaluating prior at array([0.28944175, 1.43406434])
 2023-07-02 10:33:20,542 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,542 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4340643419224306, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,542 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,542 [classy] Re-using computed results
 2023-07-02 10:33:20,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
 2023-07-02 10:33:20,542 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,542 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4340643419224306, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,542 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,563 [fs_likelihood.fslikelihood] Computed log-likelihood = -4408.03
 2023-07-02 10:33:20,563 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,563 [model] Posterior to be computed for parameters {'Omega_m': 0.30295063089933244, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,563 [prior] Evaluating prior at array([0.30295063, 0.56415425])
 2023-07-02 10:33:20,563 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,563 [model] Got input parameters: {'Omega_m': 0.30295063089933244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,563 [classy] Got parameters {'Omega_m': 0.30295063089933244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,563 [classy] Computing new state
 2023-07-02 10:33:20,563 [classy] Setting parameters: {'Omega_m': 0.30295063089933244, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,607 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.42301723965483}
 2023-07-02 10:33:20,607 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00591048
 2023-07-02 10:33:20,609 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,609 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,629 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.8405
 2023-07-02 10:33:20,629 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,629 [mcmc] New sample, #30:
   Omega_m:0.2894417, b1:0.5641542
 2023-07-02 10:33:20,630 [model] Posterior to be computed for parameters {'Omega_m': 0.30295063089933244, 'b1': -0.2732113224454442}
 2023-07-02 10:33:20,630 [prior] Evaluating prior at array([ 0.30295063, -0.27321132])
 2023-07-02 10:33:20,630 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:20,630 [model] Posterior to be computed for parameters {'Omega_m': 0.30366844514979685, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,630 [prior] Evaluating prior at array([0.30366845, 0.56415425])
 2023-07-02 10:33:20,630 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,630 [model] Got input parameters: {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,630 [classy] Got parameters {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,630 [classy] Computing new state
 2023-07-02 10:33:20,630 [classy] Setting parameters: {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3343464303195}
 2023-07-02 10:33:20,674 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,676 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00507447
 2023-07-02 10:33:20,676 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,676 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,696 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.05599
 2023-07-02 10:33:20,697 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,697 [mcmc] New sample, #31:
   Omega_m:0.3029506, b1:0.5641542
 2023-07-02 10:33:20,697 [model] Posterior to be computed for parameters {'Omega_m': 0.30366844514979685, 'b1': 0.11577309985055517}
 2023-07-02 10:33:20,697 [prior] Evaluating prior at array([0.30366845, 0.1157731 ])
 2023-07-02 10:33:20,697 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,697 [model] Got input parameters: {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.11577309985055517, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,697 [classy] Got parameters {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,697 [classy] Re-using computed results
 2023-07-02 10:33:20,697 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3343464303195}
 2023-07-02 10:33:20,697 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.11577309985055517, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,697 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,717 [fs_likelihood.fslikelihood] Computed log-likelihood = -283.026
 2023-07-02 10:33:20,717 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,717 [model] Posterior to be computed for parameters {'Omega_m': 0.2854367779256794, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,717 [prior] Evaluating prior at array([0.28543678, 0.56415425])
 2023-07-02 10:33:20,718 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,718 [model] Got input parameters: {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,718 [classy] Got parameters {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,718 [classy] Computing new state
 2023-07-02 10:33:20,718 [classy] Setting parameters: {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,761 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.64559075835916}
 2023-07-02 10:33:20,761 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,763 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0482707
 2023-07-02 10:33:20,763 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,763 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,783 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.98634
 2023-07-02 10:33:20,783 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,783 [mcmc] New sample, #32:
   Omega_m:0.3036684, b1:0.5641542
 2023-07-02 10:33:20,784 [model] Posterior to be computed for parameters {'Omega_m': 0.2854367779256794, 'b1': 0.42099387633952906}
 2023-07-02 10:33:20,784 [prior] Evaluating prior at array([0.28543678, 0.42099388])
 2023-07-02 10:33:20,784 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,784 [model] Got input parameters: {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42099387633952906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,784 [classy] Got parameters {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,784 [classy] Re-using computed results
 2023-07-02 10:33:20,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.64559075835916}
 2023-07-02 10:33:20,784 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42099387633952906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,784 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,804 [fs_likelihood.fslikelihood] Computed log-likelihood = -43.0887
 2023-07-02 10:33:20,804 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,805 [model] Posterior to be computed for parameters {'Omega_m': 0.2966337824155873, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,805 [prior] Evaluating prior at array([0.29663378, 0.56415425])
 2023-07-02 10:33:20,805 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,805 [model] Got input parameters: {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,805 [classy] Got parameters {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,805 [classy] Computing new state
 2023-07-02 10:33:20,805 [classy] Setting parameters: {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.21143016255388}
 2023-07-02 10:33:20,849 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0162375
 2023-07-02 10:33:20,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,851 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,871 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.6962
 2023-07-02 10:33:20,871 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,871 [mcmc] New sample, #33:
   Omega_m:0.2854368, b1:0.5641542
 2023-07-02 10:33:20,871 [model] Posterior to be computed for parameters {'Omega_m': 0.2966337824155873, 'b1': 0.3522189405098124}
 2023-07-02 10:33:20,871 [prior] Evaluating prior at array([0.29663378, 0.35221894])
 2023-07-02 10:33:20,871 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,871 [model] Got input parameters: {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3522189405098124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,872 [classy] Got parameters {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,872 [classy] Re-using computed results
 2023-07-02 10:33:20,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.21143016255388}
 2023-07-02 10:33:20,872 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,872 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3522189405098124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,872 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,891 [fs_likelihood.fslikelihood] Computed log-likelihood = -71.5437
 2023-07-02 10:33:20,891 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,892 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,892 [prior] Evaluating prior at array([0.29448202, 0.56415425])
 2023-07-02 10:33:20,892 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,892 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,892 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,892 [classy] Computing new state
 2023-07-02 10:33:20,892 [classy] Setting parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:20,936 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
 2023-07-02 10:33:20,936 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:20,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0210017
 2023-07-02 10:33:20,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,937 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61477
 2023-07-02 10:33:20,958 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,958 [mcmc] New sample, #34:
   Omega_m:0.2966338, b1:0.5641542
 2023-07-02 10:33:20,958 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.47492093010750247}
 2023-07-02 10:33:20,958 [prior] Evaluating prior at array([0.29448202, 0.47492093])
 2023-07-02 10:33:20,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,958 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47492093010750247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,958 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,958 [classy] Re-using computed results
 2023-07-02 10:33:20,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
 2023-07-02 10:33:20,958 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:20,958 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47492093010750247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,959 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:20,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.43943
 2023-07-02 10:33:20,978 [model] Computed derived parameters: {}
 2023-07-02 10:33:20,979 [model] Posterior to be computed for parameters {'Omega_m': 0.2821014324407688, 'b1': 0.5641542472169249}
 2023-07-02 10:33:20,979 [prior] Evaluating prior at array([0.28210143, 0.56415425])
 2023-07-02 10:33:20,979 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:20,979 [model] Got input parameters: {'Omega_m': 0.2821014324407688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:20,979 [classy] Got parameters {'Omega_m': 0.2821014324407688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:20,979 [classy] Computing new state
 2023-07-02 10:33:20,979 [classy] Setting parameters: {'Omega_m': 0.2821014324407688, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.0822287036112}
 2023-07-02 10:33:21,023 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,025 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0613934
 2023-07-02 10:33:21,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,025 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,045 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.19088
 2023-07-02 10:33:21,045 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,045 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 1.226053315941949}
 2023-07-02 10:33:21,045 [prior] Evaluating prior at array([0.29448202, 1.22605332])
 2023-07-02 10:33:21,045 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,045 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.226053315941949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,045 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,045 [classy] Re-using computed results
 2023-07-02 10:33:21,045 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
 2023-07-02 10:33:21,045 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.226053315941949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,045 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,066 [fs_likelihood.fslikelihood] Computed log-likelihood = -2300.08
 2023-07-02 10:33:21,066 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,066 [model] Posterior to be computed for parameters {'Omega_m': 0.31203035024093445, 'b1': 0.5641542472169249}
 2023-07-02 10:33:21,066 [prior] Evaluating prior at array([0.31203035, 0.56415425])
 2023-07-02 10:33:21,066 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,066 [model] Got input parameters: {'Omega_m': 0.31203035024093445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,066 [classy] Got parameters {'Omega_m': 0.31203035024093445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,067 [classy] Computing new state
 2023-07-02 10:33:21,067 [classy] Setting parameters: {'Omega_m': 0.31203035024093445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,110 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31474783532698}
 2023-07-02 10:33:21,110 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,112 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000215002
 2023-07-02 10:33:21,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,112 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,135 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.85098
 2023-07-02 10:33:21,135 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,135 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.8280079237581743}
 2023-07-02 10:33:21,135 [prior] Evaluating prior at array([0.29448202, 0.82800792])
 2023-07-02 10:33:21,135 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,135 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8280079237581743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,135 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,135 [classy] Re-using computed results
 2023-07-02 10:33:21,135 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
 2023-07-02 10:33:21,135 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8280079237581743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,135 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -292.563
 2023-07-02 10:33:21,156 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3156198531201341, 'b1': 0.5641542472169249}
 2023-07-02 10:33:21,156 [prior] Evaluating prior at array([0.31561985, 0.56415425])
 2023-07-02 10:33:21,157 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,157 [model] Got input parameters: {'Omega_m': 0.3156198531201341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,157 [classy] Got parameters {'Omega_m': 0.3156198531201341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,157 [classy] Computing new state
 2023-07-02 10:33:21,157 [classy] Setting parameters: {'Omega_m': 0.3156198531201341, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88446042732156}
 2023-07-02 10:33:21,201 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000800791
 2023-07-02 10:33:21,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,202 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,222 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.206
 2023-07-02 10:33:21,223 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,223 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,223 [prior] Evaluating prior at array([0.29448202, 0.55192213])
 2023-07-02 10:33:21,223 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,223 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,223 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,223 [classy] Re-using computed results
 2023-07-02 10:33:21,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
 2023-07-02 10:33:21,223 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,223 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.253267
 2023-07-02 10:33:21,243 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,243 [mcmc] New sample, #35:
   Omega_m:0.294482, b1:0.5641542
 2023-07-02 10:33:21,243 [model] Posterior to be computed for parameters {'Omega_m': 0.31237177930015986, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,243 [prior] Evaluating prior at array([0.31237178, 0.55192213])
 2023-07-02 10:33:21,244 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,244 [model] Got input parameters: {'Omega_m': 0.31237177930015986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,244 [classy] Got parameters {'Omega_m': 0.31237177930015986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,244 [classy] Computing new state
 2023-07-02 10:33:21,244 [classy] Setting parameters: {'Omega_m': 0.31237177930015986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,288 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.27363139301724}
 2023-07-02 10:33:21,288 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,290 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00020314
 2023-07-02 10:33:21,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,290 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,312 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.28974
 2023-07-02 10:33:21,312 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,312 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': -0.20367294250460577}
 2023-07-02 10:33:21,312 [prior] Evaluating prior at array([ 0.29448202, -0.20367294])
 2023-07-02 10:33:21,312 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:21,312 [model] Posterior to be computed for parameters {'Omega_m': 0.2950824490263358, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,312 [prior] Evaluating prior at array([0.29508245, 0.55192213])
 2023-07-02 10:33:21,312 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,312 [model] Got input parameters: {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,312 [classy] Got parameters {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,313 [classy] Computing new state
 2023-07-02 10:33:21,313 [classy] Setting parameters: {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,358 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.40730383871465}
 2023-07-02 10:33:21,358 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,360 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0196075
 2023-07-02 10:33:21,360 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,360 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,380 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.184497
 2023-07-02 10:33:21,380 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,380 [mcmc] New sample, #36:
   Omega_m:0.294482, b1:0.5519221
 2023-07-02 10:33:21,380 [model] Posterior to be computed for parameters {'Omega_m': 0.2950824490263358, 'b1': 0.8947225993232409}
 2023-07-02 10:33:21,380 [prior] Evaluating prior at array([0.29508245, 0.8947226 ])
 2023-07-02 10:33:21,380 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,380 [model] Got input parameters: {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8947225993232409, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,380 [classy] Got parameters {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,380 [classy] Re-using computed results
 2023-07-02 10:33:21,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.40730383871465}
 2023-07-02 10:33:21,380 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,380 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8947225993232409, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,380 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,401 [fs_likelihood.fslikelihood] Computed log-likelihood = -473.193
 2023-07-02 10:33:21,401 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,401 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,401 [prior] Evaluating prior at array([0.29273405, 0.55192213])
 2023-07-02 10:33:21,401 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,401 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,401 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,401 [classy] Computing new state
 2023-07-02 10:33:21,401 [classy] Setting parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
 2023-07-02 10:33:21,445 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,447 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0253503
 2023-07-02 10:33:21,447 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,447 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,468 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.520962
 2023-07-02 10:33:21,468 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,468 [mcmc] New sample, #37:
   Omega_m:0.2950824, b1:0.5519221
 2023-07-02 10:33:21,469 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 1.440711872779902}
 2023-07-02 10:33:21,469 [prior] Evaluating prior at array([0.29273405, 1.44071187])
 2023-07-02 10:33:21,469 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,469 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.440711872779902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,469 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,469 [classy] Re-using computed results
 2023-07-02 10:33:21,469 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
 2023-07-02 10:33:21,469 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,469 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.440711872779902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,469 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -4602.06
 2023-07-02 10:33:21,490 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,490 [model] Posterior to be computed for parameters {'Omega_m': 0.2865468251573651, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,490 [prior] Evaluating prior at array([0.28654683, 0.55192213])
 2023-07-02 10:33:21,490 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,490 [model] Got input parameters: {'Omega_m': 0.2865468251573651, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,490 [classy] Got parameters {'Omega_m': 0.2865468251573651, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,490 [classy] Computing new state
 2023-07-02 10:33:21,490 [classy] Setting parameters: {'Omega_m': 0.2865468251573651, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,534 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.50124421138528}
 2023-07-02 10:33:21,534 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,536 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0442771
 2023-07-02 10:33:21,536 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,536 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,556 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.27575
 2023-07-02 10:33:21,556 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,557 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 0.6144424358556678}
 2023-07-02 10:33:21,557 [prior] Evaluating prior at array([0.29273405, 0.61444244])
 2023-07-02 10:33:21,557 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,557 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6144424358556678, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,557 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,557 [classy] Re-using computed results
 2023-07-02 10:33:21,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
 2023-07-02 10:33:21,557 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,557 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6144424358556678, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,557 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,577 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5554
 2023-07-02 10:33:21,577 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,577 [model] Posterior to be computed for parameters {'Omega_m': 0.28360540581866, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,577 [prior] Evaluating prior at array([0.28360541, 0.55192213])
 2023-07-02 10:33:21,577 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,577 [model] Got input parameters: {'Omega_m': 0.28360540581866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,577 [classy] Got parameters {'Omega_m': 0.28360540581866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,577 [classy] Computing new state
 2023-07-02 10:33:21,577 [classy] Setting parameters: {'Omega_m': 0.28360540581866, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,621 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.8847915800065}
 2023-07-02 10:33:21,621 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,623 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0552657
 2023-07-02 10:33:21,623 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,623 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,643 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.55146
 2023-07-02 10:33:21,643 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,643 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 0.37530129545493823}
 2023-07-02 10:33:21,643 [prior] Evaluating prior at array([0.29273405, 0.3753013 ])
 2023-07-02 10:33:21,644 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,644 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37530129545493823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,644 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,644 [classy] Re-using computed results
 2023-07-02 10:33:21,644 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
 2023-07-02 10:33:21,644 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,644 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37530129545493823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,644 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,665 [fs_likelihood.fslikelihood] Computed log-likelihood = -61.1255
 2023-07-02 10:33:21,665 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,665 [model] Posterior to be computed for parameters {'Omega_m': 0.28959677171580905, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,665 [prior] Evaluating prior at array([0.28959677, 0.55192213])
 2023-07-02 10:33:21,666 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,666 [model] Got input parameters: {'Omega_m': 0.28959677171580905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,666 [classy] Got parameters {'Omega_m': 0.28959677171580905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,666 [classy] Computing new state
 2023-07-02 10:33:21,666 [classy] Setting parameters: {'Omega_m': 0.28959677171580905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,710 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.10716351986733}
 2023-07-02 10:33:21,710 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,711 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0342498
 2023-07-02 10:33:21,711 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,712 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,731 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25342
 2023-07-02 10:33:21,732 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,732 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': -0.6875621864722891}
 2023-07-02 10:33:21,732 [prior] Evaluating prior at array([ 0.29273405, -0.68756219])
 2023-07-02 10:33:21,732 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:21,732 [model] Posterior to be computed for parameters {'Omega_m': 0.2990131287426906, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,732 [prior] Evaluating prior at array([0.29901313, 0.55192213])
 2023-07-02 10:33:21,732 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,732 [model] Got input parameters: {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,732 [classy] Got parameters {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,732 [classy] Computing new state
 2023-07-02 10:33:21,732 [classy] Setting parameters: {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,776 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91273867726886}
 2023-07-02 10:33:21,776 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,778 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117139
 2023-07-02 10:33:21,778 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,778 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,798 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0271319
 2023-07-02 10:33:21,798 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,798 [mcmc] New sample, #38:
   Omega_m:0.2927341, b1:0.5519221
 2023-07-02 10:33:21,798 [model] Posterior to be computed for parameters {'Omega_m': 0.2990131287426906, 'b1': 1.1270812526550702}
 2023-07-02 10:33:21,798 [prior] Evaluating prior at array([0.29901313, 1.12708125])
 2023-07-02 10:33:21,798 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,799 [model] Got input parameters: {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1270812526550702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,799 [classy] Got parameters {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,799 [classy] Re-using computed results
 2023-07-02 10:33:21,799 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91273867726886}
 2023-07-02 10:33:21,799 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,799 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1270812526550702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,799 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,819 [fs_likelihood.fslikelihood] Computed log-likelihood = -1622.56
 2023-07-02 10:33:21,820 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,820 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,820 [prior] Evaluating prior at array([0.30444692, 0.55192213])
 2023-07-02 10:33:21,820 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,820 [model] Got input parameters: {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,820 [classy] Got parameters {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,820 [classy] Computing new state
 2023-07-02 10:33:21,820 [classy] Setting parameters: {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2383900458081}
 2023-07-02 10:33:21,865 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00424409
 2023-07-02 10:33:21,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,866 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,886 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.646221
 2023-07-02 10:33:21,886 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,886 [mcmc] New sample, #39:
   Omega_m:0.2990131, b1:0.5519221
 2023-07-02 10:33:21,886 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': -0.011779091481928128}
 2023-07-02 10:33:21,886 [prior] Evaluating prior at array([ 0.30444692, -0.01177909])
 2023-07-02 10:33:21,887 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:21,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3108017352823357, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,887 [prior] Evaluating prior at array([0.31080174, 0.55192213])
 2023-07-02 10:33:21,887 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,887 [model] Got input parameters: {'Omega_m': 0.3108017352823357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,887 [classy] Got parameters {'Omega_m': 0.3108017352823357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,887 [classy] Computing new state
 2023-07-02 10:33:21,887 [classy] Setting parameters: {'Omega_m': 0.3108017352823357, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:21,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.46303721229393}
 2023-07-02 10:33:21,931 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:21,933 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000376649
 2023-07-02 10:33:21,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,933 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,953 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60197
 2023-07-02 10:33:21,953 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,953 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': 0.7332293952236701}
 2023-07-02 10:33:21,953 [prior] Evaluating prior at array([0.30444692, 0.7332294 ])
 2023-07-02 10:33:21,954 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,954 [model] Got input parameters: {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7332293952236701, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,954 [classy] Got parameters {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,954 [classy] Re-using computed results
 2023-07-02 10:33:21,954 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2383900458081}
 2023-07-02 10:33:21,954 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:21,954 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7332293952236701, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,954 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:21,974 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.472
 2023-07-02 10:33:21,974 [model] Computed derived parameters: {}
 2023-07-02 10:33:21,975 [model] Posterior to be computed for parameters {'Omega_m': 0.31362770677515484, 'b1': 0.5519221298133538}
 2023-07-02 10:33:21,975 [prior] Evaluating prior at array([0.31362771, 0.55192213])
 2023-07-02 10:33:21,975 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:21,975 [model] Got input parameters: {'Omega_m': 0.31362770677515484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:21,975 [classy] Got parameters {'Omega_m': 0.31362770677515484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:21,975 [classy] Computing new state
 2023-07-02 10:33:21,975 [classy] Setting parameters: {'Omega_m': 0.31362770677515484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12272193602996}
 2023-07-02 10:33:22,022 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000282393
 2023-07-02 10:33:22,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,024 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,045 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.89827
 2023-07-02 10:33:22,045 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,045 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': -0.6528175061689666}
 2023-07-02 10:33:22,045 [prior] Evaluating prior at array([ 0.30444692, -0.65281751])
 2023-07-02 10:33:22,045 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:22,045 [model] Posterior to be computed for parameters {'Omega_m': 0.30319807298190116, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,045 [prior] Evaluating prior at array([0.30319807, 0.55192213])
 2023-07-02 10:33:22,046 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,046 [model] Got input parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,046 [classy] Got parameters {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,046 [classy] Computing new state
 2023-07-02 10:33:22,046 [classy] Setting parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,090 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.39243020999936}
 2023-07-02 10:33:22,090 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,092 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00561464
 2023-07-02 10:33:22,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,092 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,112 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.418006
 2023-07-02 10:33:22,112 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,112 [mcmc] New sample, #40:
   Omega_m:0.3044469, b1:0.5519221
 2023-07-02 10:33:22,112 [model] Posterior to be computed for parameters {'Omega_m': 0.30319807298190116, 'b1': 0.8967733494569461}
 2023-07-02 10:33:22,112 [prior] Evaluating prior at array([0.30319807, 0.89677335])
 2023-07-02 10:33:22,112 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,112 [model] Got input parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8967733494569461, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,113 [classy] Got parameters {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,113 [classy] Re-using computed results
 2023-07-02 10:33:22,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.39243020999936}
 2023-07-02 10:33:22,113 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,113 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8967733494569461, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,113 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,135 [fs_likelihood.fslikelihood] Computed log-likelihood = -530.458
 2023-07-02 10:33:22,135 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,135 [model] Posterior to be computed for parameters {'Omega_m': 0.30984425966599016, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,135 [prior] Evaluating prior at array([0.30984426, 0.55192213])
 2023-07-02 10:33:22,135 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,135 [model] Got input parameters: {'Omega_m': 0.30984425966599016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,135 [classy] Got parameters {'Omega_m': 0.30984425966599016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,135 [classy] Computing new state
 2023-07-02 10:33:22,136 [classy] Setting parameters: {'Omega_m': 0.30984425966599016, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57896276336174}
 2023-07-02 10:33:22,180 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,182 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000632534
 2023-07-02 10:33:22,182 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,182 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,201 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.22233
 2023-07-02 10:33:22,201 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,202 [model] Posterior to be computed for parameters {'Omega_m': 0.30319807298190116, 'b1': 0.5903604714629186}
 2023-07-02 10:33:22,202 [prior] Evaluating prior at array([0.30319807, 0.59036047])
 2023-07-02 10:33:22,202 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,202 [model] Got input parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5903604714629186, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,202 [classy] Got parameters {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,202 [classy] Re-using computed results
 2023-07-02 10:33:22,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.39243020999936}
 2023-07-02 10:33:22,202 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5903604714629186, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,202 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,222 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.3314
 2023-07-02 10:33:22,222 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,222 [model] Posterior to be computed for parameters {'Omega_m': 0.3008435759414654, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,222 [prior] Evaluating prior at array([0.30084358, 0.55192213])
 2023-07-02 10:33:22,223 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,223 [model] Got input parameters: {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,223 [classy] Got parameters {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,223 [classy] Computing new state
 2023-07-02 10:33:22,223 [classy] Setting parameters: {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,267 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.68436678296703}
 2023-07-02 10:33:22,267 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,269 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00875779
 2023-07-02 10:33:22,269 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,269 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,289 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.127235
 2023-07-02 10:33:22,289 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,289 [mcmc] New sample, #41:
   Omega_m:0.3031981, b1:0.5519221
 2023-07-02 10:33:22,289 [model] Posterior to be computed for parameters {'Omega_m': 0.3008435759414654, 'b1': 0.8083227325463126}
 2023-07-02 10:33:22,289 [prior] Evaluating prior at array([0.30084358, 0.80832273])
 2023-07-02 10:33:22,289 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,290 [model] Got input parameters: {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8083227325463126, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,290 [classy] Got parameters {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,290 [classy] Re-using computed results
 2023-07-02 10:33:22,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.68436678296703}
 2023-07-02 10:33:22,290 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8083227325463126, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,290 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,309 [fs_likelihood.fslikelihood] Computed log-likelihood = -275.217
 2023-07-02 10:33:22,309 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,310 [model] Posterior to be computed for parameters {'Omega_m': 0.3062034503032166, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,310 [prior] Evaluating prior at array([0.30620345, 0.55192213])
 2023-07-02 10:33:22,310 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,310 [model] Got input parameters: {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,310 [classy] Got parameters {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,310 [classy] Computing new state
 2023-07-02 10:33:22,310 [classy] Setting parameters: {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.02266118955433}
 2023-07-02 10:33:22,354 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00265963
 2023-07-02 10:33:22,356 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,356 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,376 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.05401
 2023-07-02 10:33:22,376 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,376 [mcmc] New sample, #42:
   Omega_m:0.3008436, b1:0.5519221
 2023-07-02 10:33:22,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3062034503032166, 'b1': 0.37146299220949075}
 2023-07-02 10:33:22,377 [prior] Evaluating prior at array([0.30620345, 0.37146299])
 2023-07-02 10:33:22,377 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,377 [model] Got input parameters: {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37146299220949075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,377 [classy] Got parameters {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,377 [classy] Re-using computed results
 2023-07-02 10:33:22,377 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.02266118955433}
 2023-07-02 10:33:22,377 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,377 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37146299220949075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,377 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,397 [fs_likelihood.fslikelihood] Computed log-likelihood = -45.919
 2023-07-02 10:33:22,397 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,397 [model] Posterior to be computed for parameters {'Omega_m': 0.3016247485583303, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,397 [prior] Evaluating prior at array([0.30162475, 0.55192213])
 2023-07-02 10:33:22,397 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,397 [model] Got input parameters: {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,397 [classy] Got parameters {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,397 [classy] Computing new state
 2023-07-02 10:33:22,397 [classy] Setting parameters: {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.58728920924108}
 2023-07-02 10:33:22,442 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00763342
 2023-07-02 10:33:22,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,444 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.203499
 2023-07-02 10:33:22,464 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,464 [mcmc] New sample, #43:
   Omega_m:0.3062035, b1:0.5519221
 2023-07-02 10:33:22,464 [model] Posterior to be computed for parameters {'Omega_m': 0.3016247485583303, 'b1': 0.28441299083151156}
 2023-07-02 10:33:22,464 [prior] Evaluating prior at array([0.30162475, 0.28441299])
 2023-07-02 10:33:22,464 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,464 [model] Got input parameters: {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.28441299083151156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,464 [classy] Got parameters {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,464 [classy] Re-using computed results
 2023-07-02 10:33:22,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.58728920924108}
 2023-07-02 10:33:22,464 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,464 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.28441299083151156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,464 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,485 [fs_likelihood.fslikelihood] Computed log-likelihood = -117.93
 2023-07-02 10:33:22,485 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,485 [model] Posterior to be computed for parameters {'Omega_m': 0.2984268303190012, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,485 [prior] Evaluating prior at array([0.29842683, 0.55192213])
 2023-07-02 10:33:22,485 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,485 [model] Got input parameters: {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,485 [classy] Got parameters {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,485 [classy] Computing new state
 2023-07-02 10:33:22,485 [classy] Setting parameters: {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,530 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.98614873405336}
 2023-07-02 10:33:22,530 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,532 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0127568
 2023-07-02 10:33:22,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,532 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0183653
 2023-07-02 10:33:22,552 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,552 [mcmc] New sample, #44:
   Omega_m:0.3016247, b1:0.5519221
 2023-07-02 10:33:22,552 [model] Posterior to be computed for parameters {'Omega_m': 0.2984268303190012, 'b1': 0.7516198877223644}
 2023-07-02 10:33:22,552 [prior] Evaluating prior at array([0.29842683, 0.75161989])
 2023-07-02 10:33:22,552 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,552 [model] Got input parameters: {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7516198877223644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,552 [classy] Got parameters {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,552 [classy] Re-using computed results
 2023-07-02 10:33:22,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.98614873405336}
 2023-07-02 10:33:22,552 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,552 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7516198877223644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,552 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,573 [fs_likelihood.fslikelihood] Computed log-likelihood = -159.064
 2023-07-02 10:33:22,573 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,573 [model] Posterior to be computed for parameters {'Omega_m': 0.2953615175912442, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,573 [prior] Evaluating prior at array([0.29536152, 0.55192213])
 2023-07-02 10:33:22,573 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,573 [model] Got input parameters: {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,573 [classy] Got parameters {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,574 [classy] Computing new state
 2023-07-02 10:33:22,574 [classy] Setting parameters: {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3719982248647}
 2023-07-02 10:33:22,617 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,619 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0189764
 2023-07-02 10:33:22,619 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,619 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,639 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.156569
 2023-07-02 10:33:22,639 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,639 [mcmc] New sample, #45:
   Omega_m:0.2984268, b1:0.5519221
 2023-07-02 10:33:22,640 [model] Posterior to be computed for parameters {'Omega_m': 0.2953615175912442, 'b1': 0.30100388586694227}
 2023-07-02 10:33:22,640 [prior] Evaluating prior at array([0.29536152, 0.30100389])
 2023-07-02 10:33:22,640 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,640 [model] Got input parameters: {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.30100388586694227, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,640 [classy] Got parameters {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,640 [classy] Re-using computed results
 2023-07-02 10:33:22,640 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3719982248647}
 2023-07-02 10:33:22,640 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,640 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.30100388586694227, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,640 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,660 [fs_likelihood.fslikelihood] Computed log-likelihood = -114.012
 2023-07-02 10:33:22,660 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,660 [model] Posterior to be computed for parameters {'Omega_m': 0.2937591117363911, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,660 [prior] Evaluating prior at array([0.29375911, 0.55192213])
 2023-07-02 10:33:22,660 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,660 [model] Got input parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,660 [classy] Got parameters {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,660 [classy] Computing new state
 2023-07-02 10:33:22,660 [classy] Setting parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.57509318183054}
 2023-07-02 10:33:22,704 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0227478
 2023-07-02 10:33:22,706 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,706 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,727 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.351794
 2023-07-02 10:33:22,727 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,727 [mcmc] New sample, #46:
   Omega_m:0.2953615, b1:0.5519221
 2023-07-02 10:33:22,727 [model] Posterior to be computed for parameters {'Omega_m': 0.2937591117363911, 'b1': 0.7986274000650906}
 2023-07-02 10:33:22,727 [prior] Evaluating prior at array([0.29375911, 0.7986274 ])
 2023-07-02 10:33:22,727 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,727 [model] Got input parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7986274000650906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,727 [classy] Got parameters {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,727 [classy] Re-using computed results
 2023-07-02 10:33:22,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.57509318183054}
 2023-07-02 10:33:22,727 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7986274000650906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,728 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -227.504
 2023-07-02 10:33:22,747 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,748 [model] Posterior to be computed for parameters {'Omega_m': 0.30625764732277694, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,748 [prior] Evaluating prior at array([0.30625765, 0.55192213])
 2023-07-02 10:33:22,748 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,748 [model] Got input parameters: {'Omega_m': 0.30625764732277694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,748 [classy] Got parameters {'Omega_m': 0.30625764732277694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,748 [classy] Computing new state
 2023-07-02 10:33:22,748 [classy] Setting parameters: {'Omega_m': 0.30625764732277694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01602368688003}
 2023-07-02 10:33:22,792 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,794 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00261709
 2023-07-02 10:33:22,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,794 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,814 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.0682
 2023-07-02 10:33:22,814 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,814 [model] Posterior to be computed for parameters {'Omega_m': 0.2937591117363911, 'b1': 1.2593493996184808}
 2023-07-02 10:33:22,814 [prior] Evaluating prior at array([0.29375911, 1.2593494 ])
 2023-07-02 10:33:22,814 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,814 [model] Got input parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2593493996184808, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,814 [classy] Got parameters {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,814 [classy] Re-using computed results
 2023-07-02 10:33:22,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.57509318183054}
 2023-07-02 10:33:22,814 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,814 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2593493996184808, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,814 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,835 [fs_likelihood.fslikelihood] Computed log-likelihood = -2579.76
 2023-07-02 10:33:22,835 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,835 [model] Posterior to be computed for parameters {'Omega_m': 0.29930387447375584, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,835 [prior] Evaluating prior at array([0.29930387, 0.55192213])
 2023-07-02 10:33:22,835 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,835 [model] Got input parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,836 [classy] Got parameters {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,836 [classy] Computing new state
 2023-07-02 10:33:22,836 [classy] Setting parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8763825622771}
 2023-07-02 10:33:22,880 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,882 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0112142
 2023-07-02 10:33:22,882 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,882 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,902 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0356719
 2023-07-02 10:33:22,902 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,902 [mcmc] New sample, #47:
   Omega_m:0.2937591, b1:0.5519221
 2023-07-02 10:33:22,902 [model] Posterior to be computed for parameters {'Omega_m': 0.29930387447375584, 'b1': 0.9170176868694204}
 2023-07-02 10:33:22,902 [prior] Evaluating prior at array([0.29930387, 0.91701769])
 2023-07-02 10:33:22,902 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,902 [model] Got input parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9170176868694204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,902 [classy] Got parameters {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,902 [classy] Re-using computed results
 2023-07-02 10:33:22,902 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8763825622771}
 2023-07-02 10:33:22,902 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,902 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9170176868694204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,902 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,922 [fs_likelihood.fslikelihood] Computed log-likelihood = -572.844
 2023-07-02 10:33:22,923 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,923 [model] Posterior to be computed for parameters {'Omega_m': 0.28473125848640607, 'b1': 0.5519221298133538}
 2023-07-02 10:33:22,923 [prior] Evaluating prior at array([0.28473126, 0.55192213])
 2023-07-02 10:33:22,923 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,923 [model] Got input parameters: {'Omega_m': 0.28473125848640607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,923 [classy] Got parameters {'Omega_m': 0.28473125848640607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,923 [classy] Computing new state
 2023-07-02 10:33:22,923 [classy] Setting parameters: {'Omega_m': 0.28473125848640607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:22,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.7375834964338}
 2023-07-02 10:33:22,967 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:22,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0509052
 2023-07-02 10:33:22,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,969 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:22,989 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.02957
 2023-07-02 10:33:22,990 [model] Computed derived parameters: {}
 2023-07-02 10:33:22,990 [model] Posterior to be computed for parameters {'Omega_m': 0.29930387447375584, 'b1': 0.24355068844719835}
 2023-07-02 10:33:22,990 [prior] Evaluating prior at array([0.29930387, 0.24355069])
 2023-07-02 10:33:22,990 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:22,990 [model] Got input parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24355068844719835, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,990 [classy] Got parameters {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:22,990 [classy] Re-using computed results
 2023-07-02 10:33:22,990 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8763825622771}
 2023-07-02 10:33:22,990 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:22,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24355068844719835, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:22,990 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,010 [fs_likelihood.fslikelihood] Computed log-likelihood = -159.164
 2023-07-02 10:33:23,010 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,010 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.5519221298133538}
 2023-07-02 10:33:23,010 [prior] Evaluating prior at array([0.29991512, 0.55192213])
 2023-07-02 10:33:23,010 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,011 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,011 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,011 [classy] Computing new state
 2023-07-02 10:33:23,011 [classy] Setting parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
 2023-07-02 10:33:23,055 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0102007
 2023-07-02 10:33:23,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,057 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,078 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0626909
 2023-07-02 10:33:23,078 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,078 [mcmc] New sample, #48:
   Omega_m:0.2993039, b1:0.5519221
 2023-07-02 10:33:23,078 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,078 [prior] Evaluating prior at array([0.29991512, 0.51952372])
 2023-07-02 10:33:23,078 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,078 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,078 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,078 [classy] Re-using computed results
 2023-07-02 10:33:23,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
 2023-07-02 10:33:23,078 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:23,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,079 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,099 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34977
 2023-07-02 10:33:23,099 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,099 [mcmc] New sample, #49:
   Omega_m:0.2999151, b1:0.5519221
 2023-07-02 10:33:23,099 [model] Posterior to be computed for parameters {'Omega_m': 0.2983288116046203, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,099 [prior] Evaluating prior at array([0.29832881, 0.51952372])
 2023-07-02 10:33:23,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,099 [model] Got input parameters: {'Omega_m': 0.2983288116046203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,099 [classy] Got parameters {'Omega_m': 0.2983288116046203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,099 [classy] Computing new state
 2023-07-02 10:33:23,099 [classy] Setting parameters: {'Omega_m': 0.2983288116046203, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9984324763864}
 2023-07-02 10:33:23,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129356
 2023-07-02 10:33:23,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,149 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.887817
 2023-07-02 10:33:23,169 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,169 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 2.5359948169443425}
 2023-07-02 10:33:23,169 [prior] Evaluating prior at array([0.29991512, 2.53599482])
 2023-07-02 10:33:23,169 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,169 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.5359948169443425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,169 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,169 [classy] Re-using computed results
 2023-07-02 10:33:23,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
 2023-07-02 10:33:23,169 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:23,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.5359948169443425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,169 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,190 [fs_likelihood.fslikelihood] Computed log-likelihood = -46582.6
 2023-07-02 10:33:23,190 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,190 [model] Posterior to be computed for parameters {'Omega_m': 0.29122073856488007, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,190 [prior] Evaluating prior at array([0.29122074, 0.51952372])
 2023-07-02 10:33:23,191 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,191 [model] Got input parameters: {'Omega_m': 0.29122073856488007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,191 [classy] Got parameters {'Omega_m': 0.29122073856488007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,191 [classy] Computing new state
 2023-07-02 10:33:23,191 [classy] Setting parameters: {'Omega_m': 0.29122073856488007, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.89879054259472}
 2023-07-02 10:33:23,235 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0294661
 2023-07-02 10:33:23,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,237 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.12253
 2023-07-02 10:33:23,257 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,258 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.6747633984717009}
 2023-07-02 10:33:23,258 [prior] Evaluating prior at array([0.29991512, 0.6747634 ])
 2023-07-02 10:33:23,258 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,258 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6747633984717009, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,258 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,258 [classy] Re-using computed results
 2023-07-02 10:33:23,258 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
 2023-07-02 10:33:23,258 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:23,258 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6747633984717009, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,258 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,280 [fs_likelihood.fslikelihood] Computed log-likelihood = -64.6719
 2023-07-02 10:33:23,280 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,280 [model] Posterior to be computed for parameters {'Omega_m': 0.3208603102566019, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,280 [prior] Evaluating prior at array([0.32086031, 0.51952372])
 2023-07-02 10:33:23,281 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,281 [model] Got input parameters: {'Omega_m': 0.3208603102566019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,281 [classy] Got parameters {'Omega_m': 0.3208603102566019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,281 [classy] Computing new state
 2023-07-02 10:33:23,281 [classy] Setting parameters: {'Omega_m': 0.3208603102566019, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26407152024586}
 2023-07-02 10:33:23,324 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00441643
 2023-07-02 10:33:23,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,326 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,347 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.268184
 2023-07-02 10:33:23,347 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,347 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': -0.49282733057451356}
 2023-07-02 10:33:23,347 [prior] Evaluating prior at array([ 0.29991512, -0.49282733])
 2023-07-02 10:33:23,347 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:23,347 [model] Posterior to be computed for parameters {'Omega_m': 0.27955271649559543, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,347 [prior] Evaluating prior at array([0.27955272, 0.51952372])
 2023-07-02 10:33:23,348 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,348 [model] Got input parameters: {'Omega_m': 0.27955271649559543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,348 [classy] Got parameters {'Omega_m': 0.27955271649559543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,348 [classy] Computing new state
 2023-07-02 10:33:23,348 [classy] Setting parameters: {'Omega_m': 0.27955271649559543, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.41887798832215}
 2023-07-02 10:33:23,393 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,394 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0725779
 2023-07-02 10:33:23,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,395 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,415 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.3977
 2023-07-02 10:33:23,415 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,415 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.15788407551432493}
 2023-07-02 10:33:23,415 [prior] Evaluating prior at array([0.29991512, 0.15788408])
 2023-07-02 10:33:23,415 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,415 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15788407551432493, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,415 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,415 [classy] Re-using computed results
 2023-07-02 10:33:23,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
 2023-07-02 10:33:23,415 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:23,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15788407551432493, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,415 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,436 [fs_likelihood.fslikelihood] Computed log-likelihood = -244.69
 2023-07-02 10:33:23,436 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,436 [model] Posterior to be computed for parameters {'Omega_m': 0.2993546308450781, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,436 [prior] Evaluating prior at array([0.29935463, 0.51952372])
 2023-07-02 10:33:23,436 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,436 [model] Got input parameters: {'Omega_m': 0.2993546308450781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,436 [classy] Got parameters {'Omega_m': 0.2993546308450781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,436 [classy] Computing new state
 2023-07-02 10:33:23,437 [classy] Setting parameters: {'Omega_m': 0.2993546308450781, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.87003925218033}
 2023-07-02 10:33:23,484 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,486 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111281
 2023-07-02 10:33:23,486 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,486 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,506 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.1953
 2023-07-02 10:33:23,506 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,506 [mcmc] New sample, #50:
   Omega_m:0.2999151, b1:0.5195237
 2023-07-02 10:33:23,506 [model] Posterior to be computed for parameters {'Omega_m': 0.2993546308450781, 'b1': -0.23787480739684774}
 2023-07-02 10:33:23,506 [prior] Evaluating prior at array([ 0.29935463, -0.23787481])
 2023-07-02 10:33:23,507 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:23,507 [model] Posterior to be computed for parameters {'Omega_m': 0.3014410956438017, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,507 [prior] Evaluating prior at array([0.3014411 , 0.51952372])
 2023-07-02 10:33:23,507 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,507 [model] Got input parameters: {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,507 [classy] Got parameters {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,507 [classy] Computing new state
 2023-07-02 10:33:23,507 [classy] Setting parameters: {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6100921172112}
 2023-07-02 10:33:23,552 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,554 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00789044
 2023-07-02 10:33:23,554 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,554 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,573 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72189
 2023-07-02 10:33:23,574 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,574 [mcmc] New sample, #51:
   Omega_m:0.2993546, b1:0.5195237
 2023-07-02 10:33:23,574 [model] Posterior to be computed for parameters {'Omega_m': 0.3014410956438017, 'b1': 0.18239292219831027}
 2023-07-02 10:33:23,574 [prior] Evaluating prior at array([0.3014411 , 0.18239292])
 2023-07-02 10:33:23,574 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,574 [model] Got input parameters: {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.18239292219831027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,574 [classy] Got parameters {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,574 [classy] Re-using computed results
 2023-07-02 10:33:23,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6100921172112}
 2023-07-02 10:33:23,574 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:23,574 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.18239292219831027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,574 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,595 [fs_likelihood.fslikelihood] Computed log-likelihood = -216.179
 2023-07-02 10:33:23,595 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,595 [model] Posterior to be computed for parameters {'Omega_m': 0.3093467198361541, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,595 [prior] Evaluating prior at array([0.30934672, 0.51952372])
 2023-07-02 10:33:23,595 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,595 [model] Got input parameters: {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,595 [classy] Got parameters {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,595 [classy] Computing new state
 2023-07-02 10:33:23,595 [classy] Setting parameters: {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,641 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63932481434654}
 2023-07-02 10:33:23,641 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,642 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000810724
 2023-07-02 10:33:23,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,643 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,663 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51512
 2023-07-02 10:33:23,663 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,663 [mcmc] New sample, #52:
   Omega_m:0.3014411, b1:0.5195237
 2023-07-02 10:33:23,663 [model] Posterior to be computed for parameters {'Omega_m': 0.3093467198361541, 'b1': 0.9065273821202704}
 2023-07-02 10:33:23,663 [prior] Evaluating prior at array([0.30934672, 0.90652738])
 2023-07-02 10:33:23,663 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,663 [model] Got input parameters: {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9065273821202704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,663 [classy] Got parameters {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,663 [classy] Re-using computed results
 2023-07-02 10:33:23,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63932481434654}
 2023-07-02 10:33:23,663 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:23,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9065273821202704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,663 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -606.71
 2023-07-02 10:33:23,684 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,684 [model] Posterior to be computed for parameters {'Omega_m': 0.324511395815196, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,684 [prior] Evaluating prior at array([0.3245114 , 0.51952372])
 2023-07-02 10:33:23,684 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,684 [model] Got input parameters: {'Omega_m': 0.324511395815196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,684 [classy] Got parameters {'Omega_m': 0.324511395815196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,684 [classy] Computing new state
 2023-07-02 10:33:23,684 [classy] Setting parameters: {'Omega_m': 0.324511395815196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,728 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.83715652306358}
 2023-07-02 10:33:23,728 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,730 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00881386
 2023-07-02 10:33:23,730 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,730 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,751 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.28685
 2023-07-02 10:33:23,751 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,751 [model] Posterior to be computed for parameters {'Omega_m': 0.3093467198361541, 'b1': -0.1496384743576149}
 2023-07-02 10:33:23,751 [prior] Evaluating prior at array([ 0.30934672, -0.14963847])
 2023-07-02 10:33:23,751 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:23,751 [model] Posterior to be computed for parameters {'Omega_m': 0.2995984350540414, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,751 [prior] Evaluating prior at array([0.29959844, 0.51952372])
 2023-07-02 10:33:23,751 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,751 [model] Got input parameters: {'Omega_m': 0.2995984350540414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,751 [classy] Got parameters {'Omega_m': 0.2995984350540414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,751 [classy] Computing new state
 2023-07-02 10:33:23,751 [classy] Setting parameters: {'Omega_m': 0.2995984350540414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.83958023290648}
 2023-07-02 10:33:23,796 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0107195
 2023-07-02 10:33:23,798 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,798 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,817 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.26367
 2023-07-02 10:33:23,817 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,818 [mcmc] New sample, #53:
   Omega_m:0.3093467, b1:0.5195237
 2023-07-02 10:33:23,818 [model] Posterior to be computed for parameters {'Omega_m': 0.2995984350540414, 'b1': -0.739436344928673}
 2023-07-02 10:33:23,818 [prior] Evaluating prior at array([ 0.29959844, -0.73943634])
 2023-07-02 10:33:23,818 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:23,818 [model] Posterior to be computed for parameters {'Omega_m': 0.2911141695421805, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,818 [prior] Evaluating prior at array([0.29111417, 0.51952372])
 2023-07-02 10:33:23,818 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,818 [model] Got input parameters: {'Omega_m': 0.2911141695421805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,818 [classy] Got parameters {'Omega_m': 0.2911141695421805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,818 [classy] Computing new state
 2023-07-02 10:33:23,818 [classy] Setting parameters: {'Omega_m': 0.2911141695421805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.91243394628125}
 2023-07-02 10:33:23,862 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0297683
 2023-07-02 10:33:23,864 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,864 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,884 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.17936
 2023-07-02 10:33:23,885 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,885 [model] Posterior to be computed for parameters {'Omega_m': 0.2995984350540414, 'b1': -0.20179891593627486}
 2023-07-02 10:33:23,885 [prior] Evaluating prior at array([ 0.29959844, -0.20179892])
 2023-07-02 10:33:23,885 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:23,885 [model] Posterior to be computed for parameters {'Omega_m': 0.3025261049903241, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,885 [prior] Evaluating prior at array([0.3025261 , 0.51952372])
 2023-07-02 10:33:23,885 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,885 [model] Got input parameters: {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,885 [classy] Got parameters {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,885 [classy] Computing new state
 2023-07-02 10:33:23,885 [classy] Setting parameters: {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.47554719676702}
 2023-07-02 10:33:23,929 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00643685
 2023-07-02 10:33:23,931 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,931 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:23,951 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94336
 2023-07-02 10:33:23,952 [model] Computed derived parameters: {}
 2023-07-02 10:33:23,952 [mcmc] New sample, #54:
   Omega_m:0.2995984, b1:0.5195237
 2023-07-02 10:33:23,952 [model] Posterior to be computed for parameters {'Omega_m': 0.3025261049903241, 'b1': -0.7969473131310648}
 2023-07-02 10:33:23,952 [prior] Evaluating prior at array([ 0.3025261 , -0.79694731])
 2023-07-02 10:33:23,952 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:23,952 [model] Posterior to be computed for parameters {'Omega_m': 0.3318560344270412, 'b1': 0.5195237182842224}
 2023-07-02 10:33:23,952 [prior] Evaluating prior at array([0.33185603, 0.51952372])
 2023-07-02 10:33:23,952 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:23,952 [model] Got input parameters: {'Omega_m': 0.3318560344270412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,952 [classy] Got parameters {'Omega_m': 0.3318560344270412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:23,952 [classy] Computing new state
 2023-07-02 10:33:23,952 [classy] Setting parameters: {'Omega_m': 0.3318560344270412, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:23,997 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99126308332833}
 2023-07-02 10:33:23,997 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:23,999 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221508
 2023-07-02 10:33:23,999 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:23,999 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,019 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.64387
 2023-07-02 10:33:24,019 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,019 [model] Posterior to be computed for parameters {'Omega_m': 0.3025261049903241, 'b1': 0.29461570873738535}
 2023-07-02 10:33:24,019 [prior] Evaluating prior at array([0.3025261 , 0.29461571])
 2023-07-02 10:33:24,020 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,020 [model] Got input parameters: {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.29461570873738535, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,020 [classy] Got parameters {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,020 [classy] Re-using computed results
 2023-07-02 10:33:24,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.47554719676702}
 2023-07-02 10:33:24,020 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.29461570873738535, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,020 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,040 [fs_likelihood.fslikelihood] Computed log-likelihood = -107.743
 2023-07-02 10:33:24,040 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,040 [model] Posterior to be computed for parameters {'Omega_m': 0.3000975386302018, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,040 [prior] Evaluating prior at array([0.30009754, 0.51952372])
 2023-07-02 10:33:24,040 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,040 [model] Got input parameters: {'Omega_m': 0.3000975386302018, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,040 [classy] Got parameters {'Omega_m': 0.3000975386302018, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,040 [classy] Computing new state
 2023-07-02 10:33:24,040 [classy] Setting parameters: {'Omega_m': 0.3000975386302018, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,084 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7772941201249}
 2023-07-02 10:33:24,084 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,086 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00990805
 2023-07-02 10:33:24,086 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,086 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,106 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39798
 2023-07-02 10:33:24,107 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,107 [mcmc] New sample, #55:
   Omega_m:0.3025261, b1:0.5195237
 2023-07-02 10:33:24,107 [model] Posterior to be computed for parameters {'Omega_m': 0.3000975386302018, 'b1': -0.05134008881847618}
 2023-07-02 10:33:24,107 [prior] Evaluating prior at array([ 0.30009754, -0.05134009])
 2023-07-02 10:33:24,107 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:24,107 [model] Posterior to be computed for parameters {'Omega_m': 0.3138328208814638, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,107 [prior] Evaluating prior at array([0.31383282, 0.51952372])
 2023-07-02 10:33:24,107 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,107 [model] Got input parameters: {'Omega_m': 0.3138328208814638, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,107 [classy] Got parameters {'Omega_m': 0.3138328208814638, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,107 [classy] Computing new state
 2023-07-02 10:33:24,107 [classy] Setting parameters: {'Omega_m': 0.3138328208814638, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.09812802479559}
 2023-07-02 10:33:24,154 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,156 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000313603
 2023-07-02 10:33:24,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,156 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,176 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11935
 2023-07-02 10:33:24,176 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,176 [mcmc] New sample, #56:
   Omega_m:0.3000975, b1:0.5195237
 2023-07-02 10:33:24,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3138328208814638, 'b1': -1.168791499354323}
 2023-07-02 10:33:24,176 [prior] Evaluating prior at array([ 0.31383282, -1.1687915 ])
 2023-07-02 10:33:24,176 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:24,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,176 [prior] Evaluating prior at array([0.31035703, 0.51952372])
 2023-07-02 10:33:24,176 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,176 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,176 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,176 [classy] Computing new state
 2023-07-02 10:33:24,176 [classy] Setting parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
 2023-07-02 10:33:24,220 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000481284
 2023-07-02 10:33:24,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,222 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47942
 2023-07-02 10:33:24,243 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,243 [mcmc] New sample, #57:
   Omega_m:0.3138328, b1:0.5195237
 2023-07-02 10:33:24,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.18046939925790145}
 2023-07-02 10:33:24,243 [prior] Evaluating prior at array([0.31035703, 0.1804694 ])
 2023-07-02 10:33:24,243 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,243 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.18046939925790145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,243 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,243 [classy] Re-using computed results
 2023-07-02 10:33:24,243 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
 2023-07-02 10:33:24,243 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,243 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.18046939925790145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,243 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,263 [fs_likelihood.fslikelihood] Computed log-likelihood = -202.222
 2023-07-02 10:33:24,263 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,264 [model] Posterior to be computed for parameters {'Omega_m': 0.29423264591678533, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,264 [prior] Evaluating prior at array([0.29423265, 0.51952372])
 2023-07-02 10:33:24,264 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,264 [model] Got input parameters: {'Omega_m': 0.29423264591678533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,264 [classy] Got parameters {'Omega_m': 0.29423264591678533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,264 [classy] Computing new state
 2023-07-02 10:33:24,264 [classy] Setting parameters: {'Omega_m': 0.29423264591678533, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,308 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.51497698761037}
 2023-07-02 10:33:24,308 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,310 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0215958
 2023-07-02 10:33:24,310 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,310 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,330 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.659223
 2023-07-02 10:33:24,330 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,330 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.4499952051144753}
 2023-07-02 10:33:24,330 [prior] Evaluating prior at array([0.31035703, 0.44999521])
 2023-07-02 10:33:24,330 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,330 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4499952051144753, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,330 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,330 [classy] Re-using computed results
 2023-07-02 10:33:24,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
 2023-07-02 10:33:24,330 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4499952051144753, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,330 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,351 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.94713
 2023-07-02 10:33:24,351 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,351 [model] Posterior to be computed for parameters {'Omega_m': 0.3195468611781863, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,351 [prior] Evaluating prior at array([0.31954686, 0.51952372])
 2023-07-02 10:33:24,351 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,351 [model] Got input parameters: {'Omega_m': 0.3195468611781863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,351 [classy] Got parameters {'Omega_m': 0.3195468611781863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,351 [classy] Computing new state
 2023-07-02 10:33:24,351 [classy] Setting parameters: {'Omega_m': 0.3195468611781863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4187117702353}
 2023-07-02 10:33:24,395 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,397 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00320815
 2023-07-02 10:33:24,397 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,397 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,417 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.728372
 2023-07-02 10:33:24,417 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,417 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.46083567127657843}
 2023-07-02 10:33:24,417 [prior] Evaluating prior at array([0.31035703, 0.46083567])
 2023-07-02 10:33:24,418 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,418 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46083567127657843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,418 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,418 [classy] Re-using computed results
 2023-07-02 10:33:24,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
 2023-07-02 10:33:24,418 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46083567127657843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,418 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.08539
 2023-07-02 10:33:24,438 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,438 [model] Posterior to be computed for parameters {'Omega_m': 0.3301718701829529, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,438 [prior] Evaluating prior at array([0.33017187, 0.51952372])
 2023-07-02 10:33:24,438 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,438 [model] Got input parameters: {'Omega_m': 0.3301718701829529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,438 [classy] Got parameters {'Omega_m': 0.3301718701829529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,438 [classy] Computing new state
 2023-07-02 10:33:24,438 [classy] Setting parameters: {'Omega_m': 0.3301718701829529, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,482 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1837132550769}
 2023-07-02 10:33:24,482 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,484 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185751
 2023-07-02 10:33:24,484 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,484 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,505 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.49972
 2023-07-02 10:33:24,505 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,505 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.017222164919888927}
 2023-07-02 10:33:24,505 [prior] Evaluating prior at array([0.31035703, 0.01722216])
 2023-07-02 10:33:24,505 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,505 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.017222164919888927, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,505 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,505 [classy] Re-using computed results
 2023-07-02 10:33:24,505 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
 2023-07-02 10:33:24,505 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,505 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.017222164919888927, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,505 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,526 [fs_likelihood.fslikelihood] Computed log-likelihood = -380.86
 2023-07-02 10:33:24,526 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,526 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,526 [prior] Evaluating prior at array([0.31830587, 0.51952372])
 2023-07-02 10:33:24,526 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,526 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,526 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,526 [classy] Computing new state
 2023-07-02 10:33:24,526 [classy] Setting parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
 2023-07-02 10:33:24,570 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,572 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00225092
 2023-07-02 10:33:24,572 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,572 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,592 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.11494
 2023-07-02 10:33:24,592 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,592 [mcmc] New sample, #58:
   Omega_m:0.310357, b1:0.5195237
 2023-07-02 10:33:24,592 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 1.0575120862193421}
 2023-07-02 10:33:24,592 [prior] Evaluating prior at array([0.31830587, 1.05751209])
 2023-07-02 10:33:24,592 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,592 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0575120862193421, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,592 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,592 [classy] Re-using computed results
 2023-07-02 10:33:24,592 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
 2023-07-02 10:33:24,592 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0575120862193421, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,592 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,613 [fs_likelihood.fslikelihood] Computed log-likelihood = -1436.91
 2023-07-02 10:33:24,613 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,613 [model] Posterior to be computed for parameters {'Omega_m': 0.3231966957321344, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,613 [prior] Evaluating prior at array([0.3231967 , 0.51952372])
 2023-07-02 10:33:24,613 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,613 [model] Got input parameters: {'Omega_m': 0.3231966957321344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,613 [classy] Got parameters {'Omega_m': 0.3231966957321344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,613 [classy] Computing new state
 2023-07-02 10:33:24,613 [classy] Setting parameters: {'Omega_m': 0.3231966957321344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,657 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99038509512}
 2023-07-02 10:33:24,657 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,659 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00705596
 2023-07-02 10:33:24,659 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,659 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,679 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.680164
 2023-07-02 10:33:24,679 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,679 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 1.7504185492310702}
 2023-07-02 10:33:24,679 [prior] Evaluating prior at array([0.31830587, 1.75041855])
 2023-07-02 10:33:24,679 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,679 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7504185492310702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,679 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,679 [classy] Re-using computed results
 2023-07-02 10:33:24,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
 2023-07-02 10:33:24,679 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,679 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7504185492310702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,679 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,699 [fs_likelihood.fslikelihood] Computed log-likelihood = -12038.2
 2023-07-02 10:33:24,699 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,700 [model] Posterior to be computed for parameters {'Omega_m': 0.32767226246062503, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,700 [prior] Evaluating prior at array([0.32767226, 0.51952372])
 2023-07-02 10:33:24,700 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,700 [model] Got input parameters: {'Omega_m': 0.32767226246062503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,700 [classy] Got parameters {'Omega_m': 0.32767226246062503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,700 [classy] Computing new state
 2023-07-02 10:33:24,700 [classy] Setting parameters: {'Omega_m': 0.32767226246062503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4710135077093}
 2023-07-02 10:33:24,743 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0138308
 2023-07-02 10:33:24,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,745 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,766 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.96072
 2023-07-02 10:33:24,766 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,766 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 2.9027508328963614}
 2023-07-02 10:33:24,766 [prior] Evaluating prior at array([0.31830587, 2.90275083])
 2023-07-02 10:33:24,766 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,766 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.9027508328963614, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,766 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,766 [classy] Re-using computed results
 2023-07-02 10:33:24,766 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
 2023-07-02 10:33:24,766 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.9027508328963614, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -85915.6
 2023-07-02 10:33:24,786 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,786 [model] Posterior to be computed for parameters {'Omega_m': 0.2673348157751925, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,786 [prior] Evaluating prior at array([0.26733482, 0.51952372])
 2023-07-02 10:33:24,786 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,786 [model] Got input parameters: {'Omega_m': 0.2673348157751925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,786 [classy] Got parameters {'Omega_m': 0.2673348157751925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,786 [classy] Computing new state
 2023-07-02 10:33:24,786 [classy] Setting parameters: {'Omega_m': 0.2673348157751925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,830 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.06998584706656}
 2023-07-02 10:33:24,830 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140793
 2023-07-02 10:33:24,832 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,832 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,852 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.5036
 2023-07-02 10:33:24,852 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,852 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 0.8196620529927041}
 2023-07-02 10:33:24,852 [prior] Evaluating prior at array([0.31830587, 0.81966205])
 2023-07-02 10:33:24,853 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,853 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8196620529927041, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,853 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,853 [classy] Re-using computed results
 2023-07-02 10:33:24,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
 2023-07-02 10:33:24,853 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,853 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8196620529927041, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,853 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,873 [fs_likelihood.fslikelihood] Computed log-likelihood = -387.683
 2023-07-02 10:33:24,873 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,873 [model] Posterior to be computed for parameters {'Omega_m': 0.31423781033551457, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,873 [prior] Evaluating prior at array([0.31423781, 0.51952372])
 2023-07-02 10:33:24,873 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,873 [model] Got input parameters: {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,873 [classy] Got parameters {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,873 [classy] Computing new state
 2023-07-02 10:33:24,873 [classy] Setting parameters: {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:24,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04960475911685}
 2023-07-02 10:33:24,917 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:24,919 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000390255
 2023-07-02 10:33:24,919 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,919 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,939 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05348
 2023-07-02 10:33:24,939 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,939 [mcmc] New sample, #59:
   Omega_m:0.3183059, b1:0.5195237
 2023-07-02 10:33:24,939 [model] Posterior to be computed for parameters {'Omega_m': 0.31423781033551457, 'b1': 0.8253143886442103}
 2023-07-02 10:33:24,939 [prior] Evaluating prior at array([0.31423781, 0.82531439])
 2023-07-02 10:33:24,939 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,939 [model] Got input parameters: {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8253143886442103, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,939 [classy] Got parameters {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,939 [classy] Re-using computed results
 2023-07-02 10:33:24,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04960475911685}
 2023-07-02 10:33:24,939 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:24,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8253143886442103, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,939 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:24,959 [fs_likelihood.fslikelihood] Computed log-likelihood = -381.066
 2023-07-02 10:33:24,959 [model] Computed derived parameters: {}
 2023-07-02 10:33:24,960 [model] Posterior to be computed for parameters {'Omega_m': 0.3051693498916591, 'b1': 0.5195237182842224}
 2023-07-02 10:33:24,960 [prior] Evaluating prior at array([0.30516935, 0.51952372])
 2023-07-02 10:33:24,960 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:24,960 [model] Got input parameters: {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:24,960 [classy] Got parameters {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:24,960 [classy] Computing new state
 2023-07-02 10:33:24,960 [classy] Setting parameters: {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14953217415507}
 2023-07-02 10:33:25,004 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00354408
 2023-07-02 10:33:25,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,006 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33296
 2023-07-02 10:33:25,026 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,026 [mcmc] New sample, #60:
   Omega_m:0.3142378, b1:0.5195237
 2023-07-02 10:33:25,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3051693498916591, 'b1': 2.905029832805368}
 2023-07-02 10:33:25,026 [prior] Evaluating prior at array([0.30516935, 2.90502983])
 2023-07-02 10:33:25,027 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,027 [model] Got input parameters: {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.905029832805368, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,027 [classy] Got parameters {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,027 [classy] Re-using computed results
 2023-07-02 10:33:25,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14953217415507}
 2023-07-02 10:33:25,027 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.905029832805368, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,027 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -80952.8
 2023-07-02 10:33:25,046 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,046 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,047 [prior] Evaluating prior at array([0.30796169, 0.51952372])
 2023-07-02 10:33:25,047 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,047 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,047 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,047 [classy] Computing new state
 2023-07-02 10:33:25,047 [classy] Setting parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,091 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,091 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,092 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00147081
 2023-07-02 10:33:25,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,092 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,113 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51357
 2023-07-02 10:33:25,113 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,113 [mcmc] New sample, #61:
   Omega_m:0.3051693, b1:0.5195237
 2023-07-02 10:33:25,113 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.6321737352190662}
 2023-07-02 10:33:25,113 [prior] Evaluating prior at array([0.30796169, 0.63217374])
 2023-07-02 10:33:25,113 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,113 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6321737352190662, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,113 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,113 [classy] Re-using computed results
 2023-07-02 10:33:25,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,113 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,113 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6321737352190662, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,113 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,136 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.0195
 2023-07-02 10:33:25,136 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,136 [model] Posterior to be computed for parameters {'Omega_m': 0.3361635290202818, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,136 [prior] Evaluating prior at array([0.33616353, 0.51952372])
 2023-07-02 10:33:25,136 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,136 [model] Got input parameters: {'Omega_m': 0.3361635290202818, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,136 [classy] Got parameters {'Omega_m': 0.3361635290202818, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,136 [classy] Computing new state
 2023-07-02 10:33:25,136 [classy] Setting parameters: {'Omega_m': 0.3361635290202818, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.50301713651234}
 2023-07-02 10:33:25,181 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,183 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0326601
 2023-07-02 10:33:25,183 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,183 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,203 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.96293
 2023-07-02 10:33:25,203 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,203 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.23344409875363226}
 2023-07-02 10:33:25,203 [prior] Evaluating prior at array([0.30796169, 0.2334441 ])
 2023-07-02 10:33:25,203 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,203 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.23344409875363226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,203 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,203 [classy] Re-using computed results
 2023-07-02 10:33:25,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,203 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.23344409875363226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,203 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,223 [fs_likelihood.fslikelihood] Computed log-likelihood = -153.895
 2023-07-02 10:33:25,223 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,224 [model] Posterior to be computed for parameters {'Omega_m': 0.3328194360825727, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,224 [prior] Evaluating prior at array([0.33281944, 0.51952372])
 2023-07-02 10:33:25,224 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,224 [model] Got input parameters: {'Omega_m': 0.3328194360825727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,224 [classy] Got parameters {'Omega_m': 0.3328194360825727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,224 [classy] Computing new state
 2023-07-02 10:33:25,224 [classy] Setting parameters: {'Omega_m': 0.3328194360825727, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.88157058211928}
 2023-07-02 10:33:25,268 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,269 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.024332
 2023-07-02 10:33:25,269 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,269 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,290 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.33718
 2023-07-02 10:33:25,290 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,290 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 1.2195424712990772}
 2023-07-02 10:33:25,290 [prior] Evaluating prior at array([0.30796169, 1.21954247])
 2023-07-02 10:33:25,290 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,290 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2195424712990772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,290 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,290 [classy] Re-using computed results
 2023-07-02 10:33:25,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,290 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2195424712990772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,290 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,310 [fs_likelihood.fslikelihood] Computed log-likelihood = -2505.91
 2023-07-02 10:33:25,310 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,311 [model] Posterior to be computed for parameters {'Omega_m': 0.33238393811256584, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,311 [prior] Evaluating prior at array([0.33238394, 0.51952372])
 2023-07-02 10:33:25,311 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,311 [model] Got input parameters: {'Omega_m': 0.33238393811256584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,311 [classy] Got parameters {'Omega_m': 0.33238393811256584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,311 [classy] Computing new state
 2023-07-02 10:33:25,311 [classy] Setting parameters: {'Omega_m': 0.33238393811256584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.931122209442}
 2023-07-02 10:33:25,355 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0233338
 2023-07-02 10:33:25,356 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,356 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,376 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.02028
 2023-07-02 10:33:25,377 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': -0.10194500079011903}
 2023-07-02 10:33:25,377 [prior] Evaluating prior at array([ 0.30796169, -0.101945  ])
 2023-07-02 10:33:25,377 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:25,377 [model] Posterior to be computed for parameters {'Omega_m': 0.284914693969706, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,377 [prior] Evaluating prior at array([0.28491469, 0.51952372])
 2023-07-02 10:33:25,377 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,377 [model] Got input parameters: {'Omega_m': 0.284914693969706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,377 [classy] Got parameters {'Omega_m': 0.284914693969706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,377 [classy] Computing new state
 2023-07-02 10:33:25,377 [classy] Setting parameters: {'Omega_m': 0.284914693969706, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.71364698532796}
 2023-07-02 10:33:25,421 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,423 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.050213
 2023-07-02 10:33:25,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,423 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.08037
 2023-07-02 10:33:25,443 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,443 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.8090922166331185}
 2023-07-02 10:33:25,443 [prior] Evaluating prior at array([0.30796169, 0.80909222])
 2023-07-02 10:33:25,443 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,443 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8090922166331185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,443 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,443 [classy] Re-using computed results
 2023-07-02 10:33:25,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,443 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8090922166331185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,443 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -308.342
 2023-07-02 10:33:25,463 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,463 [model] Posterior to be computed for parameters {'Omega_m': 0.2982008582249032, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,463 [prior] Evaluating prior at array([0.29820086, 0.51952372])
 2023-07-02 10:33:25,463 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,463 [model] Got input parameters: {'Omega_m': 0.2982008582249032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,463 [classy] Got parameters {'Omega_m': 0.2982008582249032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,464 [classy] Computing new state
 2023-07-02 10:33:25,464 [classy] Setting parameters: {'Omega_m': 0.2982008582249032, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0144729111208}
 2023-07-02 10:33:25,508 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131711
 2023-07-02 10:33:25,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,530 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.847218
 2023-07-02 10:33:25,530 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,530 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': -1.7628234533603373}
 2023-07-02 10:33:25,530 [prior] Evaluating prior at array([ 0.30796169, -1.76282345])
 2023-07-02 10:33:25,531 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:25,531 [model] Posterior to be computed for parameters {'Omega_m': 0.30447441477554194, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,531 [prior] Evaluating prior at array([0.30447441, 0.51952372])
 2023-07-02 10:33:25,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,531 [model] Got input parameters: {'Omega_m': 0.30447441477554194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,531 [classy] Got parameters {'Omega_m': 0.30447441477554194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,531 [classy] Computing new state
 2023-07-02 10:33:25,531 [classy] Setting parameters: {'Omega_m': 0.30447441477554194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2350034609921}
 2023-07-02 10:33:25,575 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00421619
 2023-07-02 10:33:25,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,577 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,597 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25113
 2023-07-02 10:33:25,597 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,597 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 1.235299982626457}
 2023-07-02 10:33:25,597 [prior] Evaluating prior at array([0.30796169, 1.23529998])
 2023-07-02 10:33:25,597 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,597 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.235299982626457, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,598 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,598 [classy] Re-using computed results
 2023-07-02 10:33:25,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,598 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.235299982626457, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,598 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,619 [fs_likelihood.fslikelihood] Computed log-likelihood = -2651.87
 2023-07-02 10:33:25,619 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,619 [model] Posterior to be computed for parameters {'Omega_m': 0.3194329461577319, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,619 [prior] Evaluating prior at array([0.31943295, 0.51952372])
 2023-07-02 10:33:25,619 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,619 [model] Got input parameters: {'Omega_m': 0.3194329461577319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,619 [classy] Got parameters {'Omega_m': 0.3194329461577319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,619 [classy] Computing new state
 2023-07-02 10:33:25,619 [classy] Setting parameters: {'Omega_m': 0.3194329461577319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43215211073266}
 2023-07-02 10:33:25,664 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,666 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00311276
 2023-07-02 10:33:25,666 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,666 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,687 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.765809
 2023-07-02 10:33:25,687 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,687 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.13569190346342513}
 2023-07-02 10:33:25,688 [prior] Evaluating prior at array([0.30796169, 0.1356919 ])
 2023-07-02 10:33:25,688 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,688 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.13569190346342513, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,688 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,688 [classy] Re-using computed results
 2023-07-02 10:33:25,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,688 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.13569190346342513, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,688 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,709 [fs_likelihood.fslikelihood] Computed log-likelihood = -253.573
 2023-07-02 10:33:25,709 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,709 [model] Posterior to be computed for parameters {'Omega_m': 0.2995079138545972, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,709 [prior] Evaluating prior at array([0.29950791, 0.51952372])
 2023-07-02 10:33:25,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,709 [model] Got input parameters: {'Omega_m': 0.2995079138545972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,709 [classy] Got parameters {'Omega_m': 0.2995079138545972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,709 [classy] Computing new state
 2023-07-02 10:33:25,709 [classy] Setting parameters: {'Omega_m': 0.2995079138545972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,755 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.85088614150735}
 2023-07-02 10:33:25,755 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108702
 2023-07-02 10:33:25,756 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,756 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,778 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23849
 2023-07-02 10:33:25,778 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,779 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.5969587301513756}
 2023-07-02 10:33:25,779 [prior] Evaluating prior at array([0.30796169, 0.59695873])
 2023-07-02 10:33:25,779 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,779 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5969587301513756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,779 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,779 [classy] Re-using computed results
 2023-07-02 10:33:25,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,779 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5969587301513756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,779 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.8137
 2023-07-02 10:33:25,799 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,799 [model] Posterior to be computed for parameters {'Omega_m': 0.2940096597205522, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,799 [prior] Evaluating prior at array([0.29400966, 0.51952372])
 2023-07-02 10:33:25,799 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,799 [model] Got input parameters: {'Omega_m': 0.2940096597205522, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,799 [classy] Got parameters {'Omega_m': 0.2940096597205522, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,799 [classy] Computing new state
 2023-07-02 10:33:25,799 [classy] Setting parameters: {'Omega_m': 0.2940096597205522, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.5432744987018}
 2023-07-02 10:33:25,844 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221343
 2023-07-02 10:33:25,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,845 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.758095
 2023-07-02 10:33:25,865 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,865 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.46873955981859783}
 2023-07-02 10:33:25,865 [prior] Evaluating prior at array([0.30796169, 0.46873956])
 2023-07-02 10:33:25,866 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,866 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46873955981859783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,866 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,866 [classy] Re-using computed results
 2023-07-02 10:33:25,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
 2023-07-02 10:33:25,866 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46873955981859783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,866 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,886 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.42157
 2023-07-02 10:33:25,887 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,887 [prior] Evaluating prior at array([0.30724164, 0.51952372])
 2023-07-02 10:33:25,887 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,887 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,887 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,887 [classy] Computing new state
 2023-07-02 10:33:25,887 [classy] Setting parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:25,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
 2023-07-02 10:33:25,931 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:25,933 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00190998
 2023-07-02 10:33:25,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,933 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,952 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4897
 2023-07-02 10:33:25,953 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,953 [mcmc] New sample, #62:
   Omega_m:0.3079617, b1:0.5195237
 2023-07-02 10:33:25,953 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 1.1647778911305142}
 2023-07-02 10:33:25,953 [prior] Evaluating prior at array([0.30724164, 1.16477789])
 2023-07-02 10:33:25,953 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,953 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1647778911305142, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,953 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,953 [classy] Re-using computed results
 2023-07-02 10:33:25,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
 2023-07-02 10:33:25,953 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:25,953 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1647778911305142, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,953 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:25,973 [fs_likelihood.fslikelihood] Computed log-likelihood = -2028.34
 2023-07-02 10:33:25,973 [model] Computed derived parameters: {}
 2023-07-02 10:33:25,973 [model] Posterior to be computed for parameters {'Omega_m': 0.30133973011809095, 'b1': 0.5195237182842224}
 2023-07-02 10:33:25,973 [prior] Evaluating prior at array([0.30133973, 0.51952372])
 2023-07-02 10:33:25,973 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:25,973 [model] Got input parameters: {'Omega_m': 0.30133973011809095, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:25,973 [classy] Got parameters {'Omega_m': 0.30133973011809095, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:25,973 [classy] Computing new state
 2023-07-02 10:33:25,974 [classy] Setting parameters: {'Omega_m': 0.30133973011809095, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6226818769937}
 2023-07-02 10:33:26,017 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,019 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0080342
 2023-07-02 10:33:26,019 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,019 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,039 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.69936
 2023-07-02 10:33:26,039 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,040 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.39802286175431345}
 2023-07-02 10:33:26,040 [prior] Evaluating prior at array([0.30724164, 0.39802286])
 2023-07-02 10:33:26,040 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,040 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39802286175431345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,040 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,040 [classy] Re-using computed results
 2023-07-02 10:33:26,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
 2023-07-02 10:33:26,040 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39802286175431345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,060 [fs_likelihood.fslikelihood] Computed log-likelihood = -29.651
 2023-07-02 10:33:26,061 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,061 [model] Posterior to be computed for parameters {'Omega_m': 0.31703966455068633, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,061 [prior] Evaluating prior at array([0.31703966, 0.51952372])
 2023-07-02 10:33:26,061 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,061 [model] Got input parameters: {'Omega_m': 0.31703966455068633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,061 [classy] Got parameters {'Omega_m': 0.31703966455068633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,061 [classy] Computing new state
 2023-07-02 10:33:26,061 [classy] Setting parameters: {'Omega_m': 0.31703966455068633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.71547649536305}
 2023-07-02 10:33:26,105 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,107 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00146075
 2023-07-02 10:33:26,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,107 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,129 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46105
 2023-07-02 10:33:26,129 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,129 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.8757405683545079}
 2023-07-02 10:33:26,129 [prior] Evaluating prior at array([0.30724164, 0.87574057])
 2023-07-02 10:33:26,129 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,129 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8757405683545079, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,129 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,129 [classy] Re-using computed results
 2023-07-02 10:33:26,129 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
 2023-07-02 10:33:26,129 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,129 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8757405683545079, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,130 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -488.406
 2023-07-02 10:33:26,150 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,150 [model] Posterior to be computed for parameters {'Omega_m': 0.28906961564474176, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,150 [prior] Evaluating prior at array([0.28906962, 0.51952372])
 2023-07-02 10:33:26,150 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,150 [model] Got input parameters: {'Omega_m': 0.28906961564474176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,150 [classy] Got parameters {'Omega_m': 0.28906961564474176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,150 [classy] Computing new state
 2023-07-02 10:33:26,151 [classy] Setting parameters: {'Omega_m': 0.28906961564474176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.17502106524663}
 2023-07-02 10:33:26,194 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,196 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0358851
 2023-07-02 10:33:26,196 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,196 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,216 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.33663
 2023-07-02 10:33:26,216 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,216 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.22734163785337874}
 2023-07-02 10:33:26,216 [prior] Evaluating prior at array([0.30724164, 0.22734164])
 2023-07-02 10:33:26,216 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,216 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.22734163785337874, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,216 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,216 [classy] Re-using computed results
 2023-07-02 10:33:26,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
 2023-07-02 10:33:26,216 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,216 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.22734163785337874, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,216 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,237 [fs_likelihood.fslikelihood] Computed log-likelihood = -160.941
 2023-07-02 10:33:26,237 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,237 [model] Posterior to be computed for parameters {'Omega_m': 0.31079882662289215, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,237 [prior] Evaluating prior at array([0.31079883, 0.51952372])
 2023-07-02 10:33:26,237 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,237 [model] Got input parameters: {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,237 [classy] Got parameters {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,237 [classy] Computing new state
 2023-07-02 10:33:26,237 [classy] Setting parameters: {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.46338818545397}
 2023-07-02 10:33:26,281 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,283 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000377253
 2023-07-02 10:33:26,283 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,283 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,303 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45405
 2023-07-02 10:33:26,303 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,303 [mcmc] New sample, #63:
   Omega_m:0.3072416, b1:0.5195237
 2023-07-02 10:33:26,303 [model] Posterior to be computed for parameters {'Omega_m': 0.31079882662289215, 'b1': 0.48447863243664985}
 2023-07-02 10:33:26,303 [prior] Evaluating prior at array([0.31079883, 0.48447863])
 2023-07-02 10:33:26,303 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,303 [model] Got input parameters: {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48447863243664985, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,303 [classy] Got parameters {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,303 [classy] Re-using computed results
 2023-07-02 10:33:26,303 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.46338818545397}
 2023-07-02 10:33:26,303 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,303 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48447863243664985, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,304 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,324 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36821
 2023-07-02 10:33:26,324 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,324 [model] Posterior to be computed for parameters {'Omega_m': 0.30491062563358523, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,324 [prior] Evaluating prior at array([0.30491063, 0.51952372])
 2023-07-02 10:33:26,324 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,324 [model] Got input parameters: {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,324 [classy] Got parameters {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,324 [classy] Computing new state
 2023-07-02 10:33:26,324 [classy] Setting parameters: {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,368 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.18133469907934}
 2023-07-02 10:33:26,368 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,370 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.003787
 2023-07-02 10:33:26,370 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,370 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,390 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30421
 2023-07-02 10:33:26,390 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,390 [mcmc] New sample, #64:
   Omega_m:0.3107988, b1:0.5195237
 2023-07-02 10:33:26,390 [model] Posterior to be computed for parameters {'Omega_m': 0.30491062563358523, 'b1': 1.7018034328713654}
 2023-07-02 10:33:26,390 [prior] Evaluating prior at array([0.30491063, 1.70180343])
 2023-07-02 10:33:26,391 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,391 [model] Got input parameters: {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7018034328713654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,391 [classy] Got parameters {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,391 [classy] Re-using computed results
 2023-07-02 10:33:26,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.18133469907934}
 2023-07-02 10:33:26,391 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7018034328713654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,391 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,411 [fs_likelihood.fslikelihood] Computed log-likelihood = -9924.67
 2023-07-02 10:33:26,411 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,411 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,411 [prior] Evaluating prior at array([0.30689077, 0.51952372])
 2023-07-02 10:33:26,411 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,411 [model] Got input parameters: {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,411 [classy] Got parameters {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,411 [classy] Computing new state
 2023-07-02 10:33:26,411 [classy] Setting parameters: {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,459 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93854525778107}
 2023-07-02 10:33:26,460 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,461 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0021479
 2023-07-02 10:33:26,461 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,462 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,483 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47235
 2023-07-02 10:33:26,483 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,483 [mcmc] New sample, #65:
   Omega_m:0.3049106, b1:0.5195237
 2023-07-02 10:33:26,483 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': -0.7242928519955681}
 2023-07-02 10:33:26,483 [prior] Evaluating prior at array([ 0.30689077, -0.72429285])
 2023-07-02 10:33:26,483 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:26,483 [model] Posterior to be computed for parameters {'Omega_m': 0.32024040330016973, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,483 [prior] Evaluating prior at array([0.3202404 , 0.51952372])
 2023-07-02 10:33:26,483 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,483 [model] Got input parameters: {'Omega_m': 0.32024040330016973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,483 [classy] Got parameters {'Omega_m': 0.32024040330016973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,484 [classy] Computing new state
 2023-07-02 10:33:26,484 [classy] Setting parameters: {'Omega_m': 0.32024040330016973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3369878768257}
 2023-07-02 10:33:26,528 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00382124
 2023-07-02 10:33:26,530 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,530 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,550 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.49192
 2023-07-02 10:33:26,550 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,550 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': 1.4737475672089861}
 2023-07-02 10:33:26,550 [prior] Evaluating prior at array([0.30689077, 1.47374757])
 2023-07-02 10:33:26,550 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,550 [model] Got input parameters: {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4737475672089861, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,550 [classy] Got parameters {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,550 [classy] Re-using computed results
 2023-07-02 10:33:26,550 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93854525778107}
 2023-07-02 10:33:26,550 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,550 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4737475672089861, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,550 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,570 [fs_likelihood.fslikelihood] Computed log-likelihood = -5582.97
 2023-07-02 10:33:26,570 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,570 [model] Posterior to be computed for parameters {'Omega_m': 0.33343142329749453, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,570 [prior] Evaluating prior at array([0.33343142, 0.51952372])
 2023-07-02 10:33:26,570 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,570 [model] Got input parameters: {'Omega_m': 0.33343142329749453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,570 [classy] Got parameters {'Omega_m': 0.33343142329749453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,570 [classy] Computing new state
 2023-07-02 10:33:26,570 [classy] Setting parameters: {'Omega_m': 0.33343142329749453, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8120359681545}
 2023-07-02 10:33:26,614 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,615 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0257687
 2023-07-02 10:33:26,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,616 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,636 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.79227
 2023-07-02 10:33:26,636 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,636 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': -0.5045437248776469}
 2023-07-02 10:33:26,636 [prior] Evaluating prior at array([ 0.30689077, -0.50454372])
 2023-07-02 10:33:26,637 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:26,637 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,637 [prior] Evaluating prior at array([0.29894055, 0.51952372])
 2023-07-02 10:33:26,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,637 [model] Got input parameters: {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,637 [classy] Got parameters {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,637 [classy] Computing new state
 2023-07-02 10:33:26,637 [classy] Setting parameters: {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.92181981975565}
 2023-07-02 10:33:26,681 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0118405
 2023-07-02 10:33:26,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,683 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,703 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07503
 2023-07-02 10:33:26,703 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,703 [mcmc] New sample, #66:
   Omega_m:0.3068908, b1:0.5195237
 2023-07-02 10:33:26,703 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': -0.08300294939514119}
 2023-07-02 10:33:26,703 [prior] Evaluating prior at array([ 0.29894055, -0.08300295])
 2023-07-02 10:33:26,703 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:26,704 [model] Posterior to be computed for parameters {'Omega_m': 0.29822350627657324, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,704 [prior] Evaluating prior at array([0.29822351, 0.51952372])
 2023-07-02 10:33:26,704 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,704 [model] Got input parameters: {'Omega_m': 0.29822350627657324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,704 [classy] Got parameters {'Omega_m': 0.29822350627657324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,704 [classy] Computing new state
 2023-07-02 10:33:26,704 [classy] Setting parameters: {'Omega_m': 0.29822350627657324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,748 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0116352036433}
 2023-07-02 10:33:26,749 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,750 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131293
 2023-07-02 10:33:26,750 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,750 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,770 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.85444
 2023-07-02 10:33:26,770 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,770 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': -0.6037498143502248}
 2023-07-02 10:33:26,770 [prior] Evaluating prior at array([ 0.29894055, -0.60374981])
 2023-07-02 10:33:26,770 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:26,770 [model] Posterior to be computed for parameters {'Omega_m': 0.29710768172004637, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,770 [prior] Evaluating prior at array([0.29710768, 0.51952372])
 2023-07-02 10:33:26,771 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,771 [model] Got input parameters: {'Omega_m': 0.29710768172004637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,771 [classy] Got parameters {'Omega_m': 0.29710768172004637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,771 [classy] Computing new state
 2023-07-02 10:33:26,771 [classy] Setting parameters: {'Omega_m': 0.29710768172004637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.15177282220907}
 2023-07-02 10:33:26,815 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,816 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0152746
 2023-07-02 10:33:26,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,816 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,836 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.480043
 2023-07-02 10:33:26,836 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,837 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': 0.4768268561713}
 2023-07-02 10:33:26,837 [prior] Evaluating prior at array([0.29894055, 0.47682686])
 2023-07-02 10:33:26,837 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,837 [model] Got input parameters: {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4768268561713, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,837 [classy] Got parameters {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,837 [classy] Re-using computed results
 2023-07-02 10:33:26,837 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.92181981975565}
 2023-07-02 10:33:26,837 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,837 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4768268561713, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,837 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,857 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.64516
 2023-07-02 10:33:26,857 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,857 [model] Posterior to be computed for parameters {'Omega_m': 0.31546003866230893, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,857 [prior] Evaluating prior at array([0.31546004, 0.51952372])
 2023-07-02 10:33:26,857 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,857 [model] Got input parameters: {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,857 [classy] Got parameters {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,857 [classy] Computing new state
 2023-07-02 10:33:26,857 [classy] Setting parameters: {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9035219753674}
 2023-07-02 10:33:26,901 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000741594
 2023-07-02 10:33:26,903 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,903 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,923 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.82443
 2023-07-02 10:33:26,923 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,923 [mcmc] New sample, #67:
   Omega_m:0.2989405, b1:0.5195237
 2023-07-02 10:33:26,923 [model] Posterior to be computed for parameters {'Omega_m': 0.31546003866230893, 'b1': 0.933315576959987}
 2023-07-02 10:33:26,923 [prior] Evaluating prior at array([0.31546004, 0.93331558])
 2023-07-02 10:33:26,923 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,923 [model] Got input parameters: {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.933315576959987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,923 [classy] Got parameters {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,923 [classy] Re-using computed results
 2023-07-02 10:33:26,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9035219753674}
 2023-07-02 10:33:26,923 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:26,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.933315576959987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,923 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:26,944 [fs_likelihood.fslikelihood] Computed log-likelihood = -759.238
 2023-07-02 10:33:26,944 [model] Computed derived parameters: {}
 2023-07-02 10:33:26,944 [model] Posterior to be computed for parameters {'Omega_m': 0.3983003739067321, 'b1': 0.5195237182842224}
 2023-07-02 10:33:26,944 [prior] Evaluating prior at array([0.39830037, 0.51952372])
 2023-07-02 10:33:26,944 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:26,944 [model] Got input parameters: {'Omega_m': 0.3983003739067321, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,944 [classy] Got parameters {'Omega_m': 0.3983003739067321, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:26,944 [classy] Computing new state
 2023-07-02 10:33:26,944 [classy] Setting parameters: {'Omega_m': 0.3983003739067321, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:26,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.03501347492517}
 2023-07-02 10:33:26,988 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:26,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.370792
 2023-07-02 10:33:26,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:26,990 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,010 [fs_likelihood.fslikelihood] Computed log-likelihood = -119.665
 2023-07-02 10:33:27,010 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,010 [model] Posterior to be computed for parameters {'Omega_m': 0.31546003866230893, 'b1': -0.02033975695346002}
 2023-07-02 10:33:27,010 [prior] Evaluating prior at array([ 0.31546004, -0.02033976])
 2023-07-02 10:33:27,010 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:27,011 [model] Posterior to be computed for parameters {'Omega_m': 0.31072027943400077, 'b1': 0.5195237182842224}
 2023-07-02 10:33:27,011 [prior] Evaluating prior at array([0.31072028, 0.51952372])
 2023-07-02 10:33:27,011 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,011 [model] Got input parameters: {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,011 [classy] Got parameters {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,011 [classy] Computing new state
 2023-07-02 10:33:27,011 [classy] Setting parameters: {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.47288774333185}
 2023-07-02 10:33:27,056 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,058 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000393976
 2023-07-02 10:33:27,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,058 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,078 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.459
 2023-07-02 10:33:27,078 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,078 [mcmc] New sample, #68:
   Omega_m:0.31546, b1:0.5195237
 2023-07-02 10:33:27,078 [model] Posterior to be computed for parameters {'Omega_m': 0.31072027943400077, 'b1': 0.07579848278236362}
 2023-07-02 10:33:27,078 [prior] Evaluating prior at array([0.31072028, 0.07579848])
 2023-07-02 10:33:27,078 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,078 [model] Got input parameters: {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.07579848278236362, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,078 [classy] Got parameters {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,078 [classy] Re-using computed results
 2023-07-02 10:33:27,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.47288774333185}
 2023-07-02 10:33:27,078 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.07579848278236362, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,078 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,099 [fs_likelihood.fslikelihood] Computed log-likelihood = -314.293
 2023-07-02 10:33:27,099 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,099 [model] Posterior to be computed for parameters {'Omega_m': 0.3109607727905804, 'b1': 0.5195237182842224}
 2023-07-02 10:33:27,099 [prior] Evaluating prior at array([0.31096077, 0.51952372])
 2023-07-02 10:33:27,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,099 [model] Got input parameters: {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,099 [classy] Got parameters {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,099 [classy] Computing new state
 2023-07-02 10:33:27,099 [classy] Setting parameters: {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44381506408098}
 2023-07-02 10:33:27,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000345198
 2023-07-02 10:33:27,148 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,148 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,168 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.44326
 2023-07-02 10:33:27,168 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,168 [mcmc] New sample, #69:
   Omega_m:0.3107203, b1:0.5195237
 2023-07-02 10:33:27,168 [model] Posterior to be computed for parameters {'Omega_m': 0.3109607727905804, 'b1': 0.7717843124248623}
 2023-07-02 10:33:27,168 [prior] Evaluating prior at array([0.31096077, 0.77178431])
 2023-07-02 10:33:27,168 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,168 [model] Got input parameters: {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7717843124248623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,168 [classy] Got parameters {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,169 [classy] Re-using computed results
 2023-07-02 10:33:27,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44381506408098}
 2023-07-02 10:33:27,169 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7717843124248623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,169 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,188 [fs_likelihood.fslikelihood] Computed log-likelihood = -238.549
 2023-07-02 10:33:27,188 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,189 [model] Posterior to be computed for parameters {'Omega_m': 0.30801945684944393, 'b1': 0.5195237182842224}
 2023-07-02 10:33:27,189 [prior] Evaluating prior at array([0.30801946, 0.51952372])
 2023-07-02 10:33:27,189 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,189 [model] Got input parameters: {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,189 [classy] Got parameters {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,189 [classy] Computing new state
 2023-07-02 10:33:27,189 [classy] Setting parameters: {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,233 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80076778195385}
 2023-07-02 10:33:27,233 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,235 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00143842
 2023-07-02 10:33:27,235 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,235 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5148
 2023-07-02 10:33:27,255 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,255 [mcmc] New sample, #70:
   Omega_m:0.3109608, b1:0.5195237
 2023-07-02 10:33:27,255 [model] Posterior to be computed for parameters {'Omega_m': 0.30801945684944393, 'b1': 0.3044095565219965}
 2023-07-02 10:33:27,255 [prior] Evaluating prior at array([0.30801946, 0.30440956])
 2023-07-02 10:33:27,255 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,255 [model] Got input parameters: {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3044095565219965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,255 [classy] Got parameters {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,255 [classy] Re-using computed results
 2023-07-02 10:33:27,255 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80076778195385}
 2023-07-02 10:33:27,255 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3044095565219965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,255 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,275 [fs_likelihood.fslikelihood] Computed log-likelihood = -91.3448
 2023-07-02 10:33:27,275 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,275 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222451954286, 'b1': 0.5195237182842224}
 2023-07-02 10:33:27,275 [prior] Evaluating prior at array([0.31412225, 0.51952372])
 2023-07-02 10:33:27,275 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,275 [model] Got input parameters: {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,275 [classy] Got parameters {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,275 [classy] Computing new state
 2023-07-02 10:33:27,275 [classy] Setting parameters: {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,320 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344811477638}
 2023-07-02 10:33:27,320 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,321 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000366337
 2023-07-02 10:33:27,321 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,322 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,341 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07279
 2023-07-02 10:33:27,342 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,342 [mcmc] New sample, #71:
   Omega_m:0.3080195, b1:0.5195237
 2023-07-02 10:33:27,342 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222451954286, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,342 [prior] Evaluating prior at array([0.31412225, 0.51051188])
 2023-07-02 10:33:27,342 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,342 [model] Got input parameters: {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,342 [classy] Got parameters {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,342 [classy] Re-using computed results
 2023-07-02 10:33:27,342 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344811477638}
 2023-07-02 10:33:27,342 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,342 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,362 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72072
 2023-07-02 10:33:27,362 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,362 [mcmc] New sample, #72:
   Omega_m:0.3141222, b1:0.5195237
 2023-07-02 10:33:27,362 [model] Posterior to be computed for parameters {'Omega_m': 0.3116662689735015, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,362 [prior] Evaluating prior at array([0.31166627, 0.51051188])
 2023-07-02 10:33:27,362 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,362 [model] Got input parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,362 [classy] Got parameters {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,362 [classy] Computing new state
 2023-07-02 10:33:27,362 [classy] Setting parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,406 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35863904393676}
 2023-07-02 10:33:27,407 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,408 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000243456
 2023-07-02 10:33:27,408 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,408 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,428 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81022
 2023-07-02 10:33:27,428 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,428 [mcmc] New sample, #73:
   Omega_m:0.3141222, b1:0.5105119
 2023-07-02 10:33:27,428 [model] Posterior to be computed for parameters {'Omega_m': 0.3116662689735015, 'b1': 0.5423869192078473}
 2023-07-02 10:33:27,428 [prior] Evaluating prior at array([0.31166627, 0.54238692])
 2023-07-02 10:33:27,428 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,428 [model] Got input parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5423869192078473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,428 [classy] Got parameters {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,428 [classy] Re-using computed results
 2023-07-02 10:33:27,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35863904393676}
 2023-07-02 10:33:27,428 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,428 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5423869192078473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,429 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,448 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.751192
 2023-07-02 10:33:27,449 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,449 [model] Posterior to be computed for parameters {'Omega_m': 0.29542114913282985, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,449 [prior] Evaluating prior at array([0.29542115, 0.51051188])
 2023-07-02 10:33:27,449 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,449 [model] Got input parameters: {'Omega_m': 0.29542114913282985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,449 [classy] Got parameters {'Omega_m': 0.29542114913282985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,449 [classy] Computing new state
 2023-07-02 10:33:27,449 [classy] Setting parameters: {'Omega_m': 0.29542114913282985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,493 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.36446017207876}
 2023-07-02 10:33:27,493 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,495 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.018843
 2023-07-02 10:33:27,495 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,495 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,514 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.12068
 2023-07-02 10:33:27,514 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,515 [model] Posterior to be computed for parameters {'Omega_m': 0.3116662689735015, 'b1': 2.0233898161996606}
 2023-07-02 10:33:27,515 [prior] Evaluating prior at array([0.31166627, 2.02338982])
 2023-07-02 10:33:27,515 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,515 [model] Got input parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.0233898161996606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,515 [classy] Got parameters {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,515 [classy] Re-using computed results
 2023-07-02 10:33:27,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35863904393676}
 2023-07-02 10:33:27,515 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,515 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.0233898161996606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,515 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,535 [fs_likelihood.fslikelihood] Computed log-likelihood = -20522
 2023-07-02 10:33:27,535 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,535 [model] Posterior to be computed for parameters {'Omega_m': 0.3070391180491007, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,535 [prior] Evaluating prior at array([0.30703912, 0.51051188])
 2023-07-02 10:33:27,535 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,535 [model] Got input parameters: {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,535 [classy] Got parameters {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,535 [classy] Computing new state
 2023-07-02 10:33:27,535 [classy] Setting parameters: {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92041204173233}
 2023-07-02 10:33:27,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00204539
 2023-07-02 10:33:27,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,581 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,601 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4909
 2023-07-02 10:33:27,602 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,602 [mcmc] New sample, #74:
   Omega_m:0.3116663, b1:0.5105119
 2023-07-02 10:33:27,602 [model] Posterior to be computed for parameters {'Omega_m': 0.3070391180491007, 'b1': 0.8918573916496058}
 2023-07-02 10:33:27,602 [prior] Evaluating prior at array([0.30703912, 0.89185739])
 2023-07-02 10:33:27,602 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,602 [model] Got input parameters: {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8918573916496058, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,602 [classy] Got parameters {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,602 [classy] Re-using computed results
 2023-07-02 10:33:27,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92041204173233}
 2023-07-02 10:33:27,602 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8918573916496058, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,602 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -539.521
 2023-07-02 10:33:27,622 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,622 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,622 [prior] Evaluating prior at array([0.31096422, 0.51051188])
 2023-07-02 10:33:27,622 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,622 [model] Got input parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,622 [classy] Got parameters {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,622 [classy] Computing new state
 2023-07-02 10:33:27,622 [classy] Setting parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44339732401312}
 2023-07-02 10:33:27,666 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000344551
 2023-07-02 10:33:27,668 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,668 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,687 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8028
 2023-07-02 10:33:27,687 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,687 [mcmc] New sample, #75:
   Omega_m:0.3070391, b1:0.5105119
 2023-07-02 10:33:27,688 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': 0.09098674359463482}
 2023-07-02 10:33:27,688 [prior] Evaluating prior at array([0.31096422, 0.09098674])
 2023-07-02 10:33:27,688 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,688 [model] Got input parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.09098674359463482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,688 [classy] Got parameters {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,688 [classy] Re-using computed results
 2023-07-02 10:33:27,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44339732401312}
 2023-07-02 10:33:27,688 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.09098674359463482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,688 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -296.982
 2023-07-02 10:33:27,708 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,708 [model] Posterior to be computed for parameters {'Omega_m': 0.3213311636378495, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,708 [prior] Evaluating prior at array([0.32133116, 0.51051188])
 2023-07-02 10:33:27,708 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,708 [model] Got input parameters: {'Omega_m': 0.3213311636378495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,708 [classy] Got parameters {'Omega_m': 0.3213311636378495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,708 [classy] Computing new state
 2023-07-02 10:33:27,709 [classy] Setting parameters: {'Omega_m': 0.3213311636378495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.20877374326957}
 2023-07-02 10:33:27,752 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00489807
 2023-07-02 10:33:27,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,754 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,773 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42075
 2023-07-02 10:33:27,774 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,774 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': -0.073027341525574}
 2023-07-02 10:33:27,774 [prior] Evaluating prior at array([ 0.31096422, -0.07302734])
 2023-07-02 10:33:27,774 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:27,774 [model] Posterior to be computed for parameters {'Omega_m': 0.28965314656470253, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,774 [prior] Evaluating prior at array([0.28965315, 0.51051188])
 2023-07-02 10:33:27,774 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,774 [model] Got input parameters: {'Omega_m': 0.28965314656470253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,774 [classy] Got parameters {'Omega_m': 0.28965314656470253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,774 [classy] Computing new state
 2023-07-02 10:33:27,774 [classy] Setting parameters: {'Omega_m': 0.28965314656470253, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,818 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.09991312850602}
 2023-07-02 10:33:27,818 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,819 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0340774
 2023-07-02 10:33:27,820 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,820 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,839 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.40669
 2023-07-02 10:33:27,839 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,839 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': 1.3245926363231155}
 2023-07-02 10:33:27,839 [prior] Evaluating prior at array([0.31096422, 1.32459264])
 2023-07-02 10:33:27,839 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,840 [model] Got input parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3245926363231155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,840 [classy] Got parameters {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,840 [classy] Re-using computed results
 2023-07-02 10:33:27,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44339732401312}
 2023-07-02 10:33:27,840 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3245926363231155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,840 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,860 [fs_likelihood.fslikelihood] Computed log-likelihood = -3669.83
 2023-07-02 10:33:27,860 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3189529864464342, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,860 [prior] Evaluating prior at array([0.31895299, 0.51051188])
 2023-07-02 10:33:27,860 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,860 [model] Got input parameters: {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,860 [classy] Got parameters {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,860 [classy] Computing new state
 2023-07-02 10:33:27,860 [classy] Setting parameters: {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,904 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.48882050480427}
 2023-07-02 10:33:27,904 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00272759
 2023-07-02 10:33:27,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,906 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02063
 2023-07-02 10:33:27,925 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,925 [mcmc] New sample, #76:
   Omega_m:0.3109642, b1:0.5105119
 2023-07-02 10:33:27,926 [model] Posterior to be computed for parameters {'Omega_m': 0.3189529864464342, 'b1': 1.5609618453469905}
 2023-07-02 10:33:27,926 [prior] Evaluating prior at array([0.31895299, 1.56096185])
 2023-07-02 10:33:27,926 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,926 [model] Got input parameters: {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5609618453469905, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,926 [classy] Got parameters {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,926 [classy] Re-using computed results
 2023-07-02 10:33:27,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.48882050480427}
 2023-07-02 10:33:27,926 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:27,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5609618453469905, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,926 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:27,945 [fs_likelihood.fslikelihood] Computed log-likelihood = -7645.23
 2023-07-02 10:33:27,945 [model] Computed derived parameters: {}
 2023-07-02 10:33:27,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.510511879507605}
 2023-07-02 10:33:27,946 [prior] Evaluating prior at array([0.31186217, 0.51051188])
 2023-07-02 10:33:27,946 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:27,946 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,946 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:27,946 [classy] Computing new state
 2023-07-02 10:33:27,946 [classy] Setting parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:27,990 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
 2023-07-02 10:33:27,990 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:27,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000226117
 2023-07-02 10:33:27,991 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:27,991 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,012 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80967
 2023-07-02 10:33:28,012 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,012 [mcmc] New sample, #77:
   Omega_m:0.318953, b1:0.5105119
 2023-07-02 10:33:28,012 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': -1.2001337573775275}
 2023-07-02 10:33:28,012 [prior] Evaluating prior at array([ 0.31186217, -1.20013376])
 2023-07-02 10:33:28,012 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:28,012 [model] Posterior to be computed for parameters {'Omega_m': 0.2933876432486707, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,012 [prior] Evaluating prior at array([0.29338764, 0.51051188])
 2023-07-02 10:33:28,012 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,012 [model] Got input parameters: {'Omega_m': 0.2933876432486707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,013 [classy] Got parameters {'Omega_m': 0.2933876432486707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,013 [classy] Computing new state
 2023-07-02 10:33:28,013 [classy] Setting parameters: {'Omega_m': 0.2933876432486707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.6223130855612}
 2023-07-02 10:33:28,056 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,058 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0236737
 2023-07-02 10:33:28,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,058 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,078 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1661
 2023-07-02 10:33:28,078 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,078 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.23307091655401746}
 2023-07-02 10:33:28,078 [prior] Evaluating prior at array([0.31186217, 0.23307092])
 2023-07-02 10:33:28,078 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,078 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.23307091655401746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,078 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,078 [classy] Re-using computed results
 2023-07-02 10:33:28,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
 2023-07-02 10:33:28,078 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.23307091655401746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,078 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,098 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.841
 2023-07-02 10:33:28,098 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,098 [model] Posterior to be computed for parameters {'Omega_m': 0.29471412471260805, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,099 [prior] Evaluating prior at array([0.29471412, 0.51051188])
 2023-07-02 10:33:28,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,099 [model] Got input parameters: {'Omega_m': 0.29471412471260805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,099 [classy] Got parameters {'Omega_m': 0.29471412471260805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,099 [classy] Computing new state
 2023-07-02 10:33:28,099 [classy] Setting parameters: {'Omega_m': 0.29471412471260805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,144 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45393759543168}
 2023-07-02 10:33:28,144 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,146 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0204568
 2023-07-02 10:33:28,146 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,146 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,166 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.4702
 2023-07-02 10:33:28,166 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,167 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.15900443294048716}
 2023-07-02 10:33:28,167 [prior] Evaluating prior at array([0.31186217, 0.15900443])
 2023-07-02 10:33:28,167 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,167 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15900443294048716, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,167 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,167 [classy] Re-using computed results
 2023-07-02 10:33:28,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
 2023-07-02 10:33:28,167 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15900443294048716, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,167 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,187 [fs_likelihood.fslikelihood] Computed log-likelihood = -221.865
 2023-07-02 10:33:28,187 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,187 [model] Posterior to be computed for parameters {'Omega_m': 0.3040747775646616, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,187 [prior] Evaluating prior at array([0.30407478, 0.51051188])
 2023-07-02 10:33:28,187 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,187 [model] Got input parameters: {'Omega_m': 0.3040747775646616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,187 [classy] Got parameters {'Omega_m': 0.3040747775646616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,187 [classy] Computing new state
 2023-07-02 10:33:28,187 [classy] Setting parameters: {'Omega_m': 0.3040747775646616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28423482709456}
 2023-07-02 10:33:28,231 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,233 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00463118
 2023-07-02 10:33:28,233 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,233 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,253 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9513
 2023-07-02 10:33:28,253 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,253 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.6148850997181499}
 2023-07-02 10:33:28,253 [prior] Evaluating prior at array([0.31186217, 0.6148851 ])
 2023-07-02 10:33:28,253 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,253 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6148850997181499, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,254 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,254 [classy] Re-using computed results
 2023-07-02 10:33:28,254 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
 2023-07-02 10:33:28,254 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,254 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6148850997181499, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,254 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,274 [fs_likelihood.fslikelihood] Computed log-likelihood = -32.5798
 2023-07-02 10:33:28,274 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,274 [model] Posterior to be computed for parameters {'Omega_m': 0.3100697665230034, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,274 [prior] Evaluating prior at array([0.31006977, 0.51051188])
 2023-07-02 10:33:28,274 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,274 [model] Got input parameters: {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,274 [classy] Got parameters {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,274 [classy] Computing new state
 2023-07-02 10:33:28,274 [classy] Setting parameters: {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,318 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55162911848896}
 2023-07-02 10:33:28,318 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,320 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000561967
 2023-07-02 10:33:28,320 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,320 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,340 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77208
 2023-07-02 10:33:28,340 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,340 [mcmc] New sample, #78:
   Omega_m:0.3118622, b1:0.5105119
 2023-07-02 10:33:28,340 [model] Posterior to be computed for parameters {'Omega_m': 0.3100697665230034, 'b1': 1.107578690141842}
 2023-07-02 10:33:28,340 [prior] Evaluating prior at array([0.31006977, 1.10757869])
 2023-07-02 10:33:28,340 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,340 [model] Got input parameters: {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.107578690141842, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,340 [classy] Got parameters {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,340 [classy] Re-using computed results
 2023-07-02 10:33:28,340 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55162911848896}
 2023-07-02 10:33:28,341 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,341 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.107578690141842, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,341 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,361 [fs_likelihood.fslikelihood] Computed log-likelihood = -1651.46
 2023-07-02 10:33:28,361 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,361 [model] Posterior to be computed for parameters {'Omega_m': 0.3170673338430472, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,361 [prior] Evaluating prior at array([0.31706733, 0.51051188])
 2023-07-02 10:33:28,361 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,361 [model] Got input parameters: {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,361 [classy] Got parameters {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,361 [classy] Computing new state
 2023-07-02 10:33:28,361 [classy] Setting parameters: {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7121932359088}
 2023-07-02 10:33:28,408 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,409 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00147596
 2023-07-02 10:33:28,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,410 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37659
 2023-07-02 10:33:28,430 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,430 [mcmc] New sample, #79:
   Omega_m:0.3100698, b1:0.5105119
 2023-07-02 10:33:28,430 [model] Posterior to be computed for parameters {'Omega_m': 0.3170673338430472, 'b1': 1.1871695168601222}
 2023-07-02 10:33:28,430 [prior] Evaluating prior at array([0.31706733, 1.18716952])
 2023-07-02 10:33:28,430 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,431 [model] Got input parameters: {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1871695168601222, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,431 [classy] Got parameters {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,431 [classy] Re-using computed results
 2023-07-02 10:33:28,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7121932359088}
 2023-07-02 10:33:28,431 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1871695168601222, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,431 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,450 [fs_likelihood.fslikelihood] Computed log-likelihood = -2396.06
 2023-07-02 10:33:28,450 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,450 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,450 [prior] Evaluating prior at array([0.31293506, 0.51051188])
 2023-07-02 10:33:28,451 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,451 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,451 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,451 [classy] Computing new state
 2023-07-02 10:33:28,451 [classy] Setting parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
 2023-07-02 10:33:28,494 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000214845
 2023-07-02 10:33:28,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,496 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,517 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78641
 2023-07-02 10:33:28,517 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,517 [mcmc] New sample, #80:
   Omega_m:0.3170673, b1:0.5105119
 2023-07-02 10:33:28,517 [mcmc] Learn + convergence test @ 80 samples accepted.
 2023-07-02 10:33:28,517 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:33:28,522 [mcmc]  - Acceptance rate: 0.263
 2023-07-02 10:33:28,523 [mcmc]  - Condition number = 5172.46
 2023-07-02 10:33:28,523 [mcmc]  - Eigenvalues = array([7.78223671e-03, 4.02532716e+01])
 2023-07-02 10:33:28,523 [mcmc]  - Convergence of means: R-1 = 40.253272 after 64 accepted steps
 2023-07-02 10:33:28,523 [mcmc] Convergence less than requested for updates: waiting until the next convergence check.
 2023-07-02 10:33:28,523 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 1.3699776482394408}
 2023-07-02 10:33:28,523 [prior] Evaluating prior at array([0.31293506, 1.36997765])
 2023-07-02 10:33:28,523 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,523 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3699776482394408, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,523 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,523 [classy] Re-using computed results
 2023-07-02 10:33:28,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
 2023-07-02 10:33:28,523 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,523 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3699776482394408, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,523 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,544 [fs_likelihood.fslikelihood] Computed log-likelihood = -4292.78
 2023-07-02 10:33:28,544 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,544 [model] Posterior to be computed for parameters {'Omega_m': 0.30322111404638574, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,544 [prior] Evaluating prior at array([0.30322111, 0.51051188])
 2023-07-02 10:33:28,544 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,544 [model] Got input parameters: {'Omega_m': 0.30322111404638574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,544 [classy] Got parameters {'Omega_m': 0.30322111404638574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,544 [classy] Computing new state
 2023-07-02 10:33:28,544 [classy] Setting parameters: {'Omega_m': 0.30322111404638574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,589 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.38958432026266}
 2023-07-02 10:33:28,589 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,591 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00558753
 2023-07-02 10:33:28,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,591 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,611 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.74739
 2023-07-02 10:33:28,611 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,612 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 1.6986006887478249}
 2023-07-02 10:33:28,612 [prior] Evaluating prior at array([0.31293506, 1.69860069])
 2023-07-02 10:33:28,612 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,612 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6986006887478249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,612 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,612 [classy] Re-using computed results
 2023-07-02 10:33:28,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
 2023-07-02 10:33:28,612 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6986006887478249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,612 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -10343.2
 2023-07-02 10:33:28,632 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,632 [model] Posterior to be computed for parameters {'Omega_m': 0.31979737595941976, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,632 [prior] Evaluating prior at array([0.31979738, 0.51051188])
 2023-07-02 10:33:28,632 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,632 [model] Got input parameters: {'Omega_m': 0.31979737595941976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,632 [classy] Got parameters {'Omega_m': 0.31979737595941976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,632 [classy] Computing new state
 2023-07-02 10:33:28,632 [classy] Setting parameters: {'Omega_m': 0.31979737595941976, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.38917564309028}
 2023-07-02 10:33:28,676 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00342313
 2023-07-02 10:33:28,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,678 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,697 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.82692
 2023-07-02 10:33:28,697 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,697 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 0.6866664092026913}
 2023-07-02 10:33:28,698 [prior] Evaluating prior at array([0.31293506, 0.68666641])
 2023-07-02 10:33:28,698 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,698 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6866664092026913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,698 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,698 [classy] Re-using computed results
 2023-07-02 10:33:28,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
 2023-07-02 10:33:28,698 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6866664092026913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,698 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,719 [fs_likelihood.fslikelihood] Computed log-likelihood = -104.242
 2023-07-02 10:33:28,719 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,719 [model] Posterior to be computed for parameters {'Omega_m': 0.3027454002839479, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,719 [prior] Evaluating prior at array([0.3027454 , 0.51051188])
 2023-07-02 10:33:28,719 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,719 [model] Got input parameters: {'Omega_m': 0.3027454002839479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,719 [classy] Got parameters {'Omega_m': 0.3027454002839479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,719 [classy] Computing new state
 2023-07-02 10:33:28,719 [classy] Setting parameters: {'Omega_m': 0.3027454002839479, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,763 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.44840353356787}
 2023-07-02 10:33:28,764 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,765 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00616197
 2023-07-02 10:33:28,765 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,765 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,785 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62434
 2023-07-02 10:33:28,785 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,785 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 0.6899836820973305}
 2023-07-02 10:33:28,785 [prior] Evaluating prior at array([0.31293506, 0.68998368])
 2023-07-02 10:33:28,785 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,785 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6899836820973305, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,785 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,785 [classy] Re-using computed results
 2023-07-02 10:33:28,785 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
 2023-07-02 10:33:28,785 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,785 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6899836820973305, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,785 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,805 [fs_likelihood.fslikelihood] Computed log-likelihood = -108.519
 2023-07-02 10:33:28,805 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,805 [model] Posterior to be computed for parameters {'Omega_m': 0.32287791562147955, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,805 [prior] Evaluating prior at array([0.32287792, 0.51051188])
 2023-07-02 10:33:28,805 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,805 [model] Got input parameters: {'Omega_m': 0.32287791562147955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,805 [classy] Got parameters {'Omega_m': 0.32287791562147955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,805 [classy] Computing new state
 2023-07-02 10:33:28,805 [classy] Setting parameters: {'Omega_m': 0.32287791562147955, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02762402388845}
 2023-07-02 10:33:28,849 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00665912
 2023-07-02 10:33:28,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,851 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,871 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.940201
 2023-07-02 10:33:28,871 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,871 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 1.377510723496425}
 2023-07-02 10:33:28,872 [prior] Evaluating prior at array([0.31293506, 1.37751072])
 2023-07-02 10:33:28,872 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,872 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.377510723496425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,872 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,872 [classy] Re-using computed results
 2023-07-02 10:33:28,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
 2023-07-02 10:33:28,872 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:28,872 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.377510723496425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,872 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,891 [fs_likelihood.fslikelihood] Computed log-likelihood = -4392.73
 2023-07-02 10:33:28,891 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,891 [model] Posterior to be computed for parameters {'Omega_m': 0.31540071922536833, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,891 [prior] Evaluating prior at array([0.31540072, 0.51051188])
 2023-07-02 10:33:28,892 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,892 [model] Got input parameters: {'Omega_m': 0.31540071922536833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,892 [classy] Got parameters {'Omega_m': 0.31540071922536833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,892 [classy] Computing new state
 2023-07-02 10:33:28,892 [classy] Setting parameters: {'Omega_m': 0.31540071922536833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:28,936 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91059953499882}
 2023-07-02 10:33:28,936 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:28,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000720398
 2023-07-02 10:33:28,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,937 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:28,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60305
 2023-07-02 10:33:28,957 [model] Computed derived parameters: {}
 2023-07-02 10:33:28,957 [mcmc] New sample, #81:
   Omega_m:0.3129351, b1:0.5105119
 2023-07-02 10:33:28,957 [model] Posterior to be computed for parameters {'Omega_m': 0.31540071922536833, 'b1': -0.5041712964231465}
 2023-07-02 10:33:28,957 [prior] Evaluating prior at array([ 0.31540072, -0.5041713 ])
 2023-07-02 10:33:28,957 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:28,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3132009262188758, 'b1': 0.510511879507605}
 2023-07-02 10:33:28,957 [prior] Evaluating prior at array([0.31320093, 0.51051188])
 2023-07-02 10:33:28,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:28,958 [model] Got input parameters: {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:28,958 [classy] Got parameters {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:28,958 [classy] Computing new state
 2023-07-02 10:33:28,958 [classy] Setting parameters: {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,002 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17394355394978}
 2023-07-02 10:33:29,002 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000233847
 2023-07-02 10:33:29,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,003 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,024 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77534
 2023-07-02 10:33:29,024 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,024 [mcmc] New sample, #82:
   Omega_m:0.3154007, b1:0.5105119
 2023-07-02 10:33:29,024 [model] Posterior to be computed for parameters {'Omega_m': 0.3132009262188758, 'b1': 1.3084035322932421}
 2023-07-02 10:33:29,024 [prior] Evaluating prior at array([0.31320093, 1.30840353])
 2023-07-02 10:33:29,024 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,024 [model] Got input parameters: {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3084035322932421, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,024 [classy] Got parameters {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,024 [classy] Re-using computed results
 2023-07-02 10:33:29,024 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17394355394978}
 2023-07-02 10:33:29,024 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:29,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3084035322932421, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,024 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,044 [fs_likelihood.fslikelihood] Computed log-likelihood = -3540.7
 2023-07-02 10:33:29,044 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,044 [model] Posterior to be computed for parameters {'Omega_m': 0.29814529229457815, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,044 [prior] Evaluating prior at array([0.29814529, 0.51051188])
 2023-07-02 10:33:29,044 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,044 [model] Got input parameters: {'Omega_m': 0.29814529229457815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,044 [classy] Got parameters {'Omega_m': 0.29814529229457815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,044 [classy] Computing new state
 2023-07-02 10:33:29,044 [classy] Setting parameters: {'Omega_m': 0.29814529229457815, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0214418274543}
 2023-07-02 10:33:29,088 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132741
 2023-07-02 10:33:29,090 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,090 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,111 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0868517
 2023-07-02 10:33:29,111 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,111 [model] Posterior to be computed for parameters {'Omega_m': 0.3132009262188758, 'b1': -0.0817462090169998}
 2023-07-02 10:33:29,111 [prior] Evaluating prior at array([ 0.31320093, -0.08174621])
 2023-07-02 10:33:29,111 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:29,111 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,111 [prior] Evaluating prior at array([0.30867714, 0.51051188])
 2023-07-02 10:33:29,111 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,111 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,112 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,112 [classy] Computing new state
 2023-07-02 10:33:29,112 [classy] Setting parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,157 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
 2023-07-02 10:33:29,157 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00109962
 2023-07-02 10:33:29,158 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,158 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,178 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67683
 2023-07-02 10:33:29,179 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,179 [mcmc] New sample, #83:
   Omega_m:0.3132009, b1:0.5105119
 2023-07-02 10:33:29,179 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -0.9958898332894498}
 2023-07-02 10:33:29,179 [prior] Evaluating prior at array([ 0.30867714, -0.99588983])
 2023-07-02 10:33:29,179 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:29,179 [model] Posterior to be computed for parameters {'Omega_m': 0.29791442119222267, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,179 [prior] Evaluating prior at array([0.29791442, 0.51051188])
 2023-07-02 10:33:29,179 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,179 [model] Got input parameters: {'Omega_m': 0.29791442119222267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,179 [classy] Got parameters {'Omega_m': 0.29791442119222267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,179 [classy] Computing new state
 2023-07-02 10:33:29,179 [classy] Setting parameters: {'Omega_m': 0.29791442119222267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.05040754777798}
 2023-07-02 10:33:29,223 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,225 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137065
 2023-07-02 10:33:29,225 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,225 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,245 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.00691669
 2023-07-02 10:33:29,245 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,245 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 0.027527553050551823}
 2023-07-02 10:33:29,245 [prior] Evaluating prior at array([0.30867714, 0.02752755])
 2023-07-02 10:33:29,245 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,245 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.027527553050551823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,245 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,245 [classy] Re-using computed results
 2023-07-02 10:33:29,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
 2023-07-02 10:33:29,245 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:29,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.027527553050551823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,245 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -372.168
 2023-07-02 10:33:29,265 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,265 [model] Posterior to be computed for parameters {'Omega_m': 0.28025403658981685, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,265 [prior] Evaluating prior at array([0.28025404, 0.51051188])
 2023-07-02 10:33:29,265 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,265 [model] Got input parameters: {'Omega_m': 0.28025403658981685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,265 [classy] Got parameters {'Omega_m': 0.28025403658981685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,265 [classy] Computing new state
 2023-07-02 10:33:29,265 [classy] Setting parameters: {'Omega_m': 0.28025403658981685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,309 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3259796827307}
 2023-07-02 10:33:29,310 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,311 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0693989
 2023-07-02 10:33:29,311 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,311 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,331 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.8837
 2023-07-02 10:33:29,331 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,331 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -0.5741004210734669}
 2023-07-02 10:33:29,331 [prior] Evaluating prior at array([ 0.30867714, -0.57410042])
 2023-07-02 10:33:29,332 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:29,332 [model] Posterior to be computed for parameters {'Omega_m': 0.2948895775575782, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,332 [prior] Evaluating prior at array([0.29488958, 0.51051188])
 2023-07-02 10:33:29,332 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,332 [model] Got input parameters: {'Omega_m': 0.2948895775575782, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,332 [classy] Got parameters {'Omega_m': 0.2948895775575782, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,332 [classy] Computing new state
 2023-07-02 10:33:29,332 [classy] Setting parameters: {'Omega_m': 0.2948895775575782, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,376 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4317179768111}
 2023-07-02 10:33:29,376 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,377 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0200499
 2023-07-02 10:33:29,377 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,378 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,397 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.38207
 2023-07-02 10:33:29,397 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,397 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -2.6635045533376887}
 2023-07-02 10:33:29,397 [prior] Evaluating prior at array([ 0.30867714, -2.66350455])
 2023-07-02 10:33:29,397 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:29,397 [model] Posterior to be computed for parameters {'Omega_m': 0.2594474917032065, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,397 [prior] Evaluating prior at array([0.25944749, 0.51051188])
 2023-07-02 10:33:29,397 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,397 [model] Got input parameters: {'Omega_m': 0.2594474917032065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,398 [classy] Got parameters {'Omega_m': 0.2594474917032065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,398 [classy] Computing new state
 2023-07-02 10:33:29,398 [classy] Setting parameters: {'Omega_m': 0.2594474917032065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1700608232798}
 2023-07-02 10:33:29,442 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.198455
 2023-07-02 10:33:29,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,444 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -37.7918
 2023-07-02 10:33:29,463 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,463 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 1.441465329770376}
 2023-07-02 10:33:29,463 [prior] Evaluating prior at array([0.30867714, 1.44146533])
 2023-07-02 10:33:29,463 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,463 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.441465329770376, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,463 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,463 [classy] Computing new state
 2023-07-02 10:33:29,463 [classy] Setting parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,508 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
 2023-07-02 10:33:29,508 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,510 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00109962
 2023-07-02 10:33:29,510 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.441465329770376, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,510 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -5154.35
 2023-07-02 10:33:29,531 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,531 [model] Posterior to be computed for parameters {'Omega_m': 0.29310762835174614, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,531 [prior] Evaluating prior at array([0.29310763, 0.51051188])
 2023-07-02 10:33:29,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,531 [model] Got input parameters: {'Omega_m': 0.29310762835174614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,531 [classy] Got parameters {'Omega_m': 0.29310762835174614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,531 [classy] Computing new state
 2023-07-02 10:33:29,531 [classy] Setting parameters: {'Omega_m': 0.29310762835174614, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.65793890097405}
 2023-07-02 10:33:29,576 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0243845
 2023-07-02 10:33:29,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,577 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,597 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.3197
 2023-07-02 10:33:29,597 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,597 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 0.8170313498069216}
 2023-07-02 10:33:29,597 [prior] Evaluating prior at array([0.30867714, 0.81703135])
 2023-07-02 10:33:29,598 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,598 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8170313498069216, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,598 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,598 [classy] Re-using computed results
 2023-07-02 10:33:29,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
 2023-07-02 10:33:29,598 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:29,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8170313498069216, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,598 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,618 [fs_likelihood.fslikelihood] Computed log-likelihood = -331.069
 2023-07-02 10:33:29,618 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,618 [model] Posterior to be computed for parameters {'Omega_m': 0.3201995467766069, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,618 [prior] Evaluating prior at array([0.32019955, 0.51051188])
 2023-07-02 10:33:29,618 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,618 [model] Got input parameters: {'Omega_m': 0.3201995467766069, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,618 [classy] Got parameters {'Omega_m': 0.3201995467766069, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,618 [classy] Computing new state
 2023-07-02 10:33:29,618 [classy] Setting parameters: {'Omega_m': 0.3201995467766069, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,662 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34179800892252}
 2023-07-02 10:33:29,662 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00378357
 2023-07-02 10:33:29,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,664 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,684 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72719
 2023-07-02 10:33:29,684 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,684 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 1.5288595821896807}
 2023-07-02 10:33:29,684 [prior] Evaluating prior at array([0.30867714, 1.52885958])
 2023-07-02 10:33:29,684 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,684 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5288595821896807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,684 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,684 [classy] Re-using computed results
 2023-07-02 10:33:29,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
 2023-07-02 10:33:29,684 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:29,684 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5288595821896807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,685 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,705 [fs_likelihood.fslikelihood] Computed log-likelihood = -6574.06
 2023-07-02 10:33:29,705 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,705 [model] Posterior to be computed for parameters {'Omega_m': 0.29296069272429687, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,705 [prior] Evaluating prior at array([0.29296069, 0.51051188])
 2023-07-02 10:33:29,705 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,706 [model] Got input parameters: {'Omega_m': 0.29296069272429687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,706 [classy] Got parameters {'Omega_m': 0.29296069272429687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,706 [classy] Computing new state
 2023-07-02 10:33:29,706 [classy] Setting parameters: {'Omega_m': 0.29296069272429687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,751 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.67664911227692}
 2023-07-02 10:33:29,751 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,753 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247621
 2023-07-02 10:33:29,753 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,753 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,773 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.40124
 2023-07-02 10:33:29,773 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,773 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -0.2206187555957263}
 2023-07-02 10:33:29,773 [prior] Evaluating prior at array([ 0.30867714, -0.22061876])
 2023-07-02 10:33:29,773 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:29,773 [model] Posterior to be computed for parameters {'Omega_m': 0.3318034490223313, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,773 [prior] Evaluating prior at array([0.33180345, 0.51051188])
 2023-07-02 10:33:29,774 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,774 [model] Got input parameters: {'Omega_m': 0.3318034490223313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,774 [classy] Got parameters {'Omega_m': 0.3318034490223313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,774 [classy] Computing new state
 2023-07-02 10:33:29,774 [classy] Setting parameters: {'Omega_m': 0.3318034490223313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,818 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99725917221437}
 2023-07-02 10:33:29,818 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,820 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0220345
 2023-07-02 10:33:29,820 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,820 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,840 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22434
 2023-07-02 10:33:29,840 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,840 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 1.3195996238429446}
 2023-07-02 10:33:29,840 [prior] Evaluating prior at array([0.30867714, 1.31959962])
 2023-07-02 10:33:29,840 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,840 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3195996238429446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,840 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,840 [classy] Re-using computed results
 2023-07-02 10:33:29,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
 2023-07-02 10:33:29,841 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:29,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3195996238429446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,841 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,860 [fs_likelihood.fslikelihood] Computed log-likelihood = -3550.43
 2023-07-02 10:33:29,860 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,861 [prior] Evaluating prior at array([0.31060455, 0.51051188])
 2023-07-02 10:33:29,861 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,861 [model] Got input parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,861 [classy] Got parameters {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,861 [classy] Computing new state
 2023-07-02 10:33:29,861 [classy] Setting parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.48688575085552}
 2023-07-02 10:33:29,905 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,907 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000420009
 2023-07-02 10:33:29,907 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,908 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,928 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79331
 2023-07-02 10:33:29,928 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,928 [mcmc] New sample, #84:
   Omega_m:0.3086771, b1:0.5105119
 2023-07-02 10:33:29,928 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': 0.21400178716454288}
 2023-07-02 10:33:29,928 [prior] Evaluating prior at array([0.31060455, 0.21400179])
 2023-07-02 10:33:29,929 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,929 [model] Got input parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.21400178716454288, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,929 [classy] Got parameters {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,929 [classy] Re-using computed results
 2023-07-02 10:33:29,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.48688575085552}
 2023-07-02 10:33:29,929 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:29,929 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.21400178716454288, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,929 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:29,949 [fs_likelihood.fslikelihood] Computed log-likelihood = -168.208
 2023-07-02 10:33:29,949 [model] Computed derived parameters: {}
 2023-07-02 10:33:29,949 [model] Posterior to be computed for parameters {'Omega_m': 0.3162603393052345, 'b1': 0.510511879507605}
 2023-07-02 10:33:29,949 [prior] Evaluating prior at array([0.31626034, 0.51051188])
 2023-07-02 10:33:29,949 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:29,949 [model] Got input parameters: {'Omega_m': 0.3162603393052345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,949 [classy] Got parameters {'Omega_m': 0.3162603393052345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:29,949 [classy] Computing new state
 2023-07-02 10:33:29,949 [classy] Setting parameters: {'Omega_m': 0.3162603393052345, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:29,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80814397077353}
 2023-07-02 10:33:29,994 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:29,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0010688
 2023-07-02 10:33:29,995 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:29,995 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,015 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49657
 2023-07-02 10:33:30,015 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,015 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': -0.541302597363798}
 2023-07-02 10:33:30,015 [prior] Evaluating prior at array([ 0.31060455, -0.5413026 ])
 2023-07-02 10:33:30,016 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:30,016 [model] Posterior to be computed for parameters {'Omega_m': 0.31964494874295624, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,016 [prior] Evaluating prior at array([0.31964495, 0.51051188])
 2023-07-02 10:33:30,016 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,016 [model] Got input parameters: {'Omega_m': 0.31964494874295624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,016 [classy] Got parameters {'Omega_m': 0.31964494874295624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,016 [classy] Computing new state
 2023-07-02 10:33:30,016 [classy] Setting parameters: {'Omega_m': 0.31964494874295624, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.40714501773252}
 2023-07-02 10:33:30,060 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00329145
 2023-07-02 10:33:30,062 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,062 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.86346
 2023-07-02 10:33:30,083 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,083 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': 3.5107304685957548}
 2023-07-02 10:33:30,083 [prior] Evaluating prior at array([0.31060455, 3.51073047])
 2023-07-02 10:33:30,083 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,083 [model] Got input parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 3.5107304685957548, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,083 [classy] Got parameters {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,083 [classy] Re-using computed results
 2023-07-02 10:33:30,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.48688575085552}
 2023-07-02 10:33:30,083 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 3.5107304685957548, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,083 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,103 [fs_likelihood.fslikelihood] Computed log-likelihood = -172463
 2023-07-02 10:33:30,103 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,103 [model] Posterior to be computed for parameters {'Omega_m': 0.30456567764696935, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,103 [prior] Evaluating prior at array([0.30456568, 0.51051188])
 2023-07-02 10:33:30,103 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,103 [model] Got input parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,103 [classy] Got parameters {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,104 [classy] Computing new state
 2023-07-02 10:33:30,104 [classy] Setting parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2237685652061}
 2023-07-02 10:33:30,158 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00412433
 2023-07-02 10:33:30,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,160 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,180 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05874
 2023-07-02 10:33:30,180 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,180 [mcmc] New sample, #85:
   Omega_m:0.3106045, b1:0.5105119
 2023-07-02 10:33:30,180 [model] Posterior to be computed for parameters {'Omega_m': 0.30456567764696935, 'b1': 1.146721970671471}
 2023-07-02 10:33:30,180 [prior] Evaluating prior at array([0.30456568, 1.14672197])
 2023-07-02 10:33:30,181 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,181 [model] Got input parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.146721970671471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,181 [classy] Got parameters {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,181 [classy] Re-using computed results
 2023-07-02 10:33:30,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2237685652061}
 2023-07-02 10:33:30,181 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,181 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.146721970671471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,181 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,201 [fs_likelihood.fslikelihood] Computed log-likelihood = -1846.08
 2023-07-02 10:33:30,201 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,201 [model] Posterior to be computed for parameters {'Omega_m': 0.28747699989957104, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,201 [prior] Evaluating prior at array([0.287477  , 0.51051188])
 2023-07-02 10:33:30,201 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,201 [model] Got input parameters: {'Omega_m': 0.28747699989957104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,201 [classy] Got parameters {'Omega_m': 0.28747699989957104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,201 [classy] Computing new state
 2023-07-02 10:33:30,201 [classy] Setting parameters: {'Omega_m': 0.28747699989957104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.38067460101394}
 2023-07-02 10:33:30,245 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,247 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0410732
 2023-07-02 10:33:30,247 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,247 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,267 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.90381
 2023-07-02 10:33:30,267 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,267 [model] Posterior to be computed for parameters {'Omega_m': 0.30456567764696935, 'b1': 1.5801913557241027}
 2023-07-02 10:33:30,267 [prior] Evaluating prior at array([0.30456568, 1.58019136])
 2023-07-02 10:33:30,267 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,267 [model] Got input parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5801913557241027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,267 [classy] Got parameters {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,267 [classy] Re-using computed results
 2023-07-02 10:33:30,267 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2237685652061}
 2023-07-02 10:33:30,267 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5801913557241027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,267 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -7328.07
 2023-07-02 10:33:30,288 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,288 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,288 [prior] Evaluating prior at array([0.30513133, 0.51051188])
 2023-07-02 10:33:30,288 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,288 [model] Got input parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,288 [classy] Got parameters {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,288 [classy] Computing new state
 2023-07-02 10:33:30,288 [classy] Setting parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.15420420376265}
 2023-07-02 10:33:30,333 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,335 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00357923
 2023-07-02 10:33:30,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,335 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,355 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17364
 2023-07-02 10:33:30,356 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,356 [mcmc] New sample, #86:
   Omega_m:0.3045657, b1:0.5105119
 2023-07-02 10:33:30,356 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': -0.1255377975072438}
 2023-07-02 10:33:30,356 [prior] Evaluating prior at array([ 0.30513133, -0.1255378 ])
 2023-07-02 10:33:30,356 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:30,356 [model] Posterior to be computed for parameters {'Omega_m': 0.2982486691649924, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,356 [prior] Evaluating prior at array([0.29824867, 0.51051188])
 2023-07-02 10:33:30,356 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,356 [model] Got input parameters: {'Omega_m': 0.2982486691649924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,356 [classy] Got parameters {'Omega_m': 0.2982486691649924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,356 [classy] Computing new state
 2023-07-02 10:33:30,356 [classy] Setting parameters: {'Omega_m': 0.2982486691649924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0084779442951}
 2023-07-02 10:33:30,402 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0130828
 2023-07-02 10:33:30,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,404 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,424 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.128324
 2023-07-02 10:33:30,424 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,424 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': 1.4045761218467945}
 2023-07-02 10:33:30,424 [prior] Evaluating prior at array([0.30513133, 1.40457612])
 2023-07-02 10:33:30,425 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,425 [model] Got input parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4045761218467945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,425 [classy] Got parameters {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,425 [classy] Re-using computed results
 2023-07-02 10:33:30,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.15420420376265}
 2023-07-02 10:33:30,425 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4045761218467945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,425 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,445 [fs_likelihood.fslikelihood] Computed log-likelihood = -4510.75
 2023-07-02 10:33:30,445 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,445 [model] Posterior to be computed for parameters {'Omega_m': 0.2934181760088821, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,445 [prior] Evaluating prior at array([0.29341818, 0.51051188])
 2023-07-02 10:33:30,445 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,445 [model] Got input parameters: {'Omega_m': 0.2934181760088821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,445 [classy] Got parameters {'Omega_m': 0.2934181760088821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,445 [classy] Computing new state
 2023-07-02 10:33:30,445 [classy] Setting parameters: {'Omega_m': 0.2934181760088821, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.61842936385415}
 2023-07-02 10:33:30,489 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0235968
 2023-07-02 10:33:30,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,491 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,511 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1495
 2023-07-02 10:33:30,511 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,511 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': -0.4060076221101059}
 2023-07-02 10:33:30,511 [prior] Evaluating prior at array([ 0.30513133, -0.40600762])
 2023-07-02 10:33:30,511 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:30,511 [model] Posterior to be computed for parameters {'Omega_m': 0.32889537577222305, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,511 [prior] Evaluating prior at array([0.32889538, 0.51051188])
 2023-07-02 10:33:30,511 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,511 [model] Got input parameters: {'Omega_m': 0.32889537577222305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,511 [classy] Got parameters {'Omega_m': 0.32889537577222305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,511 [classy] Computing new state
 2023-07-02 10:33:30,511 [classy] Setting parameters: {'Omega_m': 0.32889537577222305, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,555 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.33018195655924}
 2023-07-02 10:33:30,555 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,557 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0160676
 2023-07-02 10:33:30,557 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,557 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,576 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.60695
 2023-07-02 10:33:30,577 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,577 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': 0.8638417869564398}
 2023-07-02 10:33:30,577 [prior] Evaluating prior at array([0.30513133, 0.86384179])
 2023-07-02 10:33:30,577 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,577 [model] Got input parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8638417869564398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,577 [classy] Got parameters {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,577 [classy] Re-using computed results
 2023-07-02 10:33:30,577 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.15420420376265}
 2023-07-02 10:33:30,577 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8638417869564398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,577 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,597 [fs_likelihood.fslikelihood] Computed log-likelihood = -439.393
 2023-07-02 10:33:30,597 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,597 [model] Posterior to be computed for parameters {'Omega_m': 0.30286665987814726, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,597 [prior] Evaluating prior at array([0.30286666, 0.51051188])
 2023-07-02 10:33:30,597 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,597 [model] Got input parameters: {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,597 [classy] Got parameters {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,597 [classy] Computing new state
 2023-07-02 10:33:30,597 [classy] Setting parameters: {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,641 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4334017783611}
 2023-07-02 10:33:30,641 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,643 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00601269
 2023-07-02 10:33:30,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,643 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,662 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65634
 2023-07-02 10:33:30,662 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,662 [mcmc] New sample, #87:
   Omega_m:0.3051313, b1:0.5105119
 2023-07-02 10:33:30,662 [model] Posterior to be computed for parameters {'Omega_m': 0.30286665987814726, 'b1': 3.340819491012145}
 2023-07-02 10:33:30,662 [prior] Evaluating prior at array([0.30286666, 3.34081949])
 2023-07-02 10:33:30,662 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,662 [model] Got input parameters: {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 3.340819491012145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,662 [classy] Got parameters {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,662 [classy] Re-using computed results
 2023-07-02 10:33:30,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4334017783611}
 2023-07-02 10:33:30,663 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 3.340819491012145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,663 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,682 [fs_likelihood.fslikelihood] Computed log-likelihood = -137440
 2023-07-02 10:33:30,682 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,682 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,682 [prior] Evaluating prior at array([0.31498327, 0.51051188])
 2023-07-02 10:33:30,682 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,682 [model] Got input parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,682 [classy] Got parameters {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,682 [classy] Computing new state
 2023-07-02 10:33:30,682 [classy] Setting parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96044280105662}
 2023-07-02 10:33:30,726 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000583166
 2023-07-02 10:33:30,728 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,728 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,748 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64682
 2023-07-02 10:33:30,748 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,748 [mcmc] New sample, #88:
   Omega_m:0.3028667, b1:0.5105119
 2023-07-02 10:33:30,748 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': -0.0034649455522184347}
 2023-07-02 10:33:30,748 [prior] Evaluating prior at array([ 0.31498327, -0.00346495])
 2023-07-02 10:33:30,748 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:30,749 [model] Posterior to be computed for parameters {'Omega_m': 0.30020534454799486, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,749 [prior] Evaluating prior at array([0.30020534, 0.51051188])
 2023-07-02 10:33:30,749 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,749 [model] Got input parameters: {'Omega_m': 0.30020534454799486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,749 [classy] Got parameters {'Omega_m': 0.30020534454799486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,749 [classy] Computing new state
 2023-07-02 10:33:30,749 [classy] Setting parameters: {'Omega_m': 0.30020534454799486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,793 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.76385339293995}
 2023-07-02 10:33:30,793 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,794 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00973721
 2023-07-02 10:33:30,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,794 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,814 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.853282
 2023-07-02 10:33:30,814 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,814 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': 0.13609352219110488}
 2023-07-02 10:33:30,814 [prior] Evaluating prior at array([0.31498327, 0.13609352])
 2023-07-02 10:33:30,814 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,814 [model] Got input parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.13609352219110488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,814 [classy] Got parameters {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,814 [classy] Re-using computed results
 2023-07-02 10:33:30,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96044280105662}
 2023-07-02 10:33:30,815 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,815 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.13609352219110488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,815 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,834 [fs_likelihood.fslikelihood] Computed log-likelihood = -240.707
 2023-07-02 10:33:30,834 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,834 [model] Posterior to be computed for parameters {'Omega_m': 0.27339348975141387, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,834 [prior] Evaluating prior at array([0.27339349, 0.51051188])
 2023-07-02 10:33:30,834 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,834 [model] Got input parameters: {'Omega_m': 0.27339348975141387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,835 [classy] Got parameters {'Omega_m': 0.27339348975141387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,835 [classy] Computing new state
 2023-07-02 10:33:30,835 [classy] Setting parameters: {'Omega_m': 0.27339348975141387, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.2433553636712}
 2023-07-02 10:33:30,878 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103874
 2023-07-02 10:33:30,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,880 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,900 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.002
 2023-07-02 10:33:30,900 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,900 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': 1.0454258679711703}
 2023-07-02 10:33:30,900 [prior] Evaluating prior at array([0.31498327, 1.04542587])
 2023-07-02 10:33:30,901 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,901 [model] Got input parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0454258679711703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,901 [classy] Got parameters {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,901 [classy] Re-using computed results
 2023-07-02 10:33:30,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96044280105662}
 2023-07-02 10:33:30,901 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:30,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0454258679711703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,901 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,922 [fs_likelihood.fslikelihood] Computed log-likelihood = -1319.56
 2023-07-02 10:33:30,922 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,922 [model] Posterior to be computed for parameters {'Omega_m': 0.29452615129947335, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,922 [prior] Evaluating prior at array([0.29452615, 0.51051188])
 2023-07-02 10:33:30,922 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,922 [model] Got input parameters: {'Omega_m': 0.29452615129947335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,922 [classy] Got parameters {'Omega_m': 0.29452615129947335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,922 [classy] Computing new state
 2023-07-02 10:33:30,922 [classy] Setting parameters: {'Omega_m': 0.29452615129947335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:30,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.47775750773326}
 2023-07-02 10:33:30,966 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:30,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0208976
 2023-07-02 10:33:30,968 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,968 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:30,988 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.56563
 2023-07-02 10:33:30,988 [model] Computed derived parameters: {}
 2023-07-02 10:33:30,988 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': -0.24265851412123307}
 2023-07-02 10:33:30,988 [prior] Evaluating prior at array([ 0.31498327, -0.24265851])
 2023-07-02 10:33:30,988 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:30,988 [model] Posterior to be computed for parameters {'Omega_m': 0.3040363147599663, 'b1': 0.510511879507605}
 2023-07-02 10:33:30,988 [prior] Evaluating prior at array([0.30403631, 0.51051188])
 2023-07-02 10:33:30,988 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:30,988 [model] Got input parameters: {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:30,988 [classy] Got parameters {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:30,988 [classy] Computing new state
 2023-07-02 10:33:30,988 [classy] Setting parameters: {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28897360630606}
 2023-07-02 10:33:31,033 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,034 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00467218
 2023-07-02 10:33:31,034 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,034 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,054 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94258
 2023-07-02 10:33:31,055 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,055 [mcmc] New sample, #89:
   Omega_m:0.3149833, b1:0.5105119
 2023-07-02 10:33:31,055 [model] Posterior to be computed for parameters {'Omega_m': 0.3040363147599663, 'b1': -0.8481631845335226}
 2023-07-02 10:33:31,055 [prior] Evaluating prior at array([ 0.30403631, -0.84816318])
 2023-07-02 10:33:31,055 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:31,055 [model] Posterior to be computed for parameters {'Omega_m': 0.33597264887436257, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,055 [prior] Evaluating prior at array([0.33597265, 0.51051188])
 2023-07-02 10:33:31,055 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,055 [model] Got input parameters: {'Omega_m': 0.33597264887436257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,055 [classy] Got parameters {'Omega_m': 0.33597264887436257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,055 [classy] Computing new state
 2023-07-02 10:33:31,055 [classy] Setting parameters: {'Omega_m': 0.33597264887436257, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5245344783747}
 2023-07-02 10:33:31,100 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,101 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0321534
 2023-07-02 10:33:31,101 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,101 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,124 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.98242
 2023-07-02 10:33:31,124 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,124 [model] Posterior to be computed for parameters {'Omega_m': 0.3040363147599663, 'b1': 0.4223719764271592}
 2023-07-02 10:33:31,124 [prior] Evaluating prior at array([0.30403631, 0.42237198])
 2023-07-02 10:33:31,124 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,124 [model] Got input parameters: {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4223719764271592, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,124 [classy] Got parameters {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,124 [classy] Re-using computed results
 2023-07-02 10:33:31,124 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28897360630606}
 2023-07-02 10:33:31,124 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,124 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4223719764271592, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,124 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,146 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.9466
 2023-07-02 10:33:31,146 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,146 [model] Posterior to be computed for parameters {'Omega_m': 0.3073216159437114, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,146 [prior] Evaluating prior at array([0.30732162, 0.51051188])
 2023-07-02 10:33:31,146 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,146 [model] Got input parameters: {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,146 [classy] Got parameters {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,146 [classy] Computing new state
 2023-07-02 10:33:31,146 [classy] Setting parameters: {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,190 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8859019013764}
 2023-07-02 10:33:31,190 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,192 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00185794
 2023-07-02 10:33:31,192 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,192 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,212 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52867
 2023-07-02 10:33:31,212 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,212 [mcmc] New sample, #90:
   Omega_m:0.3040363, b1:0.5105119
 2023-07-02 10:33:31,212 [model] Posterior to be computed for parameters {'Omega_m': 0.3073216159437114, 'b1': 1.4644300837696178}
 2023-07-02 10:33:31,212 [prior] Evaluating prior at array([0.30732162, 1.46443008])
 2023-07-02 10:33:31,212 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,212 [model] Got input parameters: {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4644300837696178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,212 [classy] Got parameters {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,212 [classy] Re-using computed results
 2023-07-02 10:33:31,212 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8859019013764}
 2023-07-02 10:33:31,212 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,212 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4644300837696178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,212 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,232 [fs_likelihood.fslikelihood] Computed log-likelihood = -5453.8
 2023-07-02 10:33:31,232 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,232 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,232 [prior] Evaluating prior at array([0.3051136 , 0.51051188])
 2023-07-02 10:33:31,233 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,233 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,233 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,233 [classy] Computing new state
 2023-07-02 10:33:31,233 [classy] Setting parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,277 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00359567
 2023-07-02 10:33:31,278 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,278 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,299 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17018
 2023-07-02 10:33:31,299 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,299 [mcmc] New sample, #91:
   Omega_m:0.3073216, b1:0.5105119
 2023-07-02 10:33:31,299 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': -0.29015794151644647}
 2023-07-02 10:33:31,299 [prior] Evaluating prior at array([ 0.3051136 , -0.29015794])
 2023-07-02 10:33:31,299 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:31,299 [model] Posterior to be computed for parameters {'Omega_m': 0.2946663252175768, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,299 [prior] Evaluating prior at array([0.29466633, 0.51051188])
 2023-07-02 10:33:31,299 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,299 [model] Got input parameters: {'Omega_m': 0.2946663252175768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,299 [classy] Got parameters {'Omega_m': 0.2946663252175768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,299 [classy] Computing new state
 2023-07-02 10:33:31,299 [classy] Setting parameters: {'Omega_m': 0.2946663252175768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45999214764888}
 2023-07-02 10:33:31,345 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0205683
 2023-07-02 10:33:31,347 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,347 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,367 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.49436
 2023-07-02 10:33:31,367 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,367 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.7263119954371279}
 2023-07-02 10:33:31,367 [prior] Evaluating prior at array([0.3051136, 0.726312 ])
 2023-07-02 10:33:31,367 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,367 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7263119954371279, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,367 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,367 [classy] Re-using computed results
 2023-07-02 10:33:31,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,367 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7263119954371279, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,367 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,386 [fs_likelihood.fslikelihood] Computed log-likelihood = -138.859
 2023-07-02 10:33:31,387 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,387 [model] Posterior to be computed for parameters {'Omega_m': 0.2952596373400552, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,387 [prior] Evaluating prior at array([0.29525964, 0.51051188])
 2023-07-02 10:33:31,387 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,387 [model] Got input parameters: {'Omega_m': 0.2952596373400552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,387 [classy] Got parameters {'Omega_m': 0.2952596373400552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,387 [classy] Computing new state
 2023-07-02 10:33:31,387 [classy] Setting parameters: {'Omega_m': 0.2952596373400552, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.38488513167317}
 2023-07-02 10:33:31,431 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,433 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0192056
 2023-07-02 10:33:31,433 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,433 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,453 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.19921
 2023-07-02 10:33:31,454 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,454 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.010467230522064441}
 2023-07-02 10:33:31,454 [prior] Evaluating prior at array([0.3051136 , 0.01046723])
 2023-07-02 10:33:31,454 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,454 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.010467230522064441, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,454 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,454 [classy] Re-using computed results
 2023-07-02 10:33:31,454 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,454 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.010467230522064441, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,454 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,474 [fs_likelihood.fslikelihood] Computed log-likelihood = -397.744
 2023-07-02 10:33:31,474 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,474 [model] Posterior to be computed for parameters {'Omega_m': 0.28736112308624284, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,474 [prior] Evaluating prior at array([0.28736112, 0.51051188])
 2023-07-02 10:33:31,474 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,474 [model] Got input parameters: {'Omega_m': 0.28736112308624284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,474 [classy] Got parameters {'Omega_m': 0.28736112308624284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,474 [classy] Computing new state
 2023-07-02 10:33:31,474 [classy] Setting parameters: {'Omega_m': 0.28736112308624284, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,519 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.39567769730567}
 2023-07-02 10:33:31,519 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0414654
 2023-07-02 10:33:31,521 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,521 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,541 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.98749
 2023-07-02 10:33:31,541 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,541 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 1.5258068269156086}
 2023-07-02 10:33:31,541 [prior] Evaluating prior at array([0.3051136 , 1.52580683])
 2023-07-02 10:33:31,541 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,541 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5258068269156086, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,541 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,541 [classy] Re-using computed results
 2023-07-02 10:33:31,541 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,541 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5258068269156086, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,541 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,561 [fs_likelihood.fslikelihood] Computed log-likelihood = -6368.86
 2023-07-02 10:33:31,561 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,562 [model] Posterior to be computed for parameters {'Omega_m': 0.28921320678237655, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,562 [prior] Evaluating prior at array([0.28921321, 0.51051188])
 2023-07-02 10:33:31,562 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,562 [model] Got input parameters: {'Omega_m': 0.28921320678237655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,562 [classy] Got parameters {'Omega_m': 0.28921320678237655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,562 [classy] Computing new state
 2023-07-02 10:33:31,562 [classy] Setting parameters: {'Omega_m': 0.28921320678237655, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.15652620457902}
 2023-07-02 10:33:31,606 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,607 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0354356
 2023-07-02 10:33:31,607 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,607 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,627 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.69799
 2023-07-02 10:33:31,627 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,627 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.14939700929281846}
 2023-07-02 10:33:31,627 [prior] Evaluating prior at array([0.3051136 , 0.14939701])
 2023-07-02 10:33:31,628 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,628 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.14939700929281846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,628 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,628 [classy] Re-using computed results
 2023-07-02 10:33:31,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,628 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.14939700929281846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,628 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,647 [fs_likelihood.fslikelihood] Computed log-likelihood = -244.082
 2023-07-02 10:33:31,647 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,648 [model] Posterior to be computed for parameters {'Omega_m': 0.30053191871268436, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,648 [prior] Evaluating prior at array([0.30053192, 0.51051188])
 2023-07-02 10:33:31,648 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,648 [model] Got input parameters: {'Omega_m': 0.30053191871268436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,648 [classy] Got parameters {'Omega_m': 0.30053191871268436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,648 [classy] Computing new state
 2023-07-02 10:33:31,648 [classy] Setting parameters: {'Omega_m': 0.30053191871268436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7231580211562}
 2023-07-02 10:33:31,692 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00922912
 2023-07-02 10:33:31,693 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,693 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,713 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.963178
 2023-07-02 10:33:31,713 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,713 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.41480488255373427}
 2023-07-02 10:33:31,714 [prior] Evaluating prior at array([0.3051136 , 0.41480488])
 2023-07-02 10:33:31,714 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,714 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41480488255373427, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,714 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,714 [classy] Re-using computed results
 2023-07-02 10:33:31,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,714 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41480488255373427, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,714 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,734 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.4164
 2023-07-02 10:33:31,734 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,734 [model] Posterior to be computed for parameters {'Omega_m': 0.3341128418266844, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,734 [prior] Evaluating prior at array([0.33411284, 0.51051188])
 2023-07-02 10:33:31,734 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,734 [model] Got input parameters: {'Omega_m': 0.3341128418266844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,734 [classy] Got parameters {'Omega_m': 0.3341128418266844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,734 [classy] Computing new state
 2023-07-02 10:33:31,734 [classy] Setting parameters: {'Omega_m': 0.3341128418266844, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.73474985200932}
 2023-07-02 10:33:31,778 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0274146
 2023-07-02 10:33:31,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,780 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.68815
 2023-07-02 10:33:31,799 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,799 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 2.7510528102294525}
 2023-07-02 10:33:31,799 [prior] Evaluating prior at array([0.3051136 , 2.75105281])
 2023-07-02 10:33:31,799 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,799 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.7510528102294525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,799 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,800 [classy] Re-using computed results
 2023-07-02 10:33:31,800 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,800 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,800 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.7510528102294525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,800 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,820 [fs_likelihood.fslikelihood] Computed log-likelihood = -65556.1
 2023-07-02 10:33:31,820 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,820 [model] Posterior to be computed for parameters {'Omega_m': 0.32283816543868477, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,820 [prior] Evaluating prior at array([0.32283817, 0.51051188])
 2023-07-02 10:33:31,820 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,820 [model] Got input parameters: {'Omega_m': 0.32283816543868477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,820 [classy] Got parameters {'Omega_m': 0.32283816543868477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,820 [classy] Computing new state
 2023-07-02 10:33:31,820 [classy] Setting parameters: {'Omega_m': 0.32283816543868477, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03226954824564}
 2023-07-02 10:33:31,864 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00661045
 2023-07-02 10:33:31,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,866 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,886 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.953443
 2023-07-02 10:33:31,886 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,886 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.002146526028987905}
 2023-07-02 10:33:31,886 [prior] Evaluating prior at array([0.3051136 , 0.00214653])
 2023-07-02 10:33:31,886 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,886 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.002146526028987905, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,886 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,886 [classy] Re-using computed results
 2023-07-02 10:33:31,886 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
 2023-07-02 10:33:31,886 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:31,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.002146526028987905, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,886 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,906 [fs_likelihood.fslikelihood] Computed log-likelihood = -407.121
 2023-07-02 10:33:31,906 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,906 [model] Posterior to be computed for parameters {'Omega_m': 0.3078560551897329, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,906 [prior] Evaluating prior at array([0.30785606, 0.51051188])
 2023-07-02 10:33:31,906 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,906 [model] Got input parameters: {'Omega_m': 0.3078560551897329, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,906 [classy] Got parameters {'Omega_m': 0.3078560551897329, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,906 [classy] Computing new state
 2023-07-02 10:33:31,906 [classy] Setting parameters: {'Omega_m': 0.3078560551897329, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:31,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82068910756414}
 2023-07-02 10:33:31,950 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:31,952 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00153111
 2023-07-02 10:33:31,952 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,952 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:31,972 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59362
 2023-07-02 10:33:31,972 [model] Computed derived parameters: {}
 2023-07-02 10:33:31,972 [mcmc] New sample, #92:
   Omega_m:0.3051136, b1:0.5105119
 2023-07-02 10:33:31,972 [model] Posterior to be computed for parameters {'Omega_m': 0.3078560551897329, 'b1': -0.5454829397011657}
 2023-07-02 10:33:31,972 [prior] Evaluating prior at array([ 0.30785606, -0.54548294])
 2023-07-02 10:33:31,972 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:31,972 [model] Posterior to be computed for parameters {'Omega_m': 0.3098111876524504, 'b1': 0.510511879507605}
 2023-07-02 10:33:31,972 [prior] Evaluating prior at array([0.30981119, 0.51051188])
 2023-07-02 10:33:31,972 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:31,973 [model] Got input parameters: {'Omega_m': 0.3098111876524504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:31,973 [classy] Got parameters {'Omega_m': 0.3098111876524504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:31,973 [classy] Computing new state
 2023-07-02 10:33:31,973 [classy] Setting parameters: {'Omega_m': 0.3098111876524504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58297050751267}
 2023-07-02 10:33:32,018 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00064341
 2023-07-02 10:33:32,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,020 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,042 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75876
 2023-07-02 10:33:32,042 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,042 [mcmc] New sample, #93:
   Omega_m:0.3078561, b1:0.5105119
 2023-07-02 10:33:32,042 [model] Posterior to be computed for parameters {'Omega_m': 0.3098111876524504, 'b1': -1.1655607977874505}
 2023-07-02 10:33:32,042 [prior] Evaluating prior at array([ 0.30981119, -1.1655608 ])
 2023-07-02 10:33:32,042 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:32,042 [model] Posterior to be computed for parameters {'Omega_m': 0.31779364668864063, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,042 [prior] Evaluating prior at array([0.31779365, 0.51051188])
 2023-07-02 10:33:32,042 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,042 [model] Got input parameters: {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,042 [classy] Got parameters {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,042 [classy] Computing new state
 2023-07-02 10:33:32,042 [classy] Setting parameters: {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6260148063591}
 2023-07-02 10:33:32,087 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,088 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00190849
 2023-07-02 10:33:32,088 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,088 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,108 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25202
 2023-07-02 10:33:32,108 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,108 [mcmc] New sample, #94:
   Omega_m:0.3098112, b1:0.5105119
 2023-07-02 10:33:32,109 [model] Posterior to be computed for parameters {'Omega_m': 0.31779364668864063, 'b1': 0.35034600656704085}
 2023-07-02 10:33:32,109 [prior] Evaluating prior at array([0.31779365, 0.35034601])
 2023-07-02 10:33:32,109 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,109 [model] Got input parameters: {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.35034600656704085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,109 [classy] Got parameters {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,109 [classy] Re-using computed results
 2023-07-02 10:33:32,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6260148063591}
 2023-07-02 10:33:32,109 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.35034600656704085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,109 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,131 [fs_likelihood.fslikelihood] Computed log-likelihood = -46.0412
 2023-07-02 10:33:32,131 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,131 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,131 [prior] Evaluating prior at array([0.30987177, 0.51051188])
 2023-07-02 10:33:32,131 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,131 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,131 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,131 [classy] Computing new state
 2023-07-02 10:33:32,131 [classy] Setting parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,176 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
 2023-07-02 10:33:32,176 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,178 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000623579
 2023-07-02 10:33:32,178 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,178 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,197 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76206
 2023-07-02 10:33:32,197 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,197 [mcmc] New sample, #95:
   Omega_m:0.3177936, b1:0.5105119
 2023-07-02 10:33:32,198 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 0.4739781878054233}
 2023-07-02 10:33:32,198 [prior] Evaluating prior at array([0.30987177, 0.47397819])
 2023-07-02 10:33:32,198 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,198 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4739781878054233, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,198 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,198 [classy] Re-using computed results
 2023-07-02 10:33:32,198 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
 2023-07-02 10:33:32,198 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4739781878054233, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,198 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,218 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.531097
 2023-07-02 10:33:32,218 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,218 [model] Posterior to be computed for parameters {'Omega_m': 0.3176712685694544, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,218 [prior] Evaluating prior at array([0.31767127, 0.51051188])
 2023-07-02 10:33:32,219 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,219 [model] Got input parameters: {'Omega_m': 0.3176712685694544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,219 [classy] Got parameters {'Omega_m': 0.3176712685694544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,219 [classy] Computing new state
 2023-07-02 10:33:32,219 [classy] Setting parameters: {'Omega_m': 0.3176712685694544, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.64052256841083}
 2023-07-02 10:33:32,263 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,264 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00183125
 2023-07-02 10:33:32,264 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,264 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27411
 2023-07-02 10:33:32,284 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,284 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 2.2254855235159896}
 2023-07-02 10:33:32,284 [prior] Evaluating prior at array([0.30987177, 2.22548552])
 2023-07-02 10:33:32,284 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,284 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.2254855235159896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,284 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,284 [classy] Re-using computed results
 2023-07-02 10:33:32,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
 2023-07-02 10:33:32,284 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,284 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.2254855235159896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,284 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -29487.7
 2023-07-02 10:33:32,304 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,304 [model] Posterior to be computed for parameters {'Omega_m': 0.30227722602460516, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,304 [prior] Evaluating prior at array([0.30227723, 0.51051188])
 2023-07-02 10:33:32,304 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,304 [model] Got input parameters: {'Omega_m': 0.30227722602460516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,304 [classy] Got parameters {'Omega_m': 0.30227722602460516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,304 [classy] Computing new state
 2023-07-02 10:33:32,304 [classy] Setting parameters: {'Omega_m': 0.30227722602460516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,348 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.50637125042036}
 2023-07-02 10:33:32,349 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,350 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00675648
 2023-07-02 10:33:32,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,350 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.49666
 2023-07-02 10:33:32,371 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,371 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': -0.5690400495012625}
 2023-07-02 10:33:32,371 [prior] Evaluating prior at array([ 0.30987177, -0.56904005])
 2023-07-02 10:33:32,371 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:32,371 [model] Posterior to be computed for parameters {'Omega_m': 0.31816045863227715, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,371 [prior] Evaluating prior at array([0.31816046, 0.51051188])
 2023-07-02 10:33:32,371 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,371 [model] Got input parameters: {'Omega_m': 0.31816045863227715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,371 [classy] Got parameters {'Omega_m': 0.31816045863227715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,371 [classy] Computing new state
 2023-07-02 10:33:32,371 [classy] Setting parameters: {'Omega_m': 0.31816045863227715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.58255803642194}
 2023-07-02 10:33:32,415 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,417 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00215059
 2023-07-02 10:33:32,417 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,417 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,437 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18314
 2023-07-02 10:33:32,437 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,437 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 0.7493333508975278}
 2023-07-02 10:33:32,437 [prior] Evaluating prior at array([0.30987177, 0.74933335])
 2023-07-02 10:33:32,437 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,437 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7493333508975278, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,437 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,437 [classy] Re-using computed results
 2023-07-02 10:33:32,437 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
 2023-07-02 10:33:32,437 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,437 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7493333508975278, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,437 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,456 [fs_likelihood.fslikelihood] Computed log-likelihood = -191.347
 2023-07-02 10:33:32,457 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,457 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,457 [prior] Evaluating prior at array([0.30956332, 0.51051188])
 2023-07-02 10:33:32,457 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,457 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,457 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,457 [classy] Computing new state
 2023-07-02 10:33:32,457 [classy] Setting parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,501 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
 2023-07-02 10:33:32,501 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,503 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000729336
 2023-07-02 10:33:32,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,503 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,523 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74412
 2023-07-02 10:33:32,523 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,523 [mcmc] New sample, #96:
   Omega_m:0.3098718, b1:0.5105119
 2023-07-02 10:33:32,523 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.7019446235702383}
 2023-07-02 10:33:32,523 [prior] Evaluating prior at array([0.30956332, 0.70194462])
 2023-07-02 10:33:32,524 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,524 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7019446235702383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,524 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,524 [classy] Re-using computed results
 2023-07-02 10:33:32,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
 2023-07-02 10:33:32,524 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7019446235702383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,524 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,544 [fs_likelihood.fslikelihood] Computed log-likelihood = -115.991
 2023-07-02 10:33:32,544 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,544 [model] Posterior to be computed for parameters {'Omega_m': 0.3025119063100622, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,544 [prior] Evaluating prior at array([0.30251191, 0.51051188])
 2023-07-02 10:33:32,544 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,544 [model] Got input parameters: {'Omega_m': 0.3025119063100622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,544 [classy] Got parameters {'Omega_m': 0.3025119063100622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,544 [classy] Computing new state
 2023-07-02 10:33:32,544 [classy] Setting parameters: {'Omega_m': 0.3025119063100622, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,588 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.47730297595706}
 2023-07-02 10:33:32,588 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,590 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00645483
 2023-07-02 10:33:32,590 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,590 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,609 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.56148
 2023-07-02 10:33:32,609 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,610 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.5829274204437522}
 2023-07-02 10:33:32,610 [prior] Evaluating prior at array([0.30956332, 0.58292742])
 2023-07-02 10:33:32,610 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,610 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5829274204437522, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,610 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,610 [classy] Re-using computed results
 2023-07-02 10:33:32,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
 2023-07-02 10:33:32,610 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,610 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5829274204437522, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,610 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,630 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4893
 2023-07-02 10:33:32,630 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,630 [model] Posterior to be computed for parameters {'Omega_m': 0.3276328459041586, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,630 [prior] Evaluating prior at array([0.32763285, 0.51051188])
 2023-07-02 10:33:32,630 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,630 [model] Got input parameters: {'Omega_m': 0.3276328459041586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,631 [classy] Got parameters {'Omega_m': 0.3276328459041586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,631 [classy] Computing new state
 2023-07-02 10:33:32,631 [classy] Setting parameters: {'Omega_m': 0.3276328459041586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.47556045259122}
 2023-07-02 10:33:32,674 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,676 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137614
 2023-07-02 10:33:32,676 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,676 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,695 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.983154
 2023-07-02 10:33:32,696 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,696 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.6411235121404907}
 2023-07-02 10:33:32,696 [prior] Evaluating prior at array([0.30956332, 0.64112351])
 2023-07-02 10:33:32,696 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,696 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6411235121404907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,696 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,696 [classy] Re-using computed results
 2023-07-02 10:33:32,696 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
 2023-07-02 10:33:32,696 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,696 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6411235121404907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,696 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,716 [fs_likelihood.fslikelihood] Computed log-likelihood = -49.4994
 2023-07-02 10:33:32,716 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,716 [model] Posterior to be computed for parameters {'Omega_m': 0.31244015636324024, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,716 [prior] Evaluating prior at array([0.31244016, 0.51051188])
 2023-07-02 10:33:32,716 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,716 [model] Got input parameters: {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,716 [classy] Got parameters {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,716 [classy] Computing new state
 2023-07-02 10:33:32,716 [classy] Setting parameters: {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,761 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2653991901287}
 2023-07-02 10:33:32,761 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,762 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202492
 2023-07-02 10:33:32,763 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,763 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,782 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8014
 2023-07-02 10:33:32,782 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,783 [mcmc] New sample, #97:
   Omega_m:0.3095633, b1:0.5105119
 2023-07-02 10:33:32,783 [model] Posterior to be computed for parameters {'Omega_m': 0.31244015636324024, 'b1': 0.8217941664462871}
 2023-07-02 10:33:32,783 [prior] Evaluating prior at array([0.31244016, 0.82179417])
 2023-07-02 10:33:32,783 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,783 [model] Got input parameters: {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8217941664462871, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,783 [classy] Got parameters {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,783 [classy] Re-using computed results
 2023-07-02 10:33:32,783 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2653991901287}
 2023-07-02 10:33:32,783 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:32,783 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8217941664462871, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,783 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,802 [fs_likelihood.fslikelihood] Computed log-likelihood = -362.145
 2023-07-02 10:33:32,802 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,802 [model] Posterior to be computed for parameters {'Omega_m': 0.31323915876884106, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,802 [prior] Evaluating prior at array([0.31323916, 0.51051188])
 2023-07-02 10:33:32,803 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,803 [model] Got input parameters: {'Omega_m': 0.31323915876884106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,803 [classy] Got parameters {'Omega_m': 0.31323915876884106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,803 [classy] Computing new state
 2023-07-02 10:33:32,803 [classy] Setting parameters: {'Omega_m': 0.31323915876884106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,847 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16935013865367}
 2023-07-02 10:33:32,847 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,849 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0002373
 2023-07-02 10:33:32,849 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,849 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,869 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77358
 2023-07-02 10:33:32,869 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,869 [mcmc] New sample, #98:
   Omega_m:0.3124402, b1:0.5105119
 2023-07-02 10:33:32,869 [model] Posterior to be computed for parameters {'Omega_m': 0.31323915876884106, 'b1': -0.34351747761885154}
 2023-07-02 10:33:32,869 [prior] Evaluating prior at array([ 0.31323916, -0.34351748])
 2023-07-02 10:33:32,869 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:32,869 [model] Posterior to be computed for parameters {'Omega_m': 0.3059748688108159, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,869 [prior] Evaluating prior at array([0.30597487, 0.51051188])
 2023-07-02 10:33:32,870 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,870 [model] Got input parameters: {'Omega_m': 0.3059748688108159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,870 [classy] Got parameters {'Omega_m': 0.3059748688108159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,870 [classy] Computing new state
 2023-07-02 10:33:32,870 [classy] Setting parameters: {'Omega_m': 0.3059748688108159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.05067481764775}
 2023-07-02 10:33:32,913 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,915 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00284329
 2023-07-02 10:33:32,915 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,915 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:32,936 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32728
 2023-07-02 10:33:32,936 [model] Computed derived parameters: {}
 2023-07-02 10:33:32,936 [mcmc] New sample, #99:
   Omega_m:0.3132392, b1:0.5105119
 2023-07-02 10:33:32,936 [model] Posterior to be computed for parameters {'Omega_m': 0.3059748688108159, 'b1': -0.051229575028154284}
 2023-07-02 10:33:32,936 [prior] Evaluating prior at array([ 0.30597487, -0.05122958])
 2023-07-02 10:33:32,936 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:32,936 [model] Posterior to be computed for parameters {'Omega_m': 0.3120549252100124, 'b1': 0.510511879507605}
 2023-07-02 10:33:32,936 [prior] Evaluating prior at array([0.31205493, 0.51051188])
 2023-07-02 10:33:32,936 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:32,936 [model] Got input parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,936 [classy] Got parameters {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:32,936 [classy] Computing new state
 2023-07-02 10:33:32,936 [classy] Setting parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:32,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31178730067924}
 2023-07-02 10:33:32,980 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:32,982 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00021367
 2023-07-02 10:33:32,982 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:32,982 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,002 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80802
 2023-07-02 10:33:33,002 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,002 [mcmc] New sample, #100:
   Omega_m:0.3059749, b1:0.5105119
 2023-07-02 10:33:33,002 [model] Posterior to be computed for parameters {'Omega_m': 0.3120549252100124, 'b1': 0.4075412264820113}
 2023-07-02 10:33:33,002 [prior] Evaluating prior at array([0.31205493, 0.40754123])
 2023-07-02 10:33:33,002 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,002 [model] Got input parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4075412264820113, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,002 [classy] Got parameters {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,002 [classy] Re-using computed results
 2023-07-02 10:33:33,002 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31178730067924}
 2023-07-02 10:33:33,002 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,002 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4075412264820113, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,002 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,022 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.5697
 2023-07-02 10:33:33,022 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,022 [model] Posterior to be computed for parameters {'Omega_m': 0.3088482424904877, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,022 [prior] Evaluating prior at array([0.30884824, 0.51051188])
 2023-07-02 10:33:33,023 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,023 [model] Got input parameters: {'Omega_m': 0.3088482424904877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,023 [classy] Got parameters {'Omega_m': 0.3088482424904877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,023 [classy] Computing new state
 2023-07-02 10:33:33,023 [classy] Setting parameters: {'Omega_m': 0.3088482424904877, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,067 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.69988718689928}
 2023-07-02 10:33:33,067 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,069 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00102042
 2023-07-02 10:33:33,069 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,069 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,089 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69165
 2023-07-02 10:33:33,089 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,089 [model] Posterior to be computed for parameters {'Omega_m': 0.3120549252100124, 'b1': 0.7261570305217346}
 2023-07-02 10:33:33,089 [prior] Evaluating prior at array([0.31205493, 0.72615703])
 2023-07-02 10:33:33,089 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,089 [model] Got input parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7261570305217346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,089 [classy] Got parameters {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,089 [classy] Re-using computed results
 2023-07-02 10:33:33,089 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31178730067924}
 2023-07-02 10:33:33,089 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7261570305217346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,089 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,109 [fs_likelihood.fslikelihood] Computed log-likelihood = -158.863
 2023-07-02 10:33:33,109 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,109 [model] Posterior to be computed for parameters {'Omega_m': 0.31088615709183126, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,109 [prior] Evaluating prior at array([0.31088616, 0.51051188])
 2023-07-02 10:33:33,109 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,109 [model] Got input parameters: {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,109 [classy] Got parameters {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,109 [classy] Computing new state
 2023-07-02 10:33:33,109 [classy] Setting parameters: {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4528310642076}
 2023-07-02 10:33:33,163 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000359562
 2023-07-02 10:33:33,165 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,165 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,185 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80106
 2023-07-02 10:33:33,185 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,185 [mcmc] New sample, #101:
   Omega_m:0.3120549, b1:0.5105119
 2023-07-02 10:33:33,185 [model] Posterior to be computed for parameters {'Omega_m': 0.31088615709183126, 'b1': 0.25565431804546845}
 2023-07-02 10:33:33,185 [prior] Evaluating prior at array([0.31088616, 0.25565432])
 2023-07-02 10:33:33,186 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,186 [model] Got input parameters: {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.25565431804546845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,186 [classy] Got parameters {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,186 [classy] Re-using computed results
 2023-07-02 10:33:33,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4528310642076}
 2023-07-02 10:33:33,186 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.25565431804546845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -128.582
 2023-07-02 10:33:33,205 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,206 [model] Posterior to be computed for parameters {'Omega_m': 0.3024573072565006, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,206 [prior] Evaluating prior at array([0.30245731, 0.51051188])
 2023-07-02 10:33:33,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,206 [model] Got input parameters: {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,206 [classy] Got parameters {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,206 [classy] Computing new state
 2023-07-02 10:33:33,206 [classy] Setting parameters: {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.48406417630432}
 2023-07-02 10:33:33,251 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00652436
 2023-07-02 10:33:33,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,253 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,273 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54654
 2023-07-02 10:33:33,273 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,273 [mcmc] New sample, #102:
   Omega_m:0.3108862, b1:0.5105119
 2023-07-02 10:33:33,273 [model] Posterior to be computed for parameters {'Omega_m': 0.3024573072565006, 'b1': -0.0029531139727430045}
 2023-07-02 10:33:33,273 [prior] Evaluating prior at array([ 0.30245731, -0.00295311])
 2023-07-02 10:33:33,273 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:33,273 [model] Posterior to be computed for parameters {'Omega_m': 0.2929279432859943, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,273 [prior] Evaluating prior at array([0.29292794, 0.51051188])
 2023-07-02 10:33:33,273 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,273 [model] Got input parameters: {'Omega_m': 0.2929279432859943, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,273 [classy] Got parameters {'Omega_m': 0.2929279432859943, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,273 [classy] Computing new state
 2023-07-02 10:33:33,273 [classy] Setting parameters: {'Omega_m': 0.2929279432859943, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.68081943336216}
 2023-07-02 10:33:33,317 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0248466
 2023-07-02 10:33:33,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,319 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,339 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.4195
 2023-07-02 10:33:33,339 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,340 [model] Posterior to be computed for parameters {'Omega_m': 0.3024573072565006, 'b1': 1.0457747798097379}
 2023-07-02 10:33:33,340 [prior] Evaluating prior at array([0.30245731, 1.04577478])
 2023-07-02 10:33:33,340 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,340 [model] Got input parameters: {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0457747798097379, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,340 [classy] Got parameters {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,340 [classy] Re-using computed results
 2023-07-02 10:33:33,340 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.48406417630432}
 2023-07-02 10:33:33,340 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,340 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0457747798097379, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,340 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,359 [fs_likelihood.fslikelihood] Computed log-likelihood = -1171.06
 2023-07-02 10:33:33,359 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,359 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,359 [prior] Evaluating prior at array([0.31070132, 0.51051188])
 2023-07-02 10:33:33,360 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,360 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,360 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,360 [classy] Computing new state
 2023-07-02 10:33:33,360 [classy] Setting parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
 2023-07-02 10:33:33,403 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000398126
 2023-07-02 10:33:33,405 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,405 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,425 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79624
 2023-07-02 10:33:33,425 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,425 [mcmc] New sample, #103:
   Omega_m:0.3024573, b1:0.5105119
 2023-07-02 10:33:33,425 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 1.2630737449377112}
 2023-07-02 10:33:33,425 [prior] Evaluating prior at array([0.31070132, 1.26307374])
 2023-07-02 10:33:33,426 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,426 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2630737449377112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,426 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,426 [classy] Re-using computed results
 2023-07-02 10:33:33,426 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
 2023-07-02 10:33:33,426 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,426 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2630737449377112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,426 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,445 [fs_likelihood.fslikelihood] Computed log-likelihood = -2985.66
 2023-07-02 10:33:33,445 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,445 [model] Posterior to be computed for parameters {'Omega_m': 0.31653720497102433, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,445 [prior] Evaluating prior at array([0.3165372 , 0.51051188])
 2023-07-02 10:33:33,446 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,446 [model] Got input parameters: {'Omega_m': 0.31653720497102433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,446 [classy] Got parameters {'Omega_m': 0.31653720497102433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,446 [classy] Computing new state
 2023-07-02 10:33:33,446 [classy] Setting parameters: {'Omega_m': 0.31653720497102433, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77520280376365}
 2023-07-02 10:33:33,490 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00119973
 2023-07-02 10:33:33,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,491 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,511 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45759
 2023-07-02 10:33:33,511 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,511 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 0.35923669070561437}
 2023-07-02 10:33:33,511 [prior] Evaluating prior at array([0.31070132, 0.35923669])
 2023-07-02 10:33:33,511 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,511 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.35923669070561437, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,511 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,511 [classy] Re-using computed results
 2023-07-02 10:33:33,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
 2023-07-02 10:33:33,511 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.35923669070561437, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,511 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -48.309
 2023-07-02 10:33:33,531 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,532 [model] Posterior to be computed for parameters {'Omega_m': 0.3241404327454483, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,532 [prior] Evaluating prior at array([0.32414043, 0.51051188])
 2023-07-02 10:33:33,532 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,532 [model] Got input parameters: {'Omega_m': 0.3241404327454483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,532 [classy] Got parameters {'Omega_m': 0.3241404327454483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,532 [classy] Computing new state
 2023-07-02 10:33:33,532 [classy] Setting parameters: {'Omega_m': 0.3241404327454483, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.88033485696266}
 2023-07-02 10:33:33,576 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00829815
 2023-07-02 10:33:33,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,577 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,597 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.49516
 2023-07-02 10:33:33,597 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,597 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': -3.7181572723007545}
 2023-07-02 10:33:33,597 [prior] Evaluating prior at array([ 0.31070132, -3.71815727])
 2023-07-02 10:33:33,597 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:33,597 [model] Posterior to be computed for parameters {'Omega_m': 0.3192744571498333, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,597 [prior] Evaluating prior at array([0.31927446, 0.51051188])
 2023-07-02 10:33:33,598 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,598 [model] Got input parameters: {'Omega_m': 0.3192744571498333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,598 [classy] Got parameters {'Omega_m': 0.3192744571498333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,598 [classy] Computing new state
 2023-07-02 10:33:33,598 [classy] Setting parameters: {'Omega_m': 0.3192744571498333, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,642 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.45085462148103}
 2023-07-02 10:33:33,642 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,643 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00298263
 2023-07-02 10:33:33,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,643 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,663 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94939
 2023-07-02 10:33:33,663 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,663 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 0.6962168149088418}
 2023-07-02 10:33:33,663 [prior] Evaluating prior at array([0.31070132, 0.69621681])
 2023-07-02 10:33:33,663 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,663 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6962168149088418, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,663 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,663 [classy] Re-using computed results
 2023-07-02 10:33:33,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
 2023-07-02 10:33:33,664 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6962168149088418, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,664 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -111.185
 2023-07-02 10:33:33,684 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,684 [model] Posterior to be computed for parameters {'Omega_m': 0.31810829980286986, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,684 [prior] Evaluating prior at array([0.3181083 , 0.51051188])
 2023-07-02 10:33:33,684 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,684 [model] Got input parameters: {'Omega_m': 0.31810829980286986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,684 [classy] Got parameters {'Omega_m': 0.31810829980286986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,684 [classy] Computing new state
 2023-07-02 10:33:33,684 [classy] Setting parameters: {'Omega_m': 0.31810829980286986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,728 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5887336823783}
 2023-07-02 10:33:33,728 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,730 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00211521
 2023-07-02 10:33:33,730 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,730 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,750 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.19317
 2023-07-02 10:33:33,750 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,750 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 1.3688422331235148}
 2023-07-02 10:33:33,750 [prior] Evaluating prior at array([0.31070132, 1.36884223])
 2023-07-02 10:33:33,750 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,750 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3688422331235148, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,750 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,750 [classy] Re-using computed results
 2023-07-02 10:33:33,750 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
 2023-07-02 10:33:33,750 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,750 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3688422331235148, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,750 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,769 [fs_likelihood.fslikelihood] Computed log-likelihood = -4210.03
 2023-07-02 10:33:33,770 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,770 [model] Posterior to be computed for parameters {'Omega_m': 0.3156534962270178, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,770 [prior] Evaluating prior at array([0.3156535 , 0.51051188])
 2023-07-02 10:33:33,770 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,770 [model] Got input parameters: {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,770 [classy] Got parameters {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,770 [classy] Computing new state
 2023-07-02 10:33:33,770 [classy] Setting parameters: {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88044928905788}
 2023-07-02 10:33:33,814 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,816 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000813639
 2023-07-02 10:33:33,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,816 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,836 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57402
 2023-07-02 10:33:33,836 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,836 [mcmc] New sample, #104:
   Omega_m:0.3107013, b1:0.5105119
 2023-07-02 10:33:33,836 [model] Posterior to be computed for parameters {'Omega_m': 0.3156534962270178, 'b1': 0.7331327887857564}
 2023-07-02 10:33:33,836 [prior] Evaluating prior at array([0.3156535 , 0.73313279])
 2023-07-02 10:33:33,837 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,837 [model] Got input parameters: {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7331327887857564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,837 [classy] Got parameters {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,837 [classy] Re-using computed results
 2023-07-02 10:33:33,837 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88044928905788}
 2023-07-02 10:33:33,837 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,837 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7331327887857564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,837 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,857 [fs_likelihood.fslikelihood] Computed log-likelihood = -182.285
 2023-07-02 10:33:33,857 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,857 [model] Posterior to be computed for parameters {'Omega_m': 0.30148400148954707, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,857 [prior] Evaluating prior at array([0.301484  , 0.51051188])
 2023-07-02 10:33:33,857 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,857 [model] Got input parameters: {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,857 [classy] Got parameters {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,857 [classy] Computing new state
 2023-07-02 10:33:33,857 [classy] Setting parameters: {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60476320536847}
 2023-07-02 10:33:33,902 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00782998
 2023-07-02 10:33:33,903 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,903 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,923 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.26544
 2023-07-02 10:33:33,923 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,923 [mcmc] New sample, #105:
   Omega_m:0.3156535, b1:0.5105119
 2023-07-02 10:33:33,923 [model] Posterior to be computed for parameters {'Omega_m': 0.30148400148954707, 'b1': 0.6548111534981944}
 2023-07-02 10:33:33,923 [prior] Evaluating prior at array([0.301484  , 0.65481115])
 2023-07-02 10:33:33,923 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,923 [model] Got input parameters: {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6548111534981944, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,923 [classy] Got parameters {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,923 [classy] Re-using computed results
 2023-07-02 10:33:33,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60476320536847}
 2023-07-02 10:33:33,923 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:33,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6548111534981944, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,923 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:33,943 [fs_likelihood.fslikelihood] Computed log-likelihood = -49.1438
 2023-07-02 10:33:33,943 [model] Computed derived parameters: {}
 2023-07-02 10:33:33,944 [model] Posterior to be computed for parameters {'Omega_m': 0.32427377016611164, 'b1': 0.510511879507605}
 2023-07-02 10:33:33,944 [prior] Evaluating prior at array([0.32427377, 0.51051188])
 2023-07-02 10:33:33,944 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:33,944 [model] Got input parameters: {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,944 [classy] Got parameters {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:33,944 [classy] Computing new state
 2023-07-02 10:33:33,944 [classy] Setting parameters: {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:33,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86481076925278}
 2023-07-02 10:33:33,988 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:33,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00848171
 2023-07-02 10:33:33,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:33,990 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,009 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.445387
 2023-07-02 10:33:34,009 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,010 [mcmc] New sample, #106:
   Omega_m:0.301484, b1:0.5105119
 2023-07-02 10:33:34,010 [model] Posterior to be computed for parameters {'Omega_m': 0.32427377016611164, 'b1': 1.3676556980386505}
 2023-07-02 10:33:34,010 [prior] Evaluating prior at array([0.32427377, 1.3676557 ])
 2023-07-02 10:33:34,010 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,010 [model] Got input parameters: {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3676556980386505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,010 [classy] Got parameters {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,010 [classy] Re-using computed results
 2023-07-02 10:33:34,010 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86481076925278}
 2023-07-02 10:33:34,010 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,010 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3676556980386505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,010 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,029 [fs_likelihood.fslikelihood] Computed log-likelihood = -4618.11
 2023-07-02 10:33:34,030 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,030 [model] Posterior to be computed for parameters {'Omega_m': 0.3149906783622375, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,030 [prior] Evaluating prior at array([0.31499068, 0.51051188])
 2023-07-02 10:33:34,030 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,030 [model] Got input parameters: {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,030 [classy] Got parameters {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,030 [classy] Computing new state
 2023-07-02 10:33:34,030 [classy] Setting parameters: {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.95955644070628}
 2023-07-02 10:33:34,074 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000585428
 2023-07-02 10:33:34,075 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,076 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,095 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64609
 2023-07-02 10:33:34,095 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,095 [mcmc] New sample, #107:
   Omega_m:0.3242738, b1:0.5105119
 2023-07-02 10:33:34,096 [model] Posterior to be computed for parameters {'Omega_m': 0.3149906783622375, 'b1': 0.5715477115202471}
 2023-07-02 10:33:34,096 [prior] Evaluating prior at array([0.31499068, 0.57154771])
 2023-07-02 10:33:34,096 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,096 [model] Got input parameters: {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5715477115202471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,096 [classy] Got parameters {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,096 [classy] Re-using computed results
 2023-07-02 10:33:34,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.95955644070628}
 2023-07-02 10:33:34,096 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,096 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5715477115202471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,096 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,115 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.7343
 2023-07-02 10:33:34,115 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,115 [model] Posterior to be computed for parameters {'Omega_m': 0.30856513789660195, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,115 [prior] Evaluating prior at array([0.30856514, 0.51051188])
 2023-07-02 10:33:34,115 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,116 [model] Got input parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,116 [classy] Got parameters {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,116 [classy] Computing new state
 2023-07-02 10:33:34,116 [classy] Setting parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,162 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7343185492424}
 2023-07-02 10:33:34,162 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,164 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00115343
 2023-07-02 10:33:34,164 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,164 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,184 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66666
 2023-07-02 10:33:34,184 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,184 [mcmc] New sample, #108:
   Omega_m:0.3149907, b1:0.5105119
 2023-07-02 10:33:34,184 [model] Posterior to be computed for parameters {'Omega_m': 0.30856513789660195, 'b1': 1.8662402570490157}
 2023-07-02 10:33:34,184 [prior] Evaluating prior at array([0.30856514, 1.86624026])
 2023-07-02 10:33:34,184 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,184 [model] Got input parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.8662402570490157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,184 [classy] Got parameters {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,184 [classy] Re-using computed results
 2023-07-02 10:33:34,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7343185492424}
 2023-07-02 10:33:34,184 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,184 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.8662402570490157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,184 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,204 [fs_likelihood.fslikelihood] Computed log-likelihood = -14663.7
 2023-07-02 10:33:34,204 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,204 [model] Posterior to be computed for parameters {'Omega_m': 0.3272101788752867, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,204 [prior] Evaluating prior at array([0.32721018, 0.51051188])
 2023-07-02 10:33:34,204 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,204 [model] Got input parameters: {'Omega_m': 0.3272101788752867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,204 [classy] Got parameters {'Omega_m': 0.3272101788752867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,204 [classy] Computing new state
 2023-07-02 10:33:34,204 [classy] Setting parameters: {'Omega_m': 0.3272101788752867, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5243403707738}
 2023-07-02 10:33:34,249 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0130284
 2023-07-02 10:33:34,250 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,250 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.784926
 2023-07-02 10:33:34,270 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,270 [model] Posterior to be computed for parameters {'Omega_m': 0.30856513789660195, 'b1': 1.3276045244962118}
 2023-07-02 10:33:34,270 [prior] Evaluating prior at array([0.30856514, 1.32760452])
 2023-07-02 10:33:34,270 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,270 [model] Got input parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3276045244962118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,270 [classy] Got parameters {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,270 [classy] Re-using computed results
 2023-07-02 10:33:34,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7343185492424}
 2023-07-02 10:33:34,270 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,270 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3276045244962118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,270 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,291 [fs_likelihood.fslikelihood] Computed log-likelihood = -3640.44
 2023-07-02 10:33:34,291 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,291 [model] Posterior to be computed for parameters {'Omega_m': 0.3015858455640156, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,291 [prior] Evaluating prior at array([0.30158585, 0.51051188])
 2023-07-02 10:33:34,291 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,291 [model] Got input parameters: {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,291 [classy] Got parameters {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,291 [classy] Computing new state
 2023-07-02 10:33:34,291 [classy] Setting parameters: {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59211816124062}
 2023-07-02 10:33:34,336 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00768748
 2023-07-02 10:33:34,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,338 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,357 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29618
 2023-07-02 10:33:34,358 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,358 [mcmc] New sample, #109:
   Omega_m:0.3085651, b1:0.5105119
 2023-07-02 10:33:34,358 [model] Posterior to be computed for parameters {'Omega_m': 0.3015858455640156, 'b1': 0.37105933901204513}
 2023-07-02 10:33:34,358 [prior] Evaluating prior at array([0.30158585, 0.37105934])
 2023-07-02 10:33:34,358 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,358 [model] Got input parameters: {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37105933901204513, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,358 [classy] Got parameters {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,358 [classy] Re-using computed results
 2023-07-02 10:33:34,358 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59211816124062}
 2023-07-02 10:33:34,358 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,358 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37105933901204513, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,358 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,377 [fs_likelihood.fslikelihood] Computed log-likelihood = -51.8586
 2023-07-02 10:33:34,377 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,378 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,378 [prior] Evaluating prior at array([0.30640492, 0.51051188])
 2023-07-02 10:33:34,378 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,378 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,378 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,378 [classy] Computing new state
 2023-07-02 10:33:34,378 [classy] Setting parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:34,422 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,424 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00250335
 2023-07-02 10:33:34,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,424 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39746
 2023-07-02 10:33:34,444 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,444 [mcmc] New sample, #110:
   Omega_m:0.3015858, b1:0.5105119
 2023-07-02 10:33:34,444 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.7862924022000481}
 2023-07-02 10:33:34,444 [prior] Evaluating prior at array([0.30640492, 0.7862924 ])
 2023-07-02 10:33:34,444 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,444 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7862924022000481, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,445 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,445 [classy] Re-using computed results
 2023-07-02 10:33:34,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:34,445 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7862924022000481, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,445 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,464 [fs_likelihood.fslikelihood] Computed log-likelihood = -250.508
 2023-07-02 10:33:34,464 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,464 [model] Posterior to be computed for parameters {'Omega_m': 0.32403621479825445, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,464 [prior] Evaluating prior at array([0.32403621, 0.51051188])
 2023-07-02 10:33:34,465 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,465 [model] Got input parameters: {'Omega_m': 0.32403621479825445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,465 [classy] Got parameters {'Omega_m': 0.32403621479825445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,465 [classy] Computing new state
 2023-07-02 10:33:34,465 [classy] Setting parameters: {'Omega_m': 0.32403621479825445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89247512917976}
 2023-07-02 10:33:34,510 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.008156
 2023-07-02 10:33:34,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,512 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,532 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.533694
 2023-07-02 10:33:34,532 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,533 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': -0.011921170393763059}
 2023-07-02 10:33:34,533 [prior] Evaluating prior at array([ 0.30640492, -0.01192117])
 2023-07-02 10:33:34,533 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:34,533 [model] Posterior to be computed for parameters {'Omega_m': 0.2873490517865083, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,533 [prior] Evaluating prior at array([0.28734905, 0.51051188])
 2023-07-02 10:33:34,533 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,533 [model] Got input parameters: {'Omega_m': 0.2873490517865083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,533 [classy] Got parameters {'Omega_m': 0.2873490517865083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,533 [classy] Computing new state
 2023-07-02 10:33:34,533 [classy] Setting parameters: {'Omega_m': 0.2873490517865083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3972400177031}
 2023-07-02 10:33:34,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0415063
 2023-07-02 10:33:34,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,581 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,602 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.99622
 2023-07-02 10:33:34,602 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,602 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 1.2527258787121205}
 2023-07-02 10:33:34,602 [prior] Evaluating prior at array([0.30640492, 1.25272588])
 2023-07-02 10:33:34,602 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,602 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2527258787121205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,602 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,602 [classy] Re-using computed results
 2023-07-02 10:33:34,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:34,603 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2527258787121205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,603 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,623 [fs_likelihood.fslikelihood] Computed log-likelihood = -2785.61
 2023-07-02 10:33:34,623 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,623 [model] Posterior to be computed for parameters {'Omega_m': 0.2960827374482946, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,623 [prior] Evaluating prior at array([0.29608274, 0.51051188])
 2023-07-02 10:33:34,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,623 [model] Got input parameters: {'Omega_m': 0.2960827374482946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,623 [classy] Got parameters {'Omega_m': 0.2960827374482946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,623 [classy] Computing new state
 2023-07-02 10:33:34,623 [classy] Setting parameters: {'Omega_m': 0.2960827374482946, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,668 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.28090295650202}
 2023-07-02 10:33:34,668 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,670 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0173962
 2023-07-02 10:33:34,670 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,670 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,690 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.807101
 2023-07-02 10:33:34,690 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,690 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': -0.1418431505032861}
 2023-07-02 10:33:34,690 [prior] Evaluating prior at array([ 0.30640492, -0.14184315])
 2023-07-02 10:33:34,690 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:34,690 [model] Posterior to be computed for parameters {'Omega_m': 0.3214539709503879, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,690 [prior] Evaluating prior at array([0.32145397, 0.51051188])
 2023-07-02 10:33:34,690 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,690 [model] Got input parameters: {'Omega_m': 0.3214539709503879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,690 [classy] Got parameters {'Omega_m': 0.3214539709503879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,690 [classy] Computing new state
 2023-07-02 10:33:34,690 [classy] Setting parameters: {'Omega_m': 0.3214539709503879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.19436419033698}
 2023-07-02 10:33:34,734 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,736 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00502786
 2023-07-02 10:33:34,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,736 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3852
 2023-07-02 10:33:34,756 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,756 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 1.8165945394336296}
 2023-07-02 10:33:34,756 [prior] Evaluating prior at array([0.30640492, 1.81659454])
 2023-07-02 10:33:34,757 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,757 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.8165945394336296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,757 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,757 [classy] Re-using computed results
 2023-07-02 10:33:34,757 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:34,757 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,757 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.8165945394336296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,757 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,776 [fs_likelihood.fslikelihood] Computed log-likelihood = -13009
 2023-07-02 10:33:34,776 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,776 [model] Posterior to be computed for parameters {'Omega_m': 0.3028093078409774, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,776 [prior] Evaluating prior at array([0.30280931, 0.51051188])
 2023-07-02 10:33:34,776 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,776 [model] Got input parameters: {'Omega_m': 0.3028093078409774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,776 [classy] Got parameters {'Omega_m': 0.3028093078409774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,777 [classy] Computing new state
 2023-07-02 10:33:34,777 [classy] Setting parameters: {'Omega_m': 0.3028093078409774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,820 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.44049426996006}
 2023-07-02 10:33:34,820 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,822 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00608301
 2023-07-02 10:33:34,822 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,822 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64126
 2023-07-02 10:33:34,843 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,843 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.265638383221054}
 2023-07-02 10:33:34,843 [prior] Evaluating prior at array([0.30640492, 0.26563838])
 2023-07-02 10:33:34,843 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,843 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.265638383221054, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,843 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,843 [classy] Re-using computed results
 2023-07-02 10:33:34,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:34,843 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,843 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.265638383221054, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,843 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,863 [fs_likelihood.fslikelihood] Computed log-likelihood = -126.743
 2023-07-02 10:33:34,863 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,863 [model] Posterior to be computed for parameters {'Omega_m': 0.2886325961293404, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,863 [prior] Evaluating prior at array([0.2886326 , 0.51051188])
 2023-07-02 10:33:34,863 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,863 [model] Got input parameters: {'Omega_m': 0.2886325961293404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,863 [classy] Got parameters {'Omega_m': 0.2886325961293404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,863 [classy] Computing new state
 2023-07-02 10:33:34,863 [classy] Setting parameters: {'Omega_m': 0.2886325961293404, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,907 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.23135530095783}
 2023-07-02 10:33:34,907 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,909 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0372716
 2023-07-02 10:33:34,909 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,909 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,928 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.09124
 2023-07-02 10:33:34,928 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,928 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.7013760088753697}
 2023-07-02 10:33:34,928 [prior] Evaluating prior at array([0.30640492, 0.70137601])
 2023-07-02 10:33:34,929 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,929 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7013760088753697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,929 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,929 [classy] Re-using computed results
 2023-07-02 10:33:34,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:34,929 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:34,929 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7013760088753697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,929 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:34,949 [fs_likelihood.fslikelihood] Computed log-likelihood = -107.528
 2023-07-02 10:33:34,949 [model] Computed derived parameters: {}
 2023-07-02 10:33:34,950 [model] Posterior to be computed for parameters {'Omega_m': 0.2958630388693177, 'b1': 0.510511879507605}
 2023-07-02 10:33:34,950 [prior] Evaluating prior at array([0.29586304, 0.51051188])
 2023-07-02 10:33:34,950 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:34,950 [model] Got input parameters: {'Omega_m': 0.2958630388693177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,950 [classy] Got parameters {'Omega_m': 0.2958630388693177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:34,950 [classy] Computing new state
 2023-07-02 10:33:34,950 [classy] Setting parameters: {'Omega_m': 0.2958630388693177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:34,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.30863171003898}
 2023-07-02 10:33:34,994 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:34,996 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0178699
 2023-07-02 10:33:34,996 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:34,996 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,015 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.909787
 2023-07-02 10:33:35,015 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,016 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 2.189496972879572}
 2023-07-02 10:33:35,016 [prior] Evaluating prior at array([0.30640492, 2.18949697])
 2023-07-02 10:33:35,016 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,016 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.189496972879572, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,016 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,016 [classy] Re-using computed results
 2023-07-02 10:33:35,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
 2023-07-02 10:33:35,016 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,016 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.189496972879572, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,016 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,036 [fs_likelihood.fslikelihood] Computed log-likelihood = -27166.8
 2023-07-02 10:33:35,036 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,036 [model] Posterior to be computed for parameters {'Omega_m': 0.31210423397057946, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,036 [prior] Evaluating prior at array([0.31210423, 0.51051188])
 2023-07-02 10:33:35,036 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,036 [model] Got input parameters: {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,036 [classy] Got parameters {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,036 [classy] Computing new state
 2023-07-02 10:33:35,036 [classy] Setting parameters: {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,080 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.30584766721276}
 2023-07-02 10:33:35,080 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,082 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000211219
 2023-07-02 10:33:35,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,082 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80742
 2023-07-02 10:33:35,102 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,102 [mcmc] New sample, #111:
   Omega_m:0.3064049, b1:0.5105119
 2023-07-02 10:33:35,102 [model] Posterior to be computed for parameters {'Omega_m': 0.31210423397057946, 'b1': 1.3012550945458492}
 2023-07-02 10:33:35,102 [prior] Evaluating prior at array([0.31210423, 1.30125509])
 2023-07-02 10:33:35,102 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,102 [model] Got input parameters: {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3012550945458492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,102 [classy] Got parameters {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,102 [classy] Re-using computed results
 2023-07-02 10:33:35,102 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.30584766721276}
 2023-07-02 10:33:35,102 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3012550945458492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,103 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,125 [fs_likelihood.fslikelihood] Computed log-likelihood = -3430.64
 2023-07-02 10:33:35,125 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,125 [prior] Evaluating prior at array([0.30992448, 0.51051188])
 2023-07-02 10:33:35,125 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,125 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,125 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,126 [classy] Computing new state
 2023-07-02 10:33:35,126 [classy] Setting parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
 2023-07-02 10:33:35,171 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000606703
 2023-07-02 10:33:35,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,173 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,192 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76484
 2023-07-02 10:33:35,192 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,192 [mcmc] New sample, #112:
   Omega_m:0.3121042, b1:0.5105119
 2023-07-02 10:33:35,193 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.9563985836392042}
 2023-07-02 10:33:35,193 [prior] Evaluating prior at array([0.30992448, 0.95639858])
 2023-07-02 10:33:35,193 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,193 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9563985836392042, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,193 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,193 [classy] Re-using computed results
 2023-07-02 10:33:35,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
 2023-07-02 10:33:35,193 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,193 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9563985836392042, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,193 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,213 [fs_likelihood.fslikelihood] Computed log-likelihood = -809.324
 2023-07-02 10:33:35,213 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,213 [model] Posterior to be computed for parameters {'Omega_m': 0.2631472327268247, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,213 [prior] Evaluating prior at array([0.26314723, 0.51051188])
 2023-07-02 10:33:35,213 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,213 [model] Got input parameters: {'Omega_m': 0.2631472327268247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,213 [classy] Got parameters {'Omega_m': 0.2631472327268247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,213 [classy] Computing new state
 2023-07-02 10:33:35,213 [classy] Setting parameters: {'Omega_m': 0.2631472327268247, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.65060781565}
 2023-07-02 10:33:35,257 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,259 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.170018
 2023-07-02 10:33:35,259 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,259 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,278 [fs_likelihood.fslikelihood] Computed log-likelihood = -32.2427
 2023-07-02 10:33:35,279 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,279 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.849369882136066}
 2023-07-02 10:33:35,279 [prior] Evaluating prior at array([0.30992448, 0.84936988])
 2023-07-02 10:33:35,279 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,279 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.849369882136066, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,279 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,279 [classy] Re-using computed results
 2023-07-02 10:33:35,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
 2023-07-02 10:33:35,279 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,279 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.849369882136066, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,279 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,299 [fs_likelihood.fslikelihood] Computed log-likelihood = -424.693
 2023-07-02 10:33:35,299 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,299 [model] Posterior to be computed for parameters {'Omega_m': 0.283507249741276, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,299 [prior] Evaluating prior at array([0.28350725, 0.51051188])
 2023-07-02 10:33:35,299 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,299 [model] Got input parameters: {'Omega_m': 0.283507249741276, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,299 [classy] Got parameters {'Omega_m': 0.283507249741276, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,299 [classy] Computing new state
 2023-07-02 10:33:35,299 [classy] Setting parameters: {'Omega_m': 0.283507249741276, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.89765195794948}
 2023-07-02 10:33:35,343 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0556552
 2023-07-02 10:33:35,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,345 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,365 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.99809
 2023-07-02 10:33:35,365 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,365 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 1.3533112392523106}
 2023-07-02 10:33:35,365 [prior] Evaluating prior at array([0.30992448, 1.35331124])
 2023-07-02 10:33:35,366 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,366 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3533112392523106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,366 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,366 [classy] Re-using computed results
 2023-07-02 10:33:35,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
 2023-07-02 10:33:35,366 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,366 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3533112392523106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,366 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,385 [fs_likelihood.fslikelihood] Computed log-likelihood = -3989.43
 2023-07-02 10:33:35,385 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,385 [model] Posterior to be computed for parameters {'Omega_m': 0.32716443271861545, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,385 [prior] Evaluating prior at array([0.32716443, 0.51051188])
 2023-07-02 10:33:35,385 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,386 [model] Got input parameters: {'Omega_m': 0.32716443271861545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,386 [classy] Got parameters {'Omega_m': 0.32716443271861545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,386 [classy] Computing new state
 2023-07-02 10:33:35,386 [classy] Setting parameters: {'Omega_m': 0.32716443271861545, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,430 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.52962483448624}
 2023-07-02 10:33:35,430 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129502
 2023-07-02 10:33:35,432 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,432 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,451 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.76379
 2023-07-02 10:33:35,451 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,452 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.9022045435649878}
 2023-07-02 10:33:35,452 [prior] Evaluating prior at array([0.30992448, 0.90220454])
 2023-07-02 10:33:35,452 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,452 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9022045435649878, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,452 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,452 [classy] Re-using computed results
 2023-07-02 10:33:35,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
 2023-07-02 10:33:35,452 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9022045435649878, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,452 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -595.351
 2023-07-02 10:33:35,471 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,472 [model] Posterior to be computed for parameters {'Omega_m': 0.31314118591289486, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,472 [prior] Evaluating prior at array([0.31314119, 0.51051188])
 2023-07-02 10:33:35,472 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,472 [model] Got input parameters: {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,472 [classy] Got parameters {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,472 [classy] Computing new state
 2023-07-02 10:33:35,472 [classy] Setting parameters: {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18111680186226}
 2023-07-02 10:33:35,516 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,517 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00022883
 2023-07-02 10:33:35,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,517 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,537 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77801
 2023-07-02 10:33:35,537 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,537 [mcmc] New sample, #113:
   Omega_m:0.3099245, b1:0.5105119
 2023-07-02 10:33:35,537 [model] Posterior to be computed for parameters {'Omega_m': 0.31314118591289486, 'b1': -1.2613782238027467}
 2023-07-02 10:33:35,537 [prior] Evaluating prior at array([ 0.31314119, -1.26137822])
 2023-07-02 10:33:35,537 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:35,537 [model] Posterior to be computed for parameters {'Omega_m': 0.34673835194328295, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,537 [prior] Evaluating prior at array([0.34673835, 0.51051188])
 2023-07-02 10:33:35,537 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,538 [model] Got input parameters: {'Omega_m': 0.34673835194328295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,538 [classy] Got parameters {'Omega_m': 0.34673835194328295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,538 [classy] Computing new state
 2023-07-02 10:33:35,538 [classy] Setting parameters: {'Omega_m': 0.34673835194328295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.32802129322866}
 2023-07-02 10:33:35,582 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0664531
 2023-07-02 10:33:35,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,583 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,603 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.498
 2023-07-02 10:33:35,603 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,603 [model] Posterior to be computed for parameters {'Omega_m': 0.31314118591289486, 'b1': 0.4270051335449099}
 2023-07-02 10:33:35,603 [prior] Evaluating prior at array([0.31314119, 0.42700513])
 2023-07-02 10:33:35,603 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,603 [model] Got input parameters: {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4270051335449099, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,603 [classy] Got parameters {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,603 [classy] Re-using computed results
 2023-07-02 10:33:35,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18111680186226}
 2023-07-02 10:33:35,604 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,604 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4270051335449099, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,604 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,623 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.751
 2023-07-02 10:33:35,623 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,623 [model] Posterior to be computed for parameters {'Omega_m': 0.3199550765255515, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,623 [prior] Evaluating prior at array([0.31995508, 0.51051188])
 2023-07-02 10:33:35,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,623 [model] Got input parameters: {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,623 [classy] Got parameters {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,623 [classy] Computing new state
 2023-07-02 10:33:35,623 [classy] Setting parameters: {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.37059227133813}
 2023-07-02 10:33:35,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00356222
 2023-07-02 10:33:35,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,669 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,689 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.78839
 2023-07-02 10:33:35,689 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,689 [mcmc] New sample, #114:
   Omega_m:0.3131412, b1:0.5105119
 2023-07-02 10:33:35,689 [model] Posterior to be computed for parameters {'Omega_m': 0.3199550765255515, 'b1': 0.6008238436729927}
 2023-07-02 10:33:35,689 [prior] Evaluating prior at array([0.31995508, 0.60082384])
 2023-07-02 10:33:35,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,689 [model] Got input parameters: {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6008238436729927, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,689 [classy] Got parameters {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,689 [classy] Re-using computed results
 2023-07-02 10:33:35,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.37059227133813}
 2023-07-02 10:33:35,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6008238436729927, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,709 [fs_likelihood.fslikelihood] Computed log-likelihood = -33.3702
 2023-07-02 10:33:35,709 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,709 [model] Posterior to be computed for parameters {'Omega_m': 0.3184991828302559, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,709 [prior] Evaluating prior at array([0.31849918, 0.51051188])
 2023-07-02 10:33:35,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,710 [model] Got input parameters: {'Omega_m': 0.3184991828302559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,710 [classy] Got parameters {'Omega_m': 0.3184991828302559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,710 [classy] Computing new state
 2023-07-02 10:33:35,710 [classy] Setting parameters: {'Omega_m': 0.3184991828302559, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54246953078496}
 2023-07-02 10:33:35,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00238819
 2023-07-02 10:33:35,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,755 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,775 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11597
 2023-07-02 10:33:35,775 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,775 [mcmc] New sample, #115:
   Omega_m:0.3199551, b1:0.5105119
 2023-07-02 10:33:35,775 [model] Posterior to be computed for parameters {'Omega_m': 0.3184991828302559, 'b1': -0.3297785535581541}
 2023-07-02 10:33:35,775 [prior] Evaluating prior at array([ 0.31849918, -0.32977855])
 2023-07-02 10:33:35,775 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:35,775 [model] Posterior to be computed for parameters {'Omega_m': 0.31022168957578045, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,775 [prior] Evaluating prior at array([0.31022169, 0.51051188])
 2023-07-02 10:33:35,775 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,776 [model] Got input parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,776 [classy] Got parameters {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,776 [classy] Computing new state
 2023-07-02 10:33:35,776 [classy] Setting parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53322897143858}
 2023-07-02 10:33:35,819 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000518019
 2023-07-02 10:33:35,821 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,821 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,841 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77897
 2023-07-02 10:33:35,841 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,841 [mcmc] New sample, #116:
   Omega_m:0.3184992, b1:0.5105119
 2023-07-02 10:33:35,841 [model] Posterior to be computed for parameters {'Omega_m': 0.31022168957578045, 'b1': 2.3113839673775423}
 2023-07-02 10:33:35,841 [prior] Evaluating prior at array([0.31022169, 2.31138397])
 2023-07-02 10:33:35,841 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,841 [model] Got input parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.3113839673775423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,841 [classy] Got parameters {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,841 [classy] Re-using computed results
 2023-07-02 10:33:35,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53322897143858}
 2023-07-02 10:33:35,841 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.3113839673775423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,842 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,861 [fs_likelihood.fslikelihood] Computed log-likelihood = -34233.8
 2023-07-02 10:33:35,862 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,862 [model] Posterior to be computed for parameters {'Omega_m': 0.2991125986817331, 'b1': 0.510511879507605}
 2023-07-02 10:33:35,862 [prior] Evaluating prior at array([0.2991126 , 0.51051188])
 2023-07-02 10:33:35,862 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,862 [model] Got input parameters: {'Omega_m': 0.2991125986817331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,862 [classy] Got parameters {'Omega_m': 0.2991125986817331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,862 [classy] Computing new state
 2023-07-02 10:33:35,862 [classy] Setting parameters: {'Omega_m': 0.2991125986817331, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.90029665267363}
 2023-07-02 10:33:35,906 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,908 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0115417
 2023-07-02 10:33:35,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,908 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,927 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.462469
 2023-07-02 10:33:35,927 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,927 [model] Posterior to be computed for parameters {'Omega_m': 0.31022168957578045, 'b1': 0.5081695971600135}
 2023-07-02 10:33:35,927 [prior] Evaluating prior at array([0.31022169, 0.5081696 ])
 2023-07-02 10:33:35,928 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,928 [model] Got input parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,928 [classy] Got parameters {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,928 [classy] Re-using computed results
 2023-07-02 10:33:35,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53322897143858}
 2023-07-02 10:33:35,928 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:35,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,928 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:35,947 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78295
 2023-07-02 10:33:35,948 [model] Computed derived parameters: {}
 2023-07-02 10:33:35,948 [mcmc] New sample, #117:
   Omega_m:0.3102217, b1:0.5105119
 2023-07-02 10:33:35,948 [model] Posterior to be computed for parameters {'Omega_m': 0.304926998135763, 'b1': 0.5081695971600135}
 2023-07-02 10:33:35,948 [prior] Evaluating prior at array([0.304927 , 0.5081696])
 2023-07-02 10:33:35,948 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:35,948 [model] Got input parameters: {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,948 [classy] Got parameters {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:35,948 [classy] Computing new state
 2023-07-02 10:33:35,948 [classy] Setting parameters: {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:35,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.17931935125597}
 2023-07-02 10:33:35,992 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:35,994 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00377134
 2023-07-02 10:33:35,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:35,994 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,014 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.01857
 2023-07-02 10:33:36,014 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,014 [mcmc] New sample, #118:
   Omega_m:0.3102217, b1:0.5081696
 2023-07-02 10:33:36,014 [model] Posterior to be computed for parameters {'Omega_m': 0.304926998135763, 'b1': 1.060201838310671}
 2023-07-02 10:33:36,014 [prior] Evaluating prior at array([0.304927  , 1.06020184])
 2023-07-02 10:33:36,015 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,015 [model] Got input parameters: {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.060201838310671, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,015 [classy] Got parameters {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,015 [classy] Re-using computed results
 2023-07-02 10:33:36,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.17931935125597}
 2023-07-02 10:33:36,015 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,015 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.060201838310671, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,015 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,034 [fs_likelihood.fslikelihood] Computed log-likelihood = -1281.68
 2023-07-02 10:33:36,034 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,034 [model] Posterior to be computed for parameters {'Omega_m': 0.3008093573410816, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,034 [prior] Evaluating prior at array([0.30080936, 0.5081696 ])
 2023-07-02 10:33:36,035 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,035 [model] Got input parameters: {'Omega_m': 0.3008093573410816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,035 [classy] Got parameters {'Omega_m': 0.3008093573410816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,035 [classy] Computing new state
 2023-07-02 10:33:36,035 [classy] Setting parameters: {'Omega_m': 0.3008093573410816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6886239463967}
 2023-07-02 10:33:36,079 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,081 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0088089
 2023-07-02 10:33:36,081 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,081 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,100 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.850393
 2023-07-02 10:33:36,100 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,100 [mcmc] New sample, #119:
   Omega_m:0.304927, b1:0.5081696
 2023-07-02 10:33:36,101 [model] Posterior to be computed for parameters {'Omega_m': 0.3008093573410816, 'b1': -0.503101310011393}
 2023-07-02 10:33:36,101 [prior] Evaluating prior at array([ 0.30080936, -0.50310131])
 2023-07-02 10:33:36,101 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:36,101 [model] Posterior to be computed for parameters {'Omega_m': 0.3055764962815365, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,101 [prior] Evaluating prior at array([0.3055765, 0.5081696])
 2023-07-02 10:33:36,101 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,101 [model] Got input parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,101 [classy] Got parameters {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,101 [classy] Computing new state
 2023-07-02 10:33:36,101 [classy] Setting parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.0995371775601}
 2023-07-02 10:33:36,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0031794
 2023-07-02 10:33:36,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,149 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15699
 2023-07-02 10:33:36,169 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,169 [mcmc] New sample, #120:
   Omega_m:0.3008094, b1:0.5081696
 2023-07-02 10:33:36,169 [model] Posterior to be computed for parameters {'Omega_m': 0.3055764962815365, 'b1': 1.2054939901200719}
 2023-07-02 10:33:36,170 [prior] Evaluating prior at array([0.3055765 , 1.20549399])
 2023-07-02 10:33:36,170 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,170 [model] Got input parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2054939901200719, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,170 [classy] Got parameters {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,170 [classy] Re-using computed results
 2023-07-02 10:33:36,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.0995371775601}
 2023-07-02 10:33:36,170 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,170 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2054939901200719, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,170 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,189 [fs_likelihood.fslikelihood] Computed log-likelihood = -2334.48
 2023-07-02 10:33:36,189 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,189 [model] Posterior to be computed for parameters {'Omega_m': 0.3260408447717924, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,189 [prior] Evaluating prior at array([0.32604084, 0.5081696 ])
 2023-07-02 10:33:36,190 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,190 [model] Got input parameters: {'Omega_m': 0.3260408447717924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,190 [classy] Got parameters {'Omega_m': 0.3260408447717924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,190 [classy] Computing new state
 2023-07-02 10:33:36,190 [classy] Setting parameters: {'Omega_m': 0.3260408447717924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,233 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.65959264316893}
 2023-07-02 10:33:36,233 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,235 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.011103
 2023-07-02 10:33:36,235 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,235 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.122503
 2023-07-02 10:33:36,255 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,255 [model] Posterior to be computed for parameters {'Omega_m': 0.3055764962815365, 'b1': 1.079658733028018}
 2023-07-02 10:33:36,255 [prior] Evaluating prior at array([0.3055765 , 1.07965873])
 2023-07-02 10:33:36,255 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,255 [model] Got input parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.079658733028018, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,255 [classy] Got parameters {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,255 [classy] Re-using computed results
 2023-07-02 10:33:36,255 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.0995371775601}
 2023-07-02 10:33:36,255 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.079658733028018, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,255 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,275 [fs_likelihood.fslikelihood] Computed log-likelihood = -1406.53
 2023-07-02 10:33:36,275 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,275 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,275 [prior] Evaluating prior at array([0.31247176, 0.5081696 ])
 2023-07-02 10:33:36,275 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,275 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,276 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,276 [classy] Computing new state
 2023-07-02 10:33:36,276 [classy] Setting parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,319 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
 2023-07-02 10:33:36,319 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,321 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202381
 2023-07-02 10:33:36,321 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,321 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,342 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8565
 2023-07-02 10:33:36,342 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,342 [mcmc] New sample, #121:
   Omega_m:0.3055765, b1:0.5081696
 2023-07-02 10:33:36,342 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 0.7720336305758482}
 2023-07-02 10:33:36,342 [prior] Evaluating prior at array([0.31247176, 0.77203363])
 2023-07-02 10:33:36,342 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,342 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7720336305758482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,342 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,342 [classy] Re-using computed results
 2023-07-02 10:33:36,342 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
 2023-07-02 10:33:36,342 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7720336305758482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,342 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,363 [fs_likelihood.fslikelihood] Computed log-likelihood = -245.103
 2023-07-02 10:33:36,363 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,363 [model] Posterior to be computed for parameters {'Omega_m': 0.29155448467519973, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,363 [prior] Evaluating prior at array([0.29155448, 0.5081696 ])
 2023-07-02 10:33:36,363 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,363 [model] Got input parameters: {'Omega_m': 0.29155448467519973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,363 [classy] Got parameters {'Omega_m': 0.29155448467519973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,363 [classy] Computing new state
 2023-07-02 10:33:36,363 [classy] Setting parameters: {'Omega_m': 0.29155448467519973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.85609140897708}
 2023-07-02 10:33:36,407 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,408 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0285302
 2023-07-02 10:33:36,408 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,408 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,428 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.60724
 2023-07-02 10:33:36,428 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,428 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 1.7393984440137882}
 2023-07-02 10:33:36,428 [prior] Evaluating prior at array([0.31247176, 1.73939844])
 2023-07-02 10:33:36,429 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,429 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7393984440137882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,429 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,429 [classy] Re-using computed results
 2023-07-02 10:33:36,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
 2023-07-02 10:33:36,429 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,429 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7393984440137882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,429 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,448 [fs_likelihood.fslikelihood] Computed log-likelihood = -11340.5
 2023-07-02 10:33:36,448 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,448 [model] Posterior to be computed for parameters {'Omega_m': 0.29316465552280807, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,448 [prior] Evaluating prior at array([0.29316466, 0.5081696 ])
 2023-07-02 10:33:36,448 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,448 [model] Got input parameters: {'Omega_m': 0.29316465552280807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,448 [classy] Got parameters {'Omega_m': 0.29316465552280807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,448 [classy] Computing new state
 2023-07-02 10:33:36,449 [classy] Setting parameters: {'Omega_m': 0.29316465552280807, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,493 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.65068292008283}
 2023-07-02 10:33:36,493 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,494 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0242389
 2023-07-02 10:33:36,495 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,495 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,514 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.64948
 2023-07-02 10:33:36,514 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,514 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 0.33105147055559525}
 2023-07-02 10:33:36,514 [prior] Evaluating prior at array([0.31247176, 0.33105147])
 2023-07-02 10:33:36,515 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,515 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.33105147055559525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,515 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,515 [classy] Re-using computed results
 2023-07-02 10:33:36,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
 2023-07-02 10:33:36,515 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,515 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.33105147055559525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,515 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,534 [fs_likelihood.fslikelihood] Computed log-likelihood = -65.1219
 2023-07-02 10:33:36,534 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,535 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,535 [prior] Evaluating prior at array([0.30840967, 0.5081696 ])
 2023-07-02 10:33:36,535 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,535 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,535 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,535 [classy] Computing new state
 2023-07-02 10:33:36,535 [classy] Setting parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
 2023-07-02 10:33:36,580 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0012308
 2023-07-02 10:33:36,582 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,582 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,601 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61477
 2023-07-02 10:33:36,601 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,601 [mcmc] New sample, #122:
   Omega_m:0.3124718, b1:0.5081696
 2023-07-02 10:33:36,601 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 1.7275159147977868}
 2023-07-02 10:33:36,601 [prior] Evaluating prior at array([0.30840967, 1.72751591])
 2023-07-02 10:33:36,602 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,602 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7275159147977868, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,602 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,602 [classy] Re-using computed results
 2023-07-02 10:33:36,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
 2023-07-02 10:33:36,602 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7275159147977868, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,602 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -10768.1
 2023-07-02 10:33:36,622 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,623 [model] Posterior to be computed for parameters {'Omega_m': 0.30446167646349287, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,623 [prior] Evaluating prior at array([0.30446168, 0.5081696 ])
 2023-07-02 10:33:36,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,623 [model] Got input parameters: {'Omega_m': 0.30446167646349287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,623 [classy] Got parameters {'Omega_m': 0.30446167646349287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,623 [classy] Computing new state
 2023-07-02 10:33:36,623 [classy] Setting parameters: {'Omega_m': 0.30446167646349287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.23657293161716}
 2023-07-02 10:33:36,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00422911
 2023-07-02 10:33:36,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,669 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,688 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91171
 2023-07-02 10:33:36,689 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,689 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 0.015378842072254428}
 2023-07-02 10:33:36,689 [prior] Evaluating prior at array([0.30840967, 0.01537884])
 2023-07-02 10:33:36,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,689 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.015378842072254428, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,689 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,689 [classy] Re-using computed results
 2023-07-02 10:33:36,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
 2023-07-02 10:33:36,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.015378842072254428, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -386.368
 2023-07-02 10:33:36,708 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,708 [model] Posterior to be computed for parameters {'Omega_m': 0.3018960180983903, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,709 [prior] Evaluating prior at array([0.30189602, 0.5081696 ])
 2023-07-02 10:33:36,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,709 [model] Got input parameters: {'Omega_m': 0.3018960180983903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,709 [classy] Got parameters {'Omega_m': 0.3018960180983903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,709 [classy] Computing new state
 2023-07-02 10:33:36,709 [classy] Setting parameters: {'Omega_m': 0.3018960180983903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.55362652446505}
 2023-07-02 10:33:36,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00726192
 2023-07-02 10:33:36,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,754 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,775 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20743
 2023-07-02 10:33:36,775 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,775 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': -0.29249185115331444}
 2023-07-02 10:33:36,775 [prior] Evaluating prior at array([ 0.30840967, -0.29249185])
 2023-07-02 10:33:36,775 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:36,776 [model] Posterior to be computed for parameters {'Omega_m': 0.2946358412335537, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,776 [prior] Evaluating prior at array([0.29463584, 0.5081696 ])
 2023-07-02 10:33:36,776 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,776 [model] Got input parameters: {'Omega_m': 0.2946358412335537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,776 [classy] Got parameters {'Omega_m': 0.2946358412335537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,776 [classy] Computing new state
 2023-07-02 10:33:36,776 [classy] Setting parameters: {'Omega_m': 0.2946358412335537, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,820 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.46385592365976}
 2023-07-02 10:33:36,820 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,822 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0206397
 2023-07-02 10:33:36,822 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,822 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,841 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.8415
 2023-07-02 10:33:36,841 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,842 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 1.6850664810807543}
 2023-07-02 10:33:36,842 [prior] Evaluating prior at array([0.30840967, 1.68506648])
 2023-07-02 10:33:36,842 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,842 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6850664810807543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,842 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,842 [classy] Re-using computed results
 2023-07-02 10:33:36,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
 2023-07-02 10:33:36,842 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:36,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6850664810807543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,842 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,862 [fs_likelihood.fslikelihood] Computed log-likelihood = -9743.94
 2023-07-02 10:33:36,862 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,862 [model] Posterior to be computed for parameters {'Omega_m': 0.3288175442948318, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,862 [prior] Evaluating prior at array([0.32881754, 0.5081696 ])
 2023-07-02 10:33:36,862 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,862 [model] Got input parameters: {'Omega_m': 0.3288175442948318, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,862 [classy] Got parameters {'Omega_m': 0.3288175442948318, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,862 [classy] Computing new state
 2023-07-02 10:33:36,862 [classy] Setting parameters: {'Omega_m': 0.3288175442948318, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3391297745185}
 2023-07-02 10:33:36,906 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,908 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159204
 2023-07-02 10:33:36,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,908 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,928 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10883
 2023-07-02 10:33:36,928 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,929 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': -0.05116341311026684}
 2023-07-02 10:33:36,929 [prior] Evaluating prior at array([ 0.30840967, -0.05116341])
 2023-07-02 10:33:36,929 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:36,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,929 [prior] Evaluating prior at array([0.32328998, 0.5081696 ])
 2023-07-02 10:33:36,929 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,929 [model] Got input parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,929 [classy] Got parameters {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,929 [classy] Computing new state
 2023-07-02 10:33:36,929 [classy] Setting parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:36,973 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97949359718532}
 2023-07-02 10:33:36,973 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:36,975 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00717428
 2023-07-02 10:33:36,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,975 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:36,994 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.11729
 2023-07-02 10:33:36,994 [model] Computed derived parameters: {}
 2023-07-02 10:33:36,994 [mcmc] New sample, #123:
   Omega_m:0.3084097, b1:0.5081696
 2023-07-02 10:33:36,995 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': -0.44932249114335177}
 2023-07-02 10:33:36,995 [prior] Evaluating prior at array([ 0.32328998, -0.44932249])
 2023-07-02 10:33:36,995 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:36,995 [model] Posterior to be computed for parameters {'Omega_m': 0.3311757114228575, 'b1': 0.5081695971600135}
 2023-07-02 10:33:36,995 [prior] Evaluating prior at array([0.33117571, 0.5081696 ])
 2023-07-02 10:33:36,995 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:36,995 [model] Got input parameters: {'Omega_m': 0.3311757114228575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:36,995 [classy] Got parameters {'Omega_m': 0.3311757114228575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:36,995 [classy] Computing new state
 2023-07-02 10:33:36,995 [classy] Setting parameters: {'Omega_m': 0.3311757114228575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0689004795194}
 2023-07-02 10:33:37,042 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,044 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0206697
 2023-07-02 10:33:37,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,044 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,063 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.33382
 2023-07-02 10:33:37,063 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,063 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': 0.24520817249958016}
 2023-07-02 10:33:37,063 [prior] Evaluating prior at array([0.32328998, 0.24520817])
 2023-07-02 10:33:37,064 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,064 [model] Got input parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24520817249958016, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,064 [classy] Got parameters {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,064 [classy] Re-using computed results
 2023-07-02 10:33:37,064 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97949359718532}
 2023-07-02 10:33:37,064 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,064 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24520817249958016, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,064 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,084 [fs_likelihood.fslikelihood] Computed log-likelihood = -119.381
 2023-07-02 10:33:37,084 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,084 [model] Posterior to be computed for parameters {'Omega_m': 0.33501843113753715, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,084 [prior] Evaluating prior at array([0.33501843, 0.5081696 ])
 2023-07-02 10:33:37,084 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,084 [model] Got input parameters: {'Omega_m': 0.33501843113753715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,084 [classy] Got parameters {'Omega_m': 0.33501843113753715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,084 [classy] Computing new state
 2023-07-02 10:33:37,084 [classy] Setting parameters: {'Omega_m': 0.33501843113753715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,129 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.6322592423256}
 2023-07-02 10:33:37,129 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,131 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0296771
 2023-07-02 10:33:37,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,131 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,152 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.68271
 2023-07-02 10:33:37,152 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,152 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': 1.3789346849233155}
 2023-07-02 10:33:37,152 [prior] Evaluating prior at array([0.32328998, 1.37893468])
 2023-07-02 10:33:37,152 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,152 [model] Got input parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3789346849233155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,152 [classy] Got parameters {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,152 [classy] Re-using computed results
 2023-07-02 10:33:37,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97949359718532}
 2023-07-02 10:33:37,152 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3789346849233155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,152 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,173 [fs_likelihood.fslikelihood] Computed log-likelihood = -4744.79
 2023-07-02 10:33:37,173 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,173 [model] Posterior to be computed for parameters {'Omega_m': 0.32697971639747914, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,173 [prior] Evaluating prior at array([0.32697972, 0.5081696 ])
 2023-07-02 10:33:37,173 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,173 [model] Got input parameters: {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,173 [classy] Got parameters {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,173 [classy] Computing new state
 2023-07-02 10:33:37,173 [classy] Setting parameters: {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.55096424676256}
 2023-07-02 10:33:37,217 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,218 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0126369
 2023-07-02 10:33:37,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,218 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,238 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.2683
 2023-07-02 10:33:37,238 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,238 [mcmc] New sample, #124:
   Omega_m:0.32329, b1:0.5081696
 2023-07-02 10:33:37,238 [model] Posterior to be computed for parameters {'Omega_m': 0.32697971639747914, 'b1': -0.5229581498477165}
 2023-07-02 10:33:37,238 [prior] Evaluating prior at array([ 0.32697972, -0.52295815])
 2023-07-02 10:33:37,239 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:37,239 [model] Posterior to be computed for parameters {'Omega_m': 0.33430723245825184, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,239 [prior] Evaluating prior at array([0.33430723, 0.5081696 ])
 2023-07-02 10:33:37,239 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,239 [model] Got input parameters: {'Omega_m': 0.33430723245825184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,239 [classy] Got parameters {'Omega_m': 0.33430723245825184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,239 [classy] Computing new state
 2023-07-02 10:33:37,239 [classy] Setting parameters: {'Omega_m': 0.33430723245825184, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7127290004227}
 2023-07-02 10:33:37,283 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,285 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0278931
 2023-07-02 10:33:37,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,285 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.21501
 2023-07-02 10:33:37,304 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,304 [model] Posterior to be computed for parameters {'Omega_m': 0.32697971639747914, 'b1': 0.12312667819051804}
 2023-07-02 10:33:37,304 [prior] Evaluating prior at array([0.32697972, 0.12312668])
 2023-07-02 10:33:37,305 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,305 [model] Got input parameters: {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.12312667819051804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,305 [classy] Got parameters {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,305 [classy] Re-using computed results
 2023-07-02 10:33:37,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.55096424676256}
 2023-07-02 10:33:37,305 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,305 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.12312667819051804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,305 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,324 [fs_likelihood.fslikelihood] Computed log-likelihood = -234.415
 2023-07-02 10:33:37,324 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,324 [model] Posterior to be computed for parameters {'Omega_m': 0.32193156491818914, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,325 [prior] Evaluating prior at array([0.32193156, 0.5081696 ])
 2023-07-02 10:33:37,325 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,325 [model] Got input parameters: {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,325 [classy] Got parameters {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,325 [classy] Computing new state
 2023-07-02 10:33:37,325 [classy] Setting parameters: {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,369 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13836508112396}
 2023-07-02 10:33:37,369 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,371 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00554919
 2023-07-02 10:33:37,371 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,371 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,390 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.52591
 2023-07-02 10:33:37,391 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,391 [mcmc] New sample, #125:
   Omega_m:0.3269797, b1:0.5081696
 2023-07-02 10:33:37,391 [model] Posterior to be computed for parameters {'Omega_m': 0.32193156491818914, 'b1': 1.3504724504965633}
 2023-07-02 10:33:37,391 [prior] Evaluating prior at array([0.32193156, 1.35047245])
 2023-07-02 10:33:37,391 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,391 [model] Got input parameters: {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3504724504965633, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,391 [classy] Got parameters {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,391 [classy] Re-using computed results
 2023-07-02 10:33:37,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13836508112396}
 2023-07-02 10:33:37,391 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3504724504965633, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,391 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,411 [fs_likelihood.fslikelihood] Computed log-likelihood = -4310.46
 2023-07-02 10:33:37,411 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,411 [model] Posterior to be computed for parameters {'Omega_m': 0.3210690439003122, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,411 [prior] Evaluating prior at array([0.32106904, 0.5081696 ])
 2023-07-02 10:33:37,411 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,411 [model] Got input parameters: {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,411 [classy] Got parameters {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,411 [classy] Computing new state
 2023-07-02 10:33:37,412 [classy] Setting parameters: {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23955143743035}
 2023-07-02 10:33:37,455 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,457 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00462674
 2023-07-02 10:33:37,457 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,457 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,477 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.75699
 2023-07-02 10:33:37,477 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,477 [mcmc] New sample, #126:
   Omega_m:0.3219316, b1:0.5081696
 2023-07-02 10:33:37,477 [model] Posterior to be computed for parameters {'Omega_m': 0.3210690439003122, 'b1': 0.4593580081508827}
 2023-07-02 10:33:37,477 [prior] Evaluating prior at array([0.32106904, 0.45935801])
 2023-07-02 10:33:37,478 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,478 [model] Got input parameters: {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4593580081508827, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,478 [classy] Got parameters {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,478 [classy] Re-using computed results
 2023-07-02 10:33:37,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23955143743035}
 2023-07-02 10:33:37,478 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,478 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4593580081508827, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,478 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,497 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.373788
 2023-07-02 10:33:37,498 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,498 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,498 [prior] Evaluating prior at array([0.31410228, 0.5081696 ])
 2023-07-02 10:33:37,498 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,498 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,498 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,498 [classy] Computing new state
 2023-07-02 10:33:37,498 [classy] Setting parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
 2023-07-02 10:33:37,542 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,544 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000362397
 2023-07-02 10:33:37,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,544 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,564 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81612
 2023-07-02 10:33:37,564 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,564 [mcmc] New sample, #127:
   Omega_m:0.321069, b1:0.5081696
 2023-07-02 10:33:37,564 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 1.9673070374974118}
 2023-07-02 10:33:37,564 [prior] Evaluating prior at array([0.31410228, 1.96730704])
 2023-07-02 10:33:37,564 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,564 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.9673070374974118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,564 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,564 [classy] Re-using computed results
 2023-07-02 10:33:37,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
 2023-07-02 10:33:37,564 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.9673070374974118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,564 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,584 [fs_likelihood.fslikelihood] Computed log-likelihood = -18627.9
 2023-07-02 10:33:37,584 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,584 [model] Posterior to be computed for parameters {'Omega_m': 0.3251188279579224, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,584 [prior] Evaluating prior at array([0.32511883, 0.5081696 ])
 2023-07-02 10:33:37,585 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,585 [model] Got input parameters: {'Omega_m': 0.3251188279579224, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,585 [classy] Got parameters {'Omega_m': 0.3251188279579224, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,585 [classy] Computing new state
 2023-07-02 10:33:37,585 [classy] Setting parameters: {'Omega_m': 0.3251188279579224, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76654441451672}
 2023-07-02 10:33:37,628 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00969179
 2023-07-02 10:33:37,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,630 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.480892
 2023-07-02 10:33:37,650 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,650 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 1.0692039959281265}
 2023-07-02 10:33:37,650 [prior] Evaluating prior at array([0.31410228, 1.069204  ])
 2023-07-02 10:33:37,650 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,650 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0692039959281265, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,650 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,651 [classy] Re-using computed results
 2023-07-02 10:33:37,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
 2023-07-02 10:33:37,651 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,651 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0692039959281265, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,651 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,670 [fs_likelihood.fslikelihood] Computed log-likelihood = -1454.46
 2023-07-02 10:33:37,670 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,670 [model] Posterior to be computed for parameters {'Omega_m': 0.32319048762567615, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,670 [prior] Evaluating prior at array([0.32319049, 0.5081696 ])
 2023-07-02 10:33:37,671 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,671 [model] Got input parameters: {'Omega_m': 0.32319048762567615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,671 [classy] Got parameters {'Omega_m': 0.32319048762567615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,671 [classy] Computing new state
 2023-07-02 10:33:37,671 [classy] Setting parameters: {'Omega_m': 0.32319048762567615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99111118685556}
 2023-07-02 10:33:37,714 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00704809
 2023-07-02 10:33:37,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,716 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14908
 2023-07-02 10:33:37,736 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,736 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 0.7709452780085824}
 2023-07-02 10:33:37,736 [prior] Evaluating prior at array([0.31410228, 0.77094528])
 2023-07-02 10:33:37,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,736 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7709452780085824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,736 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,737 [classy] Re-using computed results
 2023-07-02 10:33:37,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
 2023-07-02 10:33:37,737 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,737 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7709452780085824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,737 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,756 [fs_likelihood.fslikelihood] Computed log-likelihood = -249.461
 2023-07-02 10:33:37,756 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,756 [model] Posterior to be computed for parameters {'Omega_m': 0.3078101188864791, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,756 [prior] Evaluating prior at array([0.30781012, 0.5081696 ])
 2023-07-02 10:33:37,756 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,756 [model] Got input parameters: {'Omega_m': 0.3078101188864791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,756 [classy] Got parameters {'Omega_m': 0.3078101188864791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,757 [classy] Computing new state
 2023-07-02 10:33:37,757 [classy] Setting parameters: {'Omega_m': 0.3078101188864791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82629060786067}
 2023-07-02 10:33:37,801 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,802 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00155778
 2023-07-02 10:33:37,802 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,802 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53772
 2023-07-02 10:33:37,822 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,822 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': -0.10535079769791722}
 2023-07-02 10:33:37,822 [prior] Evaluating prior at array([ 0.31410228, -0.1053508 ])
 2023-07-02 10:33:37,822 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:37,822 [model] Posterior to be computed for parameters {'Omega_m': 0.301964460517499, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,822 [prior] Evaluating prior at array([0.30196446, 0.5081696 ])
 2023-07-02 10:33:37,822 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,822 [model] Got input parameters: {'Omega_m': 0.301964460517499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,823 [classy] Got parameters {'Omega_m': 0.301964460517499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,823 [classy] Computing new state
 2023-07-02 10:33:37,823 [classy] Setting parameters: {'Omega_m': 0.301964460517499, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,867 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.54513882597197}
 2023-07-02 10:33:37,867 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,868 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00716976
 2023-07-02 10:33:37,869 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,869 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,889 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22875
 2023-07-02 10:33:37,889 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,889 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': -0.6016101930397859}
 2023-07-02 10:33:37,889 [prior] Evaluating prior at array([ 0.31410228, -0.60161019])
 2023-07-02 10:33:37,889 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:37,889 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,889 [prior] Evaluating prior at array([0.31626459, 0.5081696 ])
 2023-07-02 10:33:37,889 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,889 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,889 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,889 [classy] Computing new state
 2023-07-02 10:33:37,889 [classy] Setting parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:37,933 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
 2023-07-02 10:33:37,933 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:37,935 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00107071
 2023-07-02 10:33:37,935 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,935 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,954 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64118
 2023-07-02 10:33:37,955 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,955 [mcmc] New sample, #128:
   Omega_m:0.3141023, b1:0.5081696
 2023-07-02 10:33:37,955 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.15035292186360488}
 2023-07-02 10:33:37,955 [prior] Evaluating prior at array([0.31626459, 0.15035292])
 2023-07-02 10:33:37,955 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,955 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15035292186360488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,955 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,955 [classy] Re-using computed results
 2023-07-02 10:33:37,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
 2023-07-02 10:33:37,955 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:37,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15035292186360488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,955 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:37,975 [fs_likelihood.fslikelihood] Computed log-likelihood = -223.355
 2023-07-02 10:33:37,975 [model] Computed derived parameters: {}
 2023-07-02 10:33:37,975 [model] Posterior to be computed for parameters {'Omega_m': 0.3500947073394598, 'b1': 0.5081695971600135}
 2023-07-02 10:33:37,975 [prior] Evaluating prior at array([0.35009471, 0.5081696 ])
 2023-07-02 10:33:37,976 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:37,976 [model] Got input parameters: {'Omega_m': 0.3500947073394598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:37,976 [classy] Got parameters {'Omega_m': 0.3500947073394598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:37,976 [classy] Computing new state
 2023-07-02 10:33:37,976 [classy] Setting parameters: {'Omega_m': 0.3500947073394598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9619451226792}
 2023-07-02 10:33:38,020 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,021 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0794496
 2023-07-02 10:33:38,021 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,021 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,042 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.1204
 2023-07-02 10:33:38,042 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,042 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.42174943916464563}
 2023-07-02 10:33:38,042 [prior] Evaluating prior at array([0.31626459, 0.42174944])
 2023-07-02 10:33:38,042 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,042 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42174943916464563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,042 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,042 [classy] Re-using computed results
 2023-07-02 10:33:38,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
 2023-07-02 10:33:38,042 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42174943916464563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,042 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,062 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.6232
 2023-07-02 10:33:38,062 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,063 [model] Posterior to be computed for parameters {'Omega_m': 0.33005710934507876, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,063 [prior] Evaluating prior at array([0.33005711, 0.5081696 ])
 2023-07-02 10:33:38,063 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,063 [model] Got input parameters: {'Omega_m': 0.33005710934507876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,063 [classy] Got parameters {'Omega_m': 0.33005710934507876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,063 [classy] Computing new state
 2023-07-02 10:33:38,063 [classy] Setting parameters: {'Omega_m': 0.33005710934507876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.19686068462528}
 2023-07-02 10:33:38,107 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,109 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0183424
 2023-07-02 10:33:38,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,109 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,130 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.73222
 2023-07-02 10:33:38,131 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,131 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.24631095733441694}
 2023-07-02 10:33:38,131 [prior] Evaluating prior at array([0.31626459, 0.24631096])
 2023-07-02 10:33:38,131 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,131 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24631095733441694, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,131 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,131 [classy] Re-using computed results
 2023-07-02 10:33:38,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
 2023-07-02 10:33:38,131 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24631095733441694, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,131 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,152 [fs_likelihood.fslikelihood] Computed log-likelihood = -128.714
 2023-07-02 10:33:38,152 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,152 [model] Posterior to be computed for parameters {'Omega_m': 0.3264083096838791, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,152 [prior] Evaluating prior at array([0.32640831, 0.5081696 ])
 2023-07-02 10:33:38,152 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,152 [model] Got input parameters: {'Omega_m': 0.3264083096838791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,153 [classy] Got parameters {'Omega_m': 0.3264083096838791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,153 [classy] Computing new state
 2023-07-02 10:33:38,153 [classy] Setting parameters: {'Omega_m': 0.3264083096838791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.61704318193253}
 2023-07-02 10:33:38,197 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,198 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0116917
 2023-07-02 10:33:38,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,199 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,218 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0273453
 2023-07-02 10:33:38,218 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,218 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': -2.232836064909481}
 2023-07-02 10:33:38,218 [prior] Evaluating prior at array([ 0.31626459, -2.23283606])
 2023-07-02 10:33:38,218 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:38,219 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,219 [prior] Evaluating prior at array([0.32213276, 0.5081696 ])
 2023-07-02 10:33:38,219 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,219 [model] Got input parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,219 [classy] Got parameters {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,219 [classy] Computing new state
 2023-07-02 10:33:38,219 [classy] Setting parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11479559218836}
 2023-07-02 10:33:38,263 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,265 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00577664
 2023-07-02 10:33:38,265 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,265 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,285 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46883
 2023-07-02 10:33:38,285 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,285 [mcmc] New sample, #129:
   Omega_m:0.3162646, b1:0.5081696
 2023-07-02 10:33:38,285 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': -0.044039184540138}
 2023-07-02 10:33:38,285 [prior] Evaluating prior at array([ 0.32213276, -0.04403918])
 2023-07-02 10:33:38,285 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:38,285 [model] Posterior to be computed for parameters {'Omega_m': 0.32557116465223335, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,285 [prior] Evaluating prior at array([0.32557116, 0.5081696 ])
 2023-07-02 10:33:38,285 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,285 [model] Got input parameters: {'Omega_m': 0.32557116465223335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,285 [classy] Got parameters {'Omega_m': 0.32557116465223335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,285 [classy] Computing new state
 2023-07-02 10:33:38,286 [classy] Setting parameters: {'Omega_m': 0.32557116465223335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.71404168934984}
 2023-07-02 10:33:38,330 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,332 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0103723
 2023-07-02 10:33:38,332 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,332 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,352 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.308213
 2023-07-02 10:33:38,352 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,352 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': 0.6479281521144084}
 2023-07-02 10:33:38,352 [prior] Evaluating prior at array([0.32213276, 0.64792815])
 2023-07-02 10:33:38,352 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,352 [model] Got input parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6479281521144084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,352 [classy] Got parameters {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,352 [classy] Re-using computed results
 2023-07-02 10:33:38,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11479559218836}
 2023-07-02 10:33:38,353 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6479281521144084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,353 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,372 [fs_likelihood.fslikelihood] Computed log-likelihood = -79.2235
 2023-07-02 10:33:38,373 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,373 [model] Posterior to be computed for parameters {'Omega_m': 0.32911900299080266, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,373 [prior] Evaluating prior at array([0.329119 , 0.5081696])
 2023-07-02 10:33:38,373 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,373 [model] Got input parameters: {'Omega_m': 0.32911900299080266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,373 [classy] Got parameters {'Omega_m': 0.32911900299080266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,373 [classy] Computing new state
 2023-07-02 10:33:38,373 [classy] Setting parameters: {'Omega_m': 0.32911900299080266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.30448501866485}
 2023-07-02 10:33:38,417 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0164941
 2023-07-02 10:33:38,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,419 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25625
 2023-07-02 10:33:38,439 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,439 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': 0.9235474343775831}
 2023-07-02 10:33:38,439 [prior] Evaluating prior at array([0.32213276, 0.92354743])
 2023-07-02 10:33:38,439 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,439 [model] Got input parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9235474343775831, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,439 [classy] Got parameters {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,439 [classy] Re-using computed results
 2023-07-02 10:33:38,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11479559218836}
 2023-07-02 10:33:38,439 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9235474343775831, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,439 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -775.629
 2023-07-02 10:33:38,459 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,459 [model] Posterior to be computed for parameters {'Omega_m': 0.3086859712810961, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,460 [prior] Evaluating prior at array([0.30868597, 0.5081696 ])
 2023-07-02 10:33:38,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,460 [model] Got input parameters: {'Omega_m': 0.3086859712810961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,460 [classy] Got parameters {'Omega_m': 0.3086859712810961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,460 [classy] Computing new state
 2023-07-02 10:33:38,460 [classy] Setting parameters: {'Omega_m': 0.3086859712810961, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.71962048732}
 2023-07-02 10:33:38,504 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,505 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00109543
 2023-07-02 10:33:38,505 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,505 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,525 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6467
 2023-07-02 10:33:38,525 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,525 [mcmc] New sample, #130:
   Omega_m:0.3221328, b1:0.5081696
 2023-07-02 10:33:38,525 [model] Posterior to be computed for parameters {'Omega_m': 0.3086859712810961, 'b1': -0.49715929178209883}
 2023-07-02 10:33:38,525 [prior] Evaluating prior at array([ 0.30868597, -0.49715929])
 2023-07-02 10:33:38,525 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:38,525 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,525 [prior] Evaluating prior at array([0.30955454, 0.5081696 ])
 2023-07-02 10:33:38,525 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,525 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,526 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,526 [classy] Computing new state
 2023-07-02 10:33:38,526 [classy] Setting parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
 2023-07-02 10:33:38,570 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,572 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000732519
 2023-07-02 10:33:38,572 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,572 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,591 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73234
 2023-07-02 10:33:38,591 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,591 [mcmc] New sample, #131:
   Omega_m:0.308686, b1:0.5081696
 2023-07-02 10:33:38,591 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 1.059477949518619}
 2023-07-02 10:33:38,591 [prior] Evaluating prior at array([0.30955454, 1.05947795])
 2023-07-02 10:33:38,591 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,591 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.059477949518619, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,592 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,592 [classy] Re-using computed results
 2023-07-02 10:33:38,592 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
 2023-07-02 10:33:38,592 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.059477949518619, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,592 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,611 [fs_likelihood.fslikelihood] Computed log-likelihood = -1335.02
 2023-07-02 10:33:38,612 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,612 [model] Posterior to be computed for parameters {'Omega_m': 0.2878591149458605, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,612 [prior] Evaluating prior at array([0.28785911, 0.5081696 ])
 2023-07-02 10:33:38,612 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,612 [model] Got input parameters: {'Omega_m': 0.2878591149458605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,612 [classy] Got parameters {'Omega_m': 0.2878591149458605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,612 [classy] Computing new state
 2023-07-02 10:33:38,612 [classy] Setting parameters: {'Omega_m': 0.2878591149458605, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,656 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3312412248245}
 2023-07-02 10:33:38,656 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,658 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0397943
 2023-07-02 10:33:38,658 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,658 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,677 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.09554
 2023-07-02 10:33:38,678 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,678 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 0.345972338253289}
 2023-07-02 10:33:38,678 [prior] Evaluating prior at array([0.30955454, 0.34597234])
 2023-07-02 10:33:38,678 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,678 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.345972338253289, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,678 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,678 [classy] Re-using computed results
 2023-07-02 10:33:38,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
 2023-07-02 10:33:38,678 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.345972338253289, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,678 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,698 [fs_likelihood.fslikelihood] Computed log-likelihood = -58.3994
 2023-07-02 10:33:38,698 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,698 [model] Posterior to be computed for parameters {'Omega_m': 0.32639637491142215, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,698 [prior] Evaluating prior at array([0.32639637, 0.5081696 ])
 2023-07-02 10:33:38,698 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,698 [model] Got input parameters: {'Omega_m': 0.32639637491142215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,698 [classy] Got parameters {'Omega_m': 0.32639637491142215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,698 [classy] Computing new state
 2023-07-02 10:33:38,698 [classy] Setting parameters: {'Omega_m': 0.32639637491142215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.61842526522761}
 2023-07-02 10:33:38,743 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0116724
 2023-07-02 10:33:38,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,745 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,766 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0224156
 2023-07-02 10:33:38,766 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,766 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': -0.09852389063680334}
 2023-07-02 10:33:38,766 [prior] Evaluating prior at array([ 0.30955454, -0.09852389])
 2023-07-02 10:33:38,766 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:38,767 [model] Posterior to be computed for parameters {'Omega_m': 0.28604906547070286, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,767 [prior] Evaluating prior at array([0.28604907, 0.5081696 ])
 2023-07-02 10:33:38,767 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,767 [model] Got input parameters: {'Omega_m': 0.28604906547070286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,767 [classy] Got parameters {'Omega_m': 0.28604906547070286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,767 [classy] Computing new state
 2023-07-02 10:33:38,767 [classy] Setting parameters: {'Omega_m': 0.28604906547070286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,811 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.56590854782948}
 2023-07-02 10:33:38,811 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0460448
 2023-07-02 10:33:38,813 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,813 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,833 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.46186
 2023-07-02 10:33:38,833 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,833 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 0.4636689578458205}
 2023-07-02 10:33:38,833 [prior] Evaluating prior at array([0.30955454, 0.46366896])
 2023-07-02 10:33:38,834 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,834 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4636689578458205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,834 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,834 [classy] Re-using computed results
 2023-07-02 10:33:38,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
 2023-07-02 10:33:38,834 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:38,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4636689578458205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,834 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,854 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.80514
 2023-07-02 10:33:38,854 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,855 [model] Posterior to be computed for parameters {'Omega_m': 0.31233281003720503, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,855 [prior] Evaluating prior at array([0.31233281, 0.5081696 ])
 2023-07-02 10:33:38,855 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,855 [model] Got input parameters: {'Omega_m': 0.31233281003720503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,855 [classy] Got parameters {'Omega_m': 0.31233281003720503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,855 [classy] Computing new state
 2023-07-02 10:33:38,855 [classy] Setting parameters: {'Omega_m': 0.31233281003720503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2783221716335}
 2023-07-02 10:33:38,899 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,901 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00020377
 2023-07-02 10:33:38,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,901 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,920 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8563
 2023-07-02 10:33:38,920 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,920 [mcmc] New sample, #132:
   Omega_m:0.3095545, b1:0.5081696
 2023-07-02 10:33:38,921 [model] Posterior to be computed for parameters {'Omega_m': 0.31233281003720503, 'b1': -0.4138841267955299}
 2023-07-02 10:33:38,921 [prior] Evaluating prior at array([ 0.31233281, -0.41388413])
 2023-07-02 10:33:38,921 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:38,921 [model] Posterior to be computed for parameters {'Omega_m': 0.3250331638540951, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,921 [prior] Evaluating prior at array([0.32503316, 0.5081696 ])
 2023-07-02 10:33:38,921 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,921 [model] Got input parameters: {'Omega_m': 0.3250331638540951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,921 [classy] Got parameters {'Omega_m': 0.3250331638540951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,921 [classy] Computing new state
 2023-07-02 10:33:38,921 [classy] Setting parameters: {'Omega_m': 0.3250331638540951, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:38,965 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.77649620786406}
 2023-07-02 10:33:38,965 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:38,967 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00956546
 2023-07-02 10:33:38,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,967 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:38,986 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.512912
 2023-07-02 10:33:38,986 [model] Computed derived parameters: {}
 2023-07-02 10:33:38,986 [model] Posterior to be computed for parameters {'Omega_m': 0.31233281003720503, 'b1': -0.9759185775155055}
 2023-07-02 10:33:38,986 [prior] Evaluating prior at array([ 0.31233281, -0.97591858])
 2023-07-02 10:33:38,987 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:38,987 [model] Posterior to be computed for parameters {'Omega_m': 0.31253600408907434, 'b1': 0.5081695971600135}
 2023-07-02 10:33:38,987 [prior] Evaluating prior at array([0.312536 , 0.5081696])
 2023-07-02 10:33:38,987 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:38,987 [model] Got input parameters: {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:38,987 [classy] Got parameters {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:38,987 [classy] Computing new state
 2023-07-02 10:33:38,987 [classy] Setting parameters: {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2538679638761}
 2023-07-02 10:33:39,031 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,033 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202536
 2023-07-02 10:33:39,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,033 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,053 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85639
 2023-07-02 10:33:39,053 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,053 [mcmc] New sample, #133:
   Omega_m:0.3123328, b1:0.5081696
 2023-07-02 10:33:39,053 [model] Posterior to be computed for parameters {'Omega_m': 0.31253600408907434, 'b1': 1.381038890979747}
 2023-07-02 10:33:39,053 [prior] Evaluating prior at array([0.312536  , 1.38103889])
 2023-07-02 10:33:39,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,053 [model] Got input parameters: {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.381038890979747, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,053 [classy] Got parameters {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,053 [classy] Re-using computed results
 2023-07-02 10:33:39,053 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2538679638761}
 2023-07-02 10:33:39,053 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,053 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.381038890979747, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,053 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,073 [fs_likelihood.fslikelihood] Computed log-likelihood = -4427.54
 2023-07-02 10:33:39,073 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,073 [model] Posterior to be computed for parameters {'Omega_m': 0.318499954929371, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,073 [prior] Evaluating prior at array([0.31849995, 0.5081696 ])
 2023-07-02 10:33:39,073 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,073 [model] Got input parameters: {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,073 [classy] Got parameters {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,073 [classy] Computing new state
 2023-07-02 10:33:39,073 [classy] Setting parameters: {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,117 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54237872727163}
 2023-07-02 10:33:39,117 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,119 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00238873
 2023-07-02 10:33:39,119 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,119 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.31481
 2023-07-02 10:33:39,141 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,141 [mcmc] New sample, #134:
   Omega_m:0.312536, b1:0.5081696
 2023-07-02 10:33:39,141 [model] Posterior to be computed for parameters {'Omega_m': 0.318499954929371, 'b1': 1.3604718101567963}
 2023-07-02 10:33:39,141 [prior] Evaluating prior at array([0.31849995, 1.36047181])
 2023-07-02 10:33:39,141 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,141 [model] Got input parameters: {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3604718101567963, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,141 [classy] Got parameters {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,141 [classy] Re-using computed results
 2023-07-02 10:33:39,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54237872727163}
 2023-07-02 10:33:39,141 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,141 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3604718101567963, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,141 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,161 [fs_likelihood.fslikelihood] Computed log-likelihood = -4337.96
 2023-07-02 10:33:39,161 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,161 [model] Posterior to be computed for parameters {'Omega_m': 0.32164195609381807, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,161 [prior] Evaluating prior at array([0.32164196, 0.5081696 ])
 2023-07-02 10:33:39,161 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,161 [model] Got input parameters: {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,161 [classy] Got parameters {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,161 [classy] Computing new state
 2023-07-02 10:33:39,161 [classy] Setting parameters: {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1723106357125}
 2023-07-02 10:33:39,205 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00523
 2023-07-02 10:33:39,207 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,207 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,227 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60595
 2023-07-02 10:33:39,227 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,227 [mcmc] New sample, #135:
   Omega_m:0.3185, b1:0.5081696
 2023-07-02 10:33:39,227 [model] Posterior to be computed for parameters {'Omega_m': 0.32164195609381807, 'b1': -0.6305434006022945}
 2023-07-02 10:33:39,227 [prior] Evaluating prior at array([ 0.32164196, -0.6305434 ])
 2023-07-02 10:33:39,227 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:39,227 [model] Posterior to be computed for parameters {'Omega_m': 0.321938908311099, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,227 [prior] Evaluating prior at array([0.32193891, 0.5081696 ])
 2023-07-02 10:33:39,227 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,227 [model] Got input parameters: {'Omega_m': 0.321938908311099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,227 [classy] Got parameters {'Omega_m': 0.321938908311099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,227 [classy] Computing new state
 2023-07-02 10:33:39,227 [classy] Setting parameters: {'Omega_m': 0.321938908311099, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13750518099943}
 2023-07-02 10:33:39,271 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,273 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00555739
 2023-07-02 10:33:39,273 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,273 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,292 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.52384
 2023-07-02 10:33:39,292 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,292 [model] Posterior to be computed for parameters {'Omega_m': 0.32164195609381807, 'b1': 1.5048113395603688}
 2023-07-02 10:33:39,293 [prior] Evaluating prior at array([0.32164196, 1.50481134])
 2023-07-02 10:33:39,293 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,293 [model] Got input parameters: {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5048113395603688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,293 [classy] Got parameters {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,293 [classy] Re-using computed results
 2023-07-02 10:33:39,293 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1723106357125}
 2023-07-02 10:33:39,293 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,293 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5048113395603688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,293 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,313 [fs_likelihood.fslikelihood] Computed log-likelihood = -6707.29
 2023-07-02 10:33:39,313 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,313 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,313 [prior] Evaluating prior at array([0.32811838, 0.5081696 ])
 2023-07-02 10:33:39,313 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,313 [model] Got input parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,313 [classy] Got parameters {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,313 [classy] Computing new state
 2023-07-02 10:33:39,313 [classy] Setting parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41959431406062}
 2023-07-02 10:33:39,357 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0146276
 2023-07-02 10:33:39,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,359 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,379 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.777284
 2023-07-02 10:33:39,379 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,379 [mcmc] New sample, #136:
   Omega_m:0.321642, b1:0.5081696
 2023-07-02 10:33:39,379 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': 1.293426731876872}
 2023-07-02 10:33:39,379 [prior] Evaluating prior at array([0.32811838, 1.29342673])
 2023-07-02 10:33:39,379 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,379 [model] Got input parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.293426731876872, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,379 [classy] Got parameters {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,379 [classy] Re-using computed results
 2023-07-02 10:33:39,379 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41959431406062}
 2023-07-02 10:33:39,379 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.293426731876872, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,379 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,399 [fs_likelihood.fslikelihood] Computed log-likelihood = -3764.98
 2023-07-02 10:33:39,399 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,399 [model] Posterior to be computed for parameters {'Omega_m': 0.341637542132764, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,399 [prior] Evaluating prior at array([0.34163754, 0.5081696 ])
 2023-07-02 10:33:39,399 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,399 [model] Got input parameters: {'Omega_m': 0.341637542132764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,399 [classy] Got parameters {'Omega_m': 0.341637542132764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,399 [classy] Computing new state
 2023-07-02 10:33:39,399 [classy] Setting parameters: {'Omega_m': 0.341637542132764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.89064278887176}
 2023-07-02 10:33:39,443 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0487687
 2023-07-02 10:33:39,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,445 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,465 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.75376
 2023-07-02 10:33:39,465 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,465 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': -0.26403411943648536}
 2023-07-02 10:33:39,465 [prior] Evaluating prior at array([ 0.32811838, -0.26403412])
 2023-07-02 10:33:39,465 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:39,465 [model] Posterior to be computed for parameters {'Omega_m': 0.3489203198548997, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,465 [prior] Evaluating prior at array([0.34892032, 0.5081696 ])
 2023-07-02 10:33:39,466 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,466 [model] Got input parameters: {'Omega_m': 0.3489203198548997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,466 [classy] Got parameters {'Omega_m': 0.3489203198548997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,466 [classy] Computing new state
 2023-07-02 10:33:39,466 [classy] Setting parameters: {'Omega_m': 0.3489203198548997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.08967002476282}
 2023-07-02 10:33:39,510 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0747812
 2023-07-02 10:33:39,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,511 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.832
 2023-07-02 10:33:39,531 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': 0.6946306697290726}
 2023-07-02 10:33:39,531 [prior] Evaluating prior at array([0.32811838, 0.69463067])
 2023-07-02 10:33:39,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,531 [model] Got input parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6946306697290726, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,531 [classy] Got parameters {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,531 [classy] Re-using computed results
 2023-07-02 10:33:39,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41959431406062}
 2023-07-02 10:33:39,531 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,531 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6946306697290726, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,531 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -158.553
 2023-07-02 10:33:39,551 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,551 [model] Posterior to be computed for parameters {'Omega_m': 0.322841883425129, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,551 [prior] Evaluating prior at array([0.32284188, 0.5081696 ])
 2023-07-02 10:33:39,551 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,551 [model] Got input parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,551 [classy] Got parameters {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,551 [classy] Computing new state
 2023-07-02 10:33:39,551 [classy] Setting parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03183507914028}
 2023-07-02 10:33:39,595 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00661499
 2023-07-02 10:33:39,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,597 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,617 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.25812
 2023-07-02 10:33:39,617 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,617 [mcmc] New sample, #137:
   Omega_m:0.3281184, b1:0.5081696
 2023-07-02 10:33:39,617 [model] Posterior to be computed for parameters {'Omega_m': 0.322841883425129, 'b1': 0.632018246526123}
 2023-07-02 10:33:39,617 [prior] Evaluating prior at array([0.32284188, 0.63201825])
 2023-07-02 10:33:39,617 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,617 [model] Got input parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.632018246526123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,617 [classy] Got parameters {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,617 [classy] Re-using computed results
 2023-07-02 10:33:39,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03183507914028}
 2023-07-02 10:33:39,617 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.632018246526123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,617 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,637 [fs_likelihood.fslikelihood] Computed log-likelihood = -64.1411
 2023-07-02 10:33:39,637 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3312337538401237, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,637 [prior] Evaluating prior at array([0.33123375, 0.5081696 ])
 2023-07-02 10:33:39,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,637 [model] Got input parameters: {'Omega_m': 0.3312337538401237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,637 [classy] Got parameters {'Omega_m': 0.3312337538401237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,637 [classy] Computing new state
 2023-07-02 10:33:39,637 [classy] Setting parameters: {'Omega_m': 0.3312337538401237, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.06226986422362}
 2023-07-02 10:33:39,681 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0207942
 2023-07-02 10:33:39,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,683 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,702 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.36605
 2023-07-02 10:33:39,703 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,703 [model] Posterior to be computed for parameters {'Omega_m': 0.322841883425129, 'b1': 0.7016928514894645}
 2023-07-02 10:33:39,703 [prior] Evaluating prior at array([0.32284188, 0.70169285])
 2023-07-02 10:33:39,703 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,703 [model] Got input parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7016928514894645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,703 [classy] Got parameters {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,703 [classy] Re-using computed results
 2023-07-02 10:33:39,703 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03183507914028}
 2023-07-02 10:33:39,703 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,703 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7016928514894645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,703 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,723 [fs_likelihood.fslikelihood] Computed log-likelihood = -153.121
 2023-07-02 10:33:39,723 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,723 [model] Posterior to be computed for parameters {'Omega_m': 0.30950983653367176, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,723 [prior] Evaluating prior at array([0.30950984, 0.5081696 ])
 2023-07-02 10:33:39,723 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,723 [model] Got input parameters: {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,723 [classy] Got parameters {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,723 [classy] Computing new state
 2023-07-02 10:33:39,723 [classy] Setting parameters: {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6195255902834}
 2023-07-02 10:33:39,767 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000748885
 2023-07-02 10:33:39,769 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,769 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,789 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72848
 2023-07-02 10:33:39,789 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,789 [mcmc] New sample, #138:
   Omega_m:0.3228419, b1:0.5081696
 2023-07-02 10:33:39,789 [model] Posterior to be computed for parameters {'Omega_m': 0.30950983653367176, 'b1': 1.5322481000144177}
 2023-07-02 10:33:39,789 [prior] Evaluating prior at array([0.30950984, 1.5322481 ])
 2023-07-02 10:33:39,789 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,789 [model] Got input parameters: {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5322481000144177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,789 [classy] Got parameters {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,789 [classy] Re-using computed results
 2023-07-02 10:33:39,789 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6195255902834}
 2023-07-02 10:33:39,789 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5322481000144177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,789 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,808 [fs_likelihood.fslikelihood] Computed log-likelihood = -6670.33
 2023-07-02 10:33:39,808 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,809 [model] Posterior to be computed for parameters {'Omega_m': 0.30647785218661006, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,809 [prior] Evaluating prior at array([0.30647785, 0.5081696 ])
 2023-07-02 10:33:39,809 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,809 [model] Got input parameters: {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,809 [classy] Got parameters {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,809 [classy] Computing new state
 2023-07-02 10:33:39,809 [classy] Setting parameters: {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.989059674482}
 2023-07-02 10:33:39,853 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,855 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00244807
 2023-07-02 10:33:39,855 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,855 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,874 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32841
 2023-07-02 10:33:39,874 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,875 [mcmc] New sample, #139:
   Omega_m:0.3095098, b1:0.5081696
 2023-07-02 10:33:39,875 [model] Posterior to be computed for parameters {'Omega_m': 0.30647785218661006, 'b1': 0.8202622832984243}
 2023-07-02 10:33:39,875 [prior] Evaluating prior at array([0.30647785, 0.82026228])
 2023-07-02 10:33:39,875 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,875 [model] Got input parameters: {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8202622832984243, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,875 [classy] Got parameters {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,875 [classy] Re-using computed results
 2023-07-02 10:33:39,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.989059674482}
 2023-07-02 10:33:39,875 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:39,875 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8202622832984243, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,875 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,894 [fs_likelihood.fslikelihood] Computed log-likelihood = -328.481
 2023-07-02 10:33:39,894 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,895 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,895 [prior] Evaluating prior at array([0.30804903, 0.5081696 ])
 2023-07-02 10:33:39,895 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,895 [model] Got input parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,895 [classy] Got parameters {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,895 [classy] Computing new state
 2023-07-02 10:33:39,895 [classy] Setting parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:39,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79716537299896}
 2023-07-02 10:33:39,939 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:39,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00142201
 2023-07-02 10:33:39,941 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,941 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:39,960 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5697
 2023-07-02 10:33:39,960 [model] Computed derived parameters: {}
 2023-07-02 10:33:39,960 [mcmc] New sample, #140:
   Omega_m:0.3064779, b1:0.5081696
 2023-07-02 10:33:39,960 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': -0.15055873698430333}
 2023-07-02 10:33:39,960 [prior] Evaluating prior at array([ 0.30804903, -0.15055874])
 2023-07-02 10:33:39,960 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:39,961 [model] Posterior to be computed for parameters {'Omega_m': 0.2853049395846005, 'b1': 0.5081695971600135}
 2023-07-02 10:33:39,961 [prior] Evaluating prior at array([0.28530494, 0.5081696 ])
 2023-07-02 10:33:39,961 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:39,961 [model] Got input parameters: {'Omega_m': 0.2853049395846005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:39,961 [classy] Got parameters {'Omega_m': 0.2853049395846005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:39,961 [classy] Computing new state
 2023-07-02 10:33:39,961 [classy] Setting parameters: {'Omega_m': 0.2853049395846005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.66276563523996}
 2023-07-02 10:33:40,005 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0487572
 2023-07-02 10:33:40,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,006 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,026 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.0517
 2023-07-02 10:33:40,026 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,027 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': 1.1656813949788731}
 2023-07-02 10:33:40,027 [prior] Evaluating prior at array([0.30804903, 1.16568139])
 2023-07-02 10:33:40,027 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,027 [model] Got input parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1656813949788731, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,027 [classy] Got parameters {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,027 [classy] Re-using computed results
 2023-07-02 10:33:40,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79716537299896}
 2023-07-02 10:33:40,027 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1656813949788731, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,027 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -2049.43
 2023-07-02 10:33:40,046 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,047 [model] Posterior to be computed for parameters {'Omega_m': 0.30144741904340266, 'b1': 0.5081695971600135}
 2023-07-02 10:33:40,047 [prior] Evaluating prior at array([0.30144742, 0.5081696 ])
 2023-07-02 10:33:40,047 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,047 [model] Got input parameters: {'Omega_m': 0.30144741904340266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,047 [classy] Got parameters {'Omega_m': 0.30144741904340266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,047 [classy] Computing new state
 2023-07-02 10:33:40,047 [classy] Setting parameters: {'Omega_m': 0.30144741904340266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,091 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6093035816727}
 2023-07-02 10:33:40,091 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,093 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00788145
 2023-07-02 10:33:40,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,093 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,112 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.06428
 2023-07-02 10:33:40,112 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,112 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': 0.5038421282358159}
 2023-07-02 10:33:40,112 [prior] Evaluating prior at array([0.30804903, 0.50384213])
 2023-07-02 10:33:40,112 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,112 [model] Got input parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,112 [classy] Got parameters {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,112 [classy] Re-using computed results
 2023-07-02 10:33:40,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79716537299896}
 2023-07-02 10:33:40,112 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,112 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41002
 2023-07-02 10:33:40,141 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,141 [mcmc] New sample, #141:
   Omega_m:0.308049, b1:0.5081696
 2023-07-02 10:33:40,141 [model] Posterior to be computed for parameters {'Omega_m': 0.3092239989748048, 'b1': 0.5038421282358159}
 2023-07-02 10:33:40,141 [prior] Evaluating prior at array([0.309224  , 0.50384213])
 2023-07-02 10:33:40,141 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,141 [model] Got input parameters: {'Omega_m': 0.3092239989748048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,141 [classy] Got parameters {'Omega_m': 0.3092239989748048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,141 [classy] Computing new state
 2023-07-02 10:33:40,141 [classy] Setting parameters: {'Omega_m': 0.3092239989748048, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6542257251065}
 2023-07-02 10:33:40,186 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000859445
 2023-07-02 10:33:40,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,188 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,207 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59115
 2023-07-02 10:33:40,208 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,208 [mcmc] New sample, #142:
   Omega_m:0.308049, b1:0.5038421
 2023-07-02 10:33:40,208 [model] Posterior to be computed for parameters {'Omega_m': 0.3092239989748048, 'b1': -0.22378354407501733}
 2023-07-02 10:33:40,208 [prior] Evaluating prior at array([ 0.309224  , -0.22378354])
 2023-07-02 10:33:40,208 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:40,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.5038421282358159}
 2023-07-02 10:33:40,208 [prior] Evaluating prior at array([0.32119731, 0.50384213])
 2023-07-02 10:33:40,208 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,208 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,208 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,208 [classy] Computing new state
 2023-07-02 10:33:40,208 [classy] Setting parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,252 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,254 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00475854
 2023-07-02 10:33:40,254 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,254 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,274 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13102
 2023-07-02 10:33:40,274 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,275 [mcmc] New sample, #143:
   Omega_m:0.309224, b1:0.5038421
 2023-07-02 10:33:40,275 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,275 [prior] Evaluating prior at array([0.32119731, 0.50839951])
 2023-07-02 10:33:40,275 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,275 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,275 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,275 [classy] Re-using computed results
 2023-07-02 10:33:40,275 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,275 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,275 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,294 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.69941
 2023-07-02 10:33:40,295 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,295 [mcmc] New sample, #144:
   Omega_m:0.3211973, b1:0.5038421
 2023-07-02 10:33:40,295 [model] Posterior to be computed for parameters {'Omega_m': 0.29913903175634593, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,295 [prior] Evaluating prior at array([0.29913903, 0.50839951])
 2023-07-02 10:33:40,295 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,295 [model] Got input parameters: {'Omega_m': 0.29913903175634593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,295 [classy] Got parameters {'Omega_m': 0.29913903175634593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,295 [classy] Computing new state
 2023-07-02 10:33:40,295 [classy] Setting parameters: {'Omega_m': 0.29913903175634593, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,339 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89699225066107}
 2023-07-02 10:33:40,339 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,341 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114961
 2023-07-02 10:33:40,341 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,341 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,360 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.258075
 2023-07-02 10:33:40,360 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,361 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 1.0812272564714172}
 2023-07-02 10:33:40,361 [prior] Evaluating prior at array([0.32119731, 1.08122726])
 2023-07-02 10:33:40,361 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,361 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0812272564714172, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,361 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,361 [classy] Re-using computed results
 2023-07-02 10:33:40,361 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,361 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,361 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0812272564714172, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,361 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,382 [fs_likelihood.fslikelihood] Computed log-likelihood = -1634.06
 2023-07-02 10:33:40,382 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,382 [model] Posterior to be computed for parameters {'Omega_m': 0.34769066838834484, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,382 [prior] Evaluating prior at array([0.34769067, 0.50839951])
 2023-07-02 10:33:40,382 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,382 [model] Got input parameters: {'Omega_m': 0.34769066838834484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,382 [classy] Got parameters {'Omega_m': 0.34769066838834484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,382 [classy] Computing new state
 2023-07-02 10:33:40,382 [classy] Setting parameters: {'Omega_m': 0.34769066838834484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,426 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.22382506571012}
 2023-07-02 10:33:40,426 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,428 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0700324
 2023-07-02 10:33:40,428 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,428 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,447 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.6212
 2023-07-02 10:33:40,447 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,447 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.8169005672647267}
 2023-07-02 10:33:40,447 [prior] Evaluating prior at array([0.32119731, 0.81690057])
 2023-07-02 10:33:40,448 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,448 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8169005672647267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,448 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,448 [classy] Re-using computed results
 2023-07-02 10:33:40,448 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,448 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,448 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8169005672647267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,448 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,467 [fs_likelihood.fslikelihood] Computed log-likelihood = -396.012
 2023-07-02 10:33:40,467 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,467 [model] Posterior to be computed for parameters {'Omega_m': 0.33142017691773556, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,467 [prior] Evaluating prior at array([0.33142018, 0.50839951])
 2023-07-02 10:33:40,467 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,467 [model] Got input parameters: {'Omega_m': 0.33142017691773556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,467 [classy] Got parameters {'Omega_m': 0.33142017691773556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,467 [classy] Computing new state
 2023-07-02 10:33:40,467 [classy] Setting parameters: {'Omega_m': 0.33142017691773556, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.04098393235012}
 2023-07-02 10:33:40,511 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,513 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0211963
 2023-07-02 10:33:40,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,513 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,533 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.52042
 2023-07-02 10:33:40,533 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,533 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.17365251849692215}
 2023-07-02 10:33:40,533 [prior] Evaluating prior at array([0.32119731, 0.17365252])
 2023-07-02 10:33:40,533 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,533 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.17365251849692215, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,534 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,534 [classy] Re-using computed results
 2023-07-02 10:33:40,534 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,534 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,534 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.17365251849692215, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,534 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,553 [fs_likelihood.fslikelihood] Computed log-likelihood = -190.986
 2023-07-02 10:33:40,553 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,553 [model] Posterior to be computed for parameters {'Omega_m': 0.3499952494680272, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,553 [prior] Evaluating prior at array([0.34999525, 0.50839951])
 2023-07-02 10:33:40,554 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,554 [model] Got input parameters: {'Omega_m': 0.3499952494680272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,554 [classy] Got parameters {'Omega_m': 0.3499952494680272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,554 [classy] Computing new state
 2023-07-02 10:33:40,554 [classy] Setting parameters: {'Omega_m': 0.3499952494680272, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.97274649337882}
 2023-07-02 10:33:40,598 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0790493
 2023-07-02 10:33:40,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,600 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,619 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.1108
 2023-07-02 10:33:40,620 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,620 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.6691389895477349}
 2023-07-02 10:33:40,620 [prior] Evaluating prior at array([0.32119731, 0.66913899])
 2023-07-02 10:33:40,620 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,620 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6691389895477349, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,620 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,620 [classy] Re-using computed results
 2023-07-02 10:33:40,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,620 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6691389895477349, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,620 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,640 [fs_likelihood.fslikelihood] Computed log-likelihood = -102.117
 2023-07-02 10:33:40,640 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,640 [model] Posterior to be computed for parameters {'Omega_m': 0.333706756258011, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,640 [prior] Evaluating prior at array([0.33370676, 0.50839951])
 2023-07-02 10:33:40,641 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,641 [model] Got input parameters: {'Omega_m': 0.333706756258011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,641 [classy] Got parameters {'Omega_m': 0.333706756258011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,641 [classy] Computing new state
 2023-07-02 10:33:40,641 [classy] Setting parameters: {'Omega_m': 0.333706756258011, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.78079224172563}
 2023-07-02 10:33:40,685 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0264278
 2023-07-02 10:33:40,687 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,687 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,706 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.88794
 2023-07-02 10:33:40,706 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,706 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 1.7794815984096837}
 2023-07-02 10:33:40,706 [prior] Evaluating prior at array([0.32119731, 1.7794816 ])
 2023-07-02 10:33:40,706 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,706 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7794815984096837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,707 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,707 [classy] Re-using computed results
 2023-07-02 10:33:40,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
 2023-07-02 10:33:40,707 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,707 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7794815984096837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,707 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,727 [fs_likelihood.fslikelihood] Computed log-likelihood = -13067.1
 2023-07-02 10:33:40,727 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,727 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,727 [prior] Evaluating prior at array([0.31329719, 0.50839951])
 2023-07-02 10:33:40,727 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,727 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,727 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,727 [classy] Computing new state
 2023-07-02 10:33:40,727 [classy] Setting parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
 2023-07-02 10:33:40,771 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,773 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000242868
 2023-07-02 10:33:40,773 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,773 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,793 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83986
 2023-07-02 10:33:40,793 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,793 [mcmc] New sample, #145:
   Omega_m:0.3211973, b1:0.5083995
 2023-07-02 10:33:40,793 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': -0.09513429411065599}
 2023-07-02 10:33:40,793 [prior] Evaluating prior at array([ 0.31329719, -0.09513429])
 2023-07-02 10:33:40,793 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:40,793 [model] Posterior to be computed for parameters {'Omega_m': 0.3186140866614561, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,794 [prior] Evaluating prior at array([0.31861409, 0.50839951])
 2023-07-02 10:33:40,794 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,794 [model] Got input parameters: {'Omega_m': 0.3186140866614561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,794 [classy] Got parameters {'Omega_m': 0.3186140866614561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,794 [classy] Computing new state
 2023-07-02 10:33:40,794 [classy] Setting parameters: {'Omega_m': 0.3186140866614561, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.52887842403229}
 2023-07-02 10:33:40,838 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00247185
 2023-07-02 10:33:40,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,840 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,859 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27574
 2023-07-02 10:33:40,859 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,859 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 0.9591889722406497}
 2023-07-02 10:33:40,860 [prior] Evaluating prior at array([0.31329719, 0.95918897])
 2023-07-02 10:33:40,860 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,860 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9591889722406497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,860 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,860 [classy] Re-using computed results
 2023-07-02 10:33:40,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
 2023-07-02 10:33:40,860 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9591889722406497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,860 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,880 [fs_likelihood.fslikelihood] Computed log-likelihood = -852.158
 2023-07-02 10:33:40,880 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,880 [model] Posterior to be computed for parameters {'Omega_m': 0.32971730302333524, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,880 [prior] Evaluating prior at array([0.3297173 , 0.50839951])
 2023-07-02 10:33:40,881 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,881 [model] Got input parameters: {'Omega_m': 0.32971730302333524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,881 [classy] Got parameters {'Omega_m': 0.32971730302333524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,881 [classy] Computing new state
 2023-07-02 10:33:40,881 [classy] Setting parameters: {'Omega_m': 0.32971730302333524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:40,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2358093808039}
 2023-07-02 10:33:40,925 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:40,927 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0176621
 2023-07-02 10:33:40,927 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,927 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,946 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.60262
 2023-07-02 10:33:40,946 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 0.9383162136584628}
 2023-07-02 10:33:40,946 [prior] Evaluating prior at array([0.31329719, 0.93831621])
 2023-07-02 10:33:40,947 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,947 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9383162136584628, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,947 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,947 [classy] Re-using computed results
 2023-07-02 10:33:40,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
 2023-07-02 10:33:40,947 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:40,947 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9383162136584628, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,947 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:40,966 [fs_likelihood.fslikelihood] Computed log-likelihood = -761.674
 2023-07-02 10:33:40,966 [model] Computed derived parameters: {}
 2023-07-02 10:33:40,966 [model] Posterior to be computed for parameters {'Omega_m': 0.2925700401761634, 'b1': 0.5083995069720371}
 2023-07-02 10:33:40,966 [prior] Evaluating prior at array([0.29257004, 0.50839951])
 2023-07-02 10:33:40,966 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:40,966 [model] Got input parameters: {'Omega_m': 0.2925700401761634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:40,966 [classy] Got parameters {'Omega_m': 0.2925700401761634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:40,966 [classy] Computing new state
 2023-07-02 10:33:40,966 [classy] Setting parameters: {'Omega_m': 0.2925700401761634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.72642177302845}
 2023-07-02 10:33:41,011 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,012 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0257805
 2023-07-02 10:33:41,012 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,012 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,032 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.95645
 2023-07-02 10:33:41,033 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,033 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 1.1049067949901812}
 2023-07-02 10:33:41,033 [prior] Evaluating prior at array([0.31329719, 1.10490679])
 2023-07-02 10:33:41,033 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,033 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1049067949901812, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,033 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,033 [classy] Re-using computed results
 2023-07-02 10:33:41,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
 2023-07-02 10:33:41,033 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1049067949901812, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,033 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,053 [fs_likelihood.fslikelihood] Computed log-likelihood = -1680.98
 2023-07-02 10:33:41,053 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,053 [model] Posterior to be computed for parameters {'Omega_m': 0.31654590483335854, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,053 [prior] Evaluating prior at array([0.3165459 , 0.50839951])
 2023-07-02 10:33:41,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,053 [model] Got input parameters: {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,053 [classy] Got parameters {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,053 [classy] Computing new state
 2023-07-02 10:33:41,053 [classy] Setting parameters: {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77416695455352}
 2023-07-02 10:33:41,100 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,102 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00120401
 2023-07-02 10:33:41,102 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,102 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,126 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59469
 2023-07-02 10:33:41,127 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,127 [mcmc] New sample, #146:
   Omega_m:0.3132972, b1:0.5083995
 2023-07-02 10:33:41,127 [model] Posterior to be computed for parameters {'Omega_m': 0.31654590483335854, 'b1': 0.22505906937006553}
 2023-07-02 10:33:41,127 [prior] Evaluating prior at array([0.3165459 , 0.22505907])
 2023-07-02 10:33:41,127 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,127 [model] Got input parameters: {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.22505906937006553, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,127 [classy] Got parameters {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,127 [classy] Re-using computed results
 2023-07-02 10:33:41,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77416695455352}
 2023-07-02 10:33:41,127 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,127 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.22505906937006553, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,128 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.931
 2023-07-02 10:33:41,156 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3133330711121664, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,156 [prior] Evaluating prior at array([0.31333307, 0.50839951])
 2023-07-02 10:33:41,157 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,157 [model] Got input parameters: {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,157 [classy] Got parameters {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,157 [classy] Computing new state
 2023-07-02 10:33:41,157 [classy] Setting parameters: {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.15807323825592}
 2023-07-02 10:33:41,208 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,210 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000246523
 2023-07-02 10:33:41,210 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,210 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,233 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83885
 2023-07-02 10:33:41,233 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,233 [mcmc] New sample, #147:
   Omega_m:0.3165459, b1:0.5083995
 2023-07-02 10:33:41,233 [model] Posterior to be computed for parameters {'Omega_m': 0.3133330711121664, 'b1': 1.6851734476540072}
 2023-07-02 10:33:41,233 [prior] Evaluating prior at array([0.31333307, 1.68517345])
 2023-07-02 10:33:41,234 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,234 [model] Got input parameters: {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6851734476540072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,234 [classy] Got parameters {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,234 [classy] Re-using computed results
 2023-07-02 10:33:41,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.15807323825592}
 2023-07-02 10:33:41,234 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,234 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6851734476540072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,234 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,255 [fs_likelihood.fslikelihood] Computed log-likelihood = -10044
 2023-07-02 10:33:41,255 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,255 [model] Posterior to be computed for parameters {'Omega_m': 0.33407482004466765, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,255 [prior] Evaluating prior at array([0.33407482, 0.50839951])
 2023-07-02 10:33:41,255 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,255 [model] Got input parameters: {'Omega_m': 0.33407482004466765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,255 [classy] Got parameters {'Omega_m': 0.33407482004466765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,255 [classy] Computing new state
 2023-07-02 10:33:41,255 [classy] Setting parameters: {'Omega_m': 0.33407482004466765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.73906020998206}
 2023-07-02 10:33:41,304 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0273214
 2023-07-02 10:33:41,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,306 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,326 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.12254
 2023-07-02 10:33:41,326 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,326 [model] Posterior to be computed for parameters {'Omega_m': 0.3133330711121664, 'b1': -0.5370110503918133}
 2023-07-02 10:33:41,326 [prior] Evaluating prior at array([ 0.31333307, -0.53701105])
 2023-07-02 10:33:41,326 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:41,326 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,326 [prior] Evaluating prior at array([0.31532557, 0.50839951])
 2023-07-02 10:33:41,327 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,327 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,327 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,327 [classy] Computing new state
 2023-07-02 10:33:41,327 [classy] Setting parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
 2023-07-02 10:33:41,371 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,372 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000694146
 2023-07-02 10:33:41,372 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,372 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,393 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72345
 2023-07-02 10:33:41,393 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,393 [mcmc] New sample, #148:
   Omega_m:0.3133331, b1:0.5083995
 2023-07-02 10:33:41,394 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 1.4445425315185683}
 2023-07-02 10:33:41,394 [prior] Evaluating prior at array([0.31532557, 1.44454253])
 2023-07-02 10:33:41,394 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,394 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4445425315185683, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,394 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,394 [classy] Re-using computed results
 2023-07-02 10:33:41,394 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
 2023-07-02 10:33:41,394 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4445425315185683, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,394 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,414 [fs_likelihood.fslikelihood] Computed log-likelihood = -5441.92
 2023-07-02 10:33:41,414 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,414 [model] Posterior to be computed for parameters {'Omega_m': 0.3315404286579993, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,414 [prior] Evaluating prior at array([0.33154043, 0.50839951])
 2023-07-02 10:33:41,414 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,414 [model] Got input parameters: {'Omega_m': 0.3315404286579993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,414 [classy] Got parameters {'Omega_m': 0.3315404286579993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,414 [classy] Computing new state
 2023-07-02 10:33:41,414 [classy] Setting parameters: {'Omega_m': 0.3315404286579993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,459 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.02726263921818}
 2023-07-02 10:33:41,459 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,460 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0214575
 2023-07-02 10:33:41,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,480 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.58848
 2023-07-02 10:33:41,480 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,480 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.6456473276969827}
 2023-07-02 10:33:41,480 [prior] Evaluating prior at array([0.31532557, 0.64564733])
 2023-07-02 10:33:41,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,480 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6456473276969827, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,480 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,480 [classy] Re-using computed results
 2023-07-02 10:33:41,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
 2023-07-02 10:33:41,480 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6456473276969827, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,501 [fs_likelihood.fslikelihood] Computed log-likelihood = -63.3082
 2023-07-02 10:33:41,501 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,501 [model] Posterior to be computed for parameters {'Omega_m': 0.2995449599955176, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,501 [prior] Evaluating prior at array([0.29954496, 0.50839951])
 2023-07-02 10:33:41,501 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,501 [model] Got input parameters: {'Omega_m': 0.2995449599955176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,501 [classy] Got parameters {'Omega_m': 0.2995449599955176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,501 [classy] Computing new state
 2023-07-02 10:33:41,501 [classy] Setting parameters: {'Omega_m': 0.2995449599955176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.84626130589155}
 2023-07-02 10:33:41,545 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108085
 2023-07-02 10:33:41,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,547 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,567 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.41478
 2023-07-02 10:33:41,567 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,567 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': -0.2385144646084778}
 2023-07-02 10:33:41,567 [prior] Evaluating prior at array([ 0.31532557, -0.23851446])
 2023-07-02 10:33:41,567 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:41,567 [model] Posterior to be computed for parameters {'Omega_m': 0.3041229128029593, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,567 [prior] Evaluating prior at array([0.30412291, 0.50839951])
 2023-07-02 10:33:41,568 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,568 [model] Got input parameters: {'Omega_m': 0.3041229128029593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,568 [classy] Got parameters {'Omega_m': 0.3041229128029593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,568 [classy] Computing new state
 2023-07-02 10:33:41,568 [classy] Setting parameters: {'Omega_m': 0.3041229128029593, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.27830137061872}
 2023-07-02 10:33:41,612 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,614 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00458008
 2023-07-02 10:33:41,614 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,614 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,634 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84412
 2023-07-02 10:33:41,634 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,634 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.6825183886216427}
 2023-07-02 10:33:41,634 [prior] Evaluating prior at array([0.31532557, 0.68251839])
 2023-07-02 10:33:41,635 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,635 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6825183886216427, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,635 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,635 [classy] Re-using computed results
 2023-07-02 10:33:41,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
 2023-07-02 10:33:41,635 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6825183886216427, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,635 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,655 [fs_likelihood.fslikelihood] Computed log-likelihood = -104.735
 2023-07-02 10:33:41,655 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,655 [model] Posterior to be computed for parameters {'Omega_m': 0.305204922886048, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,655 [prior] Evaluating prior at array([0.30520492, 0.50839951])
 2023-07-02 10:33:41,655 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,655 [model] Got input parameters: {'Omega_m': 0.305204922886048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,655 [classy] Got parameters {'Omega_m': 0.305204922886048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,655 [classy] Computing new state
 2023-07-02 10:33:41,655 [classy] Setting parameters: {'Omega_m': 0.305204922886048, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1451618973536}
 2023-07-02 10:33:41,700 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00351136
 2023-07-02 10:33:41,702 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,702 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,721 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09125
 2023-07-02 10:33:41,721 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,721 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.8107538318824471}
 2023-07-02 10:33:41,721 [prior] Evaluating prior at array([0.31532557, 0.81075383])
 2023-07-02 10:33:41,721 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,721 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8107538318824471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,721 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,721 [classy] Re-using computed results
 2023-07-02 10:33:41,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
 2023-07-02 10:33:41,722 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,722 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8107538318824471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,722 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,742 [fs_likelihood.fslikelihood] Computed log-likelihood = -348.197
 2023-07-02 10:33:41,742 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,742 [model] Posterior to be computed for parameters {'Omega_m': 0.3114754754656021, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,742 [prior] Evaluating prior at array([0.31147548, 0.50839951])
 2023-07-02 10:33:41,742 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,742 [model] Got input parameters: {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,742 [classy] Got parameters {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,742 [classy] Computing new state
 2023-07-02 10:33:41,743 [classy] Setting parameters: {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,787 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.38165688019052}
 2023-07-02 10:33:41,787 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,789 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000264898
 2023-07-02 10:33:41,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,789 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,809 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.84052
 2023-07-02 10:33:41,809 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,809 [mcmc] New sample, #149:
   Omega_m:0.3153256, b1:0.5083995
 2023-07-02 10:33:41,809 [model] Posterior to be computed for parameters {'Omega_m': 0.3114754754656021, 'b1': 0.6988804167670525}
 2023-07-02 10:33:41,809 [prior] Evaluating prior at array([0.31147548, 0.69888042])
 2023-07-02 10:33:41,809 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,809 [model] Got input parameters: {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6988804167670525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,809 [classy] Got parameters {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,809 [classy] Re-using computed results
 2023-07-02 10:33:41,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.38165688019052}
 2023-07-02 10:33:41,809 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,809 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6988804167670525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,809 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,831 [fs_likelihood.fslikelihood] Computed log-likelihood = -116.695
 2023-07-02 10:33:41,831 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,831 [model] Posterior to be computed for parameters {'Omega_m': 0.3168658773965015, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,831 [prior] Evaluating prior at array([0.31686588, 0.50839951])
 2023-07-02 10:33:41,832 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,832 [model] Got input parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,832 [classy] Got parameters {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,832 [classy] Computing new state
 2023-07-02 10:33:41,832 [classy] Setting parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.73612504876297}
 2023-07-02 10:33:41,882 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,884 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00136708
 2023-07-02 10:33:41,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,884 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,908 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55363
 2023-07-02 10:33:41,908 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,908 [mcmc] New sample, #150:
   Omega_m:0.3114755, b1:0.5083995
 2023-07-02 10:33:41,908 [model] Posterior to be computed for parameters {'Omega_m': 0.3168658773965015, 'b1': 0.8142053456510582}
 2023-07-02 10:33:41,908 [prior] Evaluating prior at array([0.31686588, 0.81420535])
 2023-07-02 10:33:41,908 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,908 [model] Got input parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8142053456510582, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,908 [classy] Got parameters {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,908 [classy] Re-using computed results
 2023-07-02 10:33:41,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.73612504876297}
 2023-07-02 10:33:41,908 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:41,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8142053456510582, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,908 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:41,930 [fs_likelihood.fslikelihood] Computed log-likelihood = -365.192
 2023-07-02 10:33:41,930 [model] Computed derived parameters: {}
 2023-07-02 10:33:41,931 [model] Posterior to be computed for parameters {'Omega_m': 0.32471598044951794, 'b1': 0.5083995069720371}
 2023-07-02 10:33:41,931 [prior] Evaluating prior at array([0.32471598, 0.50839951])
 2023-07-02 10:33:41,931 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:41,931 [model] Got input parameters: {'Omega_m': 0.32471598044951794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,931 [classy] Got parameters {'Omega_m': 0.32471598044951794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:41,931 [classy] Computing new state
 2023-07-02 10:33:41,931 [classy] Setting parameters: {'Omega_m': 0.32471598044951794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:41,982 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.81336166604964}
 2023-07-02 10:33:41,982 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:41,985 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00910491
 2023-07-02 10:33:41,985 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:41,985 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.596353
 2023-07-02 10:33:42,007 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,007 [model] Posterior to be computed for parameters {'Omega_m': 0.3168658773965015, 'b1': 0.8186590456575431}
 2023-07-02 10:33:42,008 [prior] Evaluating prior at array([0.31686588, 0.81865905])
 2023-07-02 10:33:42,008 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,008 [model] Got input parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8186590456575431, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,008 [classy] Got parameters {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,008 [classy] Re-using computed results
 2023-07-02 10:33:42,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.73612504876297}
 2023-07-02 10:33:42,008 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8186590456575431, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,008 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -377.131
 2023-07-02 10:33:42,031 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,031 [model] Posterior to be computed for parameters {'Omega_m': 0.3147684261827027, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,031 [prior] Evaluating prior at array([0.31476843, 0.50839951])
 2023-07-02 10:33:42,031 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,031 [model] Got input parameters: {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,032 [classy] Got parameters {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,032 [classy] Computing new state
 2023-07-02 10:33:42,032 [classy] Setting parameters: {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,081 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9861199244786}
 2023-07-02 10:33:42,082 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,083 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000520692
 2023-07-02 10:33:42,084 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,084 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,106 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76756
 2023-07-02 10:33:42,106 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,106 [mcmc] New sample, #151:
   Omega_m:0.3168659, b1:0.5083995
 2023-07-02 10:33:42,106 [model] Posterior to be computed for parameters {'Omega_m': 0.3147684261827027, 'b1': 0.4834219915736692}
 2023-07-02 10:33:42,106 [prior] Evaluating prior at array([0.31476843, 0.48342199])
 2023-07-02 10:33:42,106 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,106 [model] Got input parameters: {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4834219915736692, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,106 [classy] Got parameters {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,106 [classy] Re-using computed results
 2023-07-02 10:33:42,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9861199244786}
 2023-07-02 10:33:42,106 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,106 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4834219915736692, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,106 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,131 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12869
 2023-07-02 10:33:42,131 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,132 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,132 [prior] Evaluating prior at array([0.3146766 , 0.50839951])
 2023-07-02 10:33:42,132 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,132 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,132 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,132 [classy] Computing new state
 2023-07-02 10:33:42,132 [classy] Setting parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,182 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
 2023-07-02 10:33:42,182 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,184 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000495683
 2023-07-02 10:33:42,184 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,184 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,205 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77395
 2023-07-02 10:33:42,205 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,205 [mcmc] New sample, #152:
   Omega_m:0.3147684, b1:0.5083995
 2023-07-02 10:33:42,206 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.15950987113664045}
 2023-07-02 10:33:42,206 [prior] Evaluating prior at array([0.3146766 , 0.15950987])
 2023-07-02 10:33:42,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,206 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15950987113664045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,206 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,206 [classy] Re-using computed results
 2023-07-02 10:33:42,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
 2023-07-02 10:33:42,206 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15950987113664045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,226 [fs_likelihood.fslikelihood] Computed log-likelihood = -216.464
 2023-07-02 10:33:42,226 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,226 [model] Posterior to be computed for parameters {'Omega_m': 0.3254489108874341, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,226 [prior] Evaluating prior at array([0.32544891, 0.50839951])
 2023-07-02 10:33:42,227 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,227 [model] Got input parameters: {'Omega_m': 0.3254489108874341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,227 [classy] Got parameters {'Omega_m': 0.3254489108874341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,227 [classy] Computing new state
 2023-07-02 10:33:42,227 [classy] Setting parameters: {'Omega_m': 0.3254489108874341, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.72822557366604}
 2023-07-02 10:33:42,273 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0101861
 2023-07-02 10:33:42,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,275 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,296 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.320436
 2023-07-02 10:33:42,296 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,296 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': -0.7624827321094867}
 2023-07-02 10:33:42,296 [prior] Evaluating prior at array([ 0.3146766 , -0.76248273])
 2023-07-02 10:33:42,296 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:42,296 [model] Posterior to be computed for parameters {'Omega_m': 0.3153126945062122, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,296 [prior] Evaluating prior at array([0.31531269, 0.50839951])
 2023-07-02 10:33:42,297 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,297 [model] Got input parameters: {'Omega_m': 0.3153126945062122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,297 [classy] Got parameters {'Omega_m': 0.3153126945062122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,297 [classy] Computing new state
 2023-07-02 10:33:42,297 [classy] Setting parameters: {'Omega_m': 0.3153126945062122, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,342 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9211055838606}
 2023-07-02 10:33:42,342 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,344 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000689712
 2023-07-02 10:33:42,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,344 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72457
 2023-07-02 10:33:42,364 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,364 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.18135163864203013}
 2023-07-02 10:33:42,364 [prior] Evaluating prior at array([0.3146766 , 0.18135164])
 2023-07-02 10:33:42,364 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,364 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.18135163864203013, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,364 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,364 [classy] Re-using computed results
 2023-07-02 10:33:42,364 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
 2023-07-02 10:33:42,365 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.18135163864203013, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,365 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,384 [fs_likelihood.fslikelihood] Computed log-likelihood = -193.932
 2023-07-02 10:33:42,384 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,384 [model] Posterior to be computed for parameters {'Omega_m': 0.33756082270622256, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,384 [prior] Evaluating prior at array([0.33756082, 0.50839951])
 2023-07-02 10:33:42,384 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,384 [model] Got input parameters: {'Omega_m': 0.33756082270622256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,384 [classy] Got parameters {'Omega_m': 0.33756082270622256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,384 [classy] Computing new state
 2023-07-02 10:33:42,384 [classy] Setting parameters: {'Omega_m': 0.33756082270622256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.34584754707868}
 2023-07-02 10:33:42,429 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0364832
 2023-07-02 10:33:42,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,431 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,451 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.54345
 2023-07-02 10:33:42,451 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,451 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.6612434972353614}
 2023-07-02 10:33:42,452 [prior] Evaluating prior at array([0.3146766, 0.6612435])
 2023-07-02 10:33:42,452 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,452 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6612434972353614, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,452 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,452 [classy] Re-using computed results
 2023-07-02 10:33:42,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
 2023-07-02 10:33:42,452 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6612434972353614, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,452 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -78.1031
 2023-07-02 10:33:42,471 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,472 [model] Posterior to be computed for parameters {'Omega_m': 0.31329504702485694, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,472 [prior] Evaluating prior at array([0.31329505, 0.50839951])
 2023-07-02 10:33:42,472 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,472 [model] Got input parameters: {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,472 [classy] Got parameters {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,472 [classy] Computing new state
 2023-07-02 10:33:42,472 [classy] Setting parameters: {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16264176106117}
 2023-07-02 10:33:42,517 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,519 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000242646
 2023-07-02 10:33:42,519 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,519 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,538 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83991
 2023-07-02 10:33:42,538 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,538 [mcmc] New sample, #153:
   Omega_m:0.3146766, b1:0.5083995
 2023-07-02 10:33:42,538 [model] Posterior to be computed for parameters {'Omega_m': 0.31329504702485694, 'b1': 0.12986138097374478}
 2023-07-02 10:33:42,539 [prior] Evaluating prior at array([0.31329505, 0.12986138])
 2023-07-02 10:33:42,539 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,539 [model] Got input parameters: {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.12986138097374478, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,539 [classy] Got parameters {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,539 [classy] Re-using computed results
 2023-07-02 10:33:42,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16264176106117}
 2023-07-02 10:33:42,539 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.12986138097374478, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,539 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,559 [fs_likelihood.fslikelihood] Computed log-likelihood = -250.347
 2023-07-02 10:33:42,559 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,559 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,560 [prior] Evaluating prior at array([0.3109464 , 0.50839951])
 2023-07-02 10:33:42,560 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,560 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,560 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,560 [classy] Computing new state
 2023-07-02 10:33:42,560 [classy] Setting parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
 2023-07-02 10:33:42,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000347912
 2023-07-02 10:33:42,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,613 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,637 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82229
 2023-07-02 10:33:42,637 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,637 [mcmc] New sample, #154:
   Omega_m:0.313295, b1:0.5083995
 2023-07-02 10:33:42,637 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': -0.2155186563176278}
 2023-07-02 10:33:42,637 [prior] Evaluating prior at array([ 0.3109464 , -0.21551866])
 2023-07-02 10:33:42,637 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:42,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3241053680582019, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,637 [prior] Evaluating prior at array([0.32410537, 0.50839951])
 2023-07-02 10:33:42,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,637 [model] Got input parameters: {'Omega_m': 0.3241053680582019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,637 [classy] Got parameters {'Omega_m': 0.3241053680582019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,638 [classy] Computing new state
 2023-07-02 10:33:42,638 [classy] Setting parameters: {'Omega_m': 0.3241053680582019, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,693 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8844211891672}
 2023-07-02 10:33:42,693 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,695 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00825013
 2023-07-02 10:33:42,695 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,695 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,723 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.814071
 2023-07-02 10:33:42,723 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,723 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 0.8237891926851358}
 2023-07-02 10:33:42,723 [prior] Evaluating prior at array([0.3109464 , 0.82378919])
 2023-07-02 10:33:42,723 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,723 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8237891926851358, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,724 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,724 [classy] Re-using computed results
 2023-07-02 10:33:42,724 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
 2023-07-02 10:33:42,724 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8237891926851358, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,724 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,749 [fs_likelihood.fslikelihood] Computed log-likelihood = -359.672
 2023-07-02 10:33:42,749 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,750 [model] Posterior to be computed for parameters {'Omega_m': 0.3290164248720366, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,750 [prior] Evaluating prior at array([0.32901642, 0.50839951])
 2023-07-02 10:33:42,750 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,750 [model] Got input parameters: {'Omega_m': 0.3290164248720366, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,750 [classy] Got parameters {'Omega_m': 0.3290164248720366, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,750 [classy] Computing new state
 2023-07-02 10:33:42,750 [classy] Setting parameters: {'Omega_m': 0.3290164248720366, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31626900889293}
 2023-07-02 10:33:42,807 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,810 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0162978
 2023-07-02 10:33:42,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,810 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,833 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.24981
 2023-07-02 10:33:42,833 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,834 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 0.24609791895381977}
 2023-07-02 10:33:42,834 [prior] Evaluating prior at array([0.3109464 , 0.24609792])
 2023-07-02 10:33:42,834 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,834 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24609791895381977, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,834 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,834 [classy] Re-using computed results
 2023-07-02 10:33:42,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
 2023-07-02 10:33:42,834 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24609791895381977, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,834 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,858 [fs_likelihood.fslikelihood] Computed log-likelihood = -137.187
 2023-07-02 10:33:42,858 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,858 [model] Posterior to be computed for parameters {'Omega_m': 0.3043396985082412, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,858 [prior] Evaluating prior at array([0.3043397 , 0.50839951])
 2023-07-02 10:33:42,858 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,859 [model] Got input parameters: {'Omega_m': 0.3043396985082412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,859 [classy] Got parameters {'Omega_m': 0.3043396985082412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,859 [classy] Computing new state
 2023-07-02 10:33:42,859 [classy] Setting parameters: {'Omega_m': 0.3043396985082412, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:42,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2515933016373}
 2023-07-02 10:33:42,911 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:42,913 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00435376
 2023-07-02 10:33:42,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,913 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,935 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.89641
 2023-07-02 10:33:42,935 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,935 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 1.190385110524115}
 2023-07-02 10:33:42,935 [prior] Evaluating prior at array([0.3109464 , 1.19038511])
 2023-07-02 10:33:42,935 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,935 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.190385110524115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,935 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,935 [classy] Re-using computed results
 2023-07-02 10:33:42,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
 2023-07-02 10:33:42,935 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:42,935 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.190385110524115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,935 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:42,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -2306.37
 2023-07-02 10:33:42,958 [model] Computed derived parameters: {}
 2023-07-02 10:33:42,958 [model] Posterior to be computed for parameters {'Omega_m': 0.3069555960819579, 'b1': 0.5083995069720371}
 2023-07-02 10:33:42,958 [prior] Evaluating prior at array([0.3069556 , 0.50839951])
 2023-07-02 10:33:42,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:42,958 [model] Got input parameters: {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:42,958 [classy] Got parameters {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:42,958 [classy] Computing new state
 2023-07-02 10:33:42,958 [classy] Setting parameters: {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,007 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93061852761033}
 2023-07-02 10:33:43,008 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,009 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00210274
 2023-07-02 10:33:43,009 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,009 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,031 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41764
 2023-07-02 10:33:43,031 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,031 [mcmc] New sample, #155:
   Omega_m:0.3109464, b1:0.5083995
 2023-07-02 10:33:43,031 [model] Posterior to be computed for parameters {'Omega_m': 0.3069555960819579, 'b1': 0.15817117907705347}
 2023-07-02 10:33:43,031 [prior] Evaluating prior at array([0.3069556 , 0.15817118])
 2023-07-02 10:33:43,031 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,031 [model] Got input parameters: {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15817117907705347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,031 [classy] Got parameters {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,031 [classy] Re-using computed results
 2023-07-02 10:33:43,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93061852761033}
 2023-07-02 10:33:43,031 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,031 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15817117907705347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,031 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,052 [fs_likelihood.fslikelihood] Computed log-likelihood = -231.442
 2023-07-02 10:33:43,052 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,052 [model] Posterior to be computed for parameters {'Omega_m': 0.3190647991072347, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,052 [prior] Evaluating prior at array([0.3190648 , 0.50839951])
 2023-07-02 10:33:43,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,053 [model] Got input parameters: {'Omega_m': 0.3190647991072347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,053 [classy] Got parameters {'Omega_m': 0.3190647991072347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,053 [classy] Computing new state
 2023-07-02 10:33:43,053 [classy] Setting parameters: {'Omega_m': 0.3190647991072347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47561356146335}
 2023-07-02 10:33:43,101 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,102 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00281489
 2023-07-02 10:33:43,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,103 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,127 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18942
 2023-07-02 10:33:43,127 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,127 [mcmc] New sample, #156:
   Omega_m:0.3069556, b1:0.5083995
 2023-07-02 10:33:43,127 [model] Posterior to be computed for parameters {'Omega_m': 0.3190647991072347, 'b1': -3.1786251557452827}
 2023-07-02 10:33:43,127 [prior] Evaluating prior at array([ 0.3190648 , -3.17862516])
 2023-07-02 10:33:43,128 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:43,128 [model] Posterior to be computed for parameters {'Omega_m': 0.317049612631892, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,128 [prior] Evaluating prior at array([0.31704961, 0.50839951])
 2023-07-02 10:33:43,128 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,128 [model] Got input parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,128 [classy] Got parameters {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,128 [classy] Computing new state
 2023-07-02 10:33:43,128 [classy] Setting parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,177 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.714295501389}
 2023-07-02 10:33:43,177 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,179 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00146622
 2023-07-02 10:33:43,179 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,179 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,200 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52868
 2023-07-02 10:33:43,201 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,201 [mcmc] New sample, #157:
   Omega_m:0.3190648, b1:0.5083995
 2023-07-02 10:33:43,201 [model] Posterior to be computed for parameters {'Omega_m': 0.317049612631892, 'b1': 1.1934596823028492}
 2023-07-02 10:33:43,201 [prior] Evaluating prior at array([0.31704961, 1.19345968])
 2023-07-02 10:33:43,201 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,201 [model] Got input parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1934596823028492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,201 [classy] Got parameters {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,201 [classy] Re-using computed results
 2023-07-02 10:33:43,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.714295501389}
 2023-07-02 10:33:43,201 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,201 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1934596823028492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,201 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,223 [fs_likelihood.fslikelihood] Computed log-likelihood = -2451.94
 2023-07-02 10:33:43,223 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,223 [model] Posterior to be computed for parameters {'Omega_m': 0.3314450543964287, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,223 [prior] Evaluating prior at array([0.33144505, 0.50839951])
 2023-07-02 10:33:43,223 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,223 [model] Got input parameters: {'Omega_m': 0.3314450543964287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,223 [classy] Got parameters {'Omega_m': 0.3314450543964287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,223 [classy] Computing new state
 2023-07-02 10:33:43,223 [classy] Setting parameters: {'Omega_m': 0.3314450543964287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.03814689272636}
 2023-07-02 10:33:43,271 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,272 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0212502
 2023-07-02 10:33:43,273 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,273 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,293 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.53447
 2023-07-02 10:33:43,293 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,293 [model] Posterior to be computed for parameters {'Omega_m': 0.317049612631892, 'b1': 0.28957844454413706}
 2023-07-02 10:33:43,293 [prior] Evaluating prior at array([0.31704961, 0.28957844])
 2023-07-02 10:33:43,293 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,293 [model] Got input parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.28957844454413706, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,293 [classy] Got parameters {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,293 [classy] Re-using computed results
 2023-07-02 10:33:43,293 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.714295501389}
 2023-07-02 10:33:43,293 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,293 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.28957844454413706, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,294 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,314 [fs_likelihood.fslikelihood] Computed log-likelihood = -90.5572
 2023-07-02 10:33:43,314 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,314 [model] Posterior to be computed for parameters {'Omega_m': 0.31506985853788355, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,314 [prior] Evaluating prior at array([0.31506986, 0.50839951])
 2023-07-02 10:33:43,314 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,314 [model] Got input parameters: {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,315 [classy] Got parameters {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,315 [classy] Computing new state
 2023-07-02 10:33:43,315 [classy] Setting parameters: {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9501002306261}
 2023-07-02 10:33:43,361 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000609901
 2023-07-02 10:33:43,362 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,362 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,382 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74483
 2023-07-02 10:33:43,382 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,382 [mcmc] New sample, #158:
   Omega_m:0.3170496, b1:0.5083995
 2023-07-02 10:33:43,382 [model] Posterior to be computed for parameters {'Omega_m': 0.31506985853788355, 'b1': 0.06995420839207989}
 2023-07-02 10:33:43,382 [prior] Evaluating prior at array([0.31506986, 0.06995421])
 2023-07-02 10:33:43,383 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,383 [model] Got input parameters: {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.06995420839207989, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,383 [classy] Got parameters {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,383 [classy] Re-using computed results
 2023-07-02 10:33:43,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9501002306261}
 2023-07-02 10:33:43,383 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,383 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.06995420839207989, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,383 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,403 [fs_likelihood.fslikelihood] Computed log-likelihood = -313.113
 2023-07-02 10:33:43,403 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,403 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,403 [prior] Evaluating prior at array([0.31637922, 0.50839951])
 2023-07-02 10:33:43,403 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,403 [model] Got input parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,403 [classy] Got parameters {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,403 [classy] Computing new state
 2023-07-02 10:33:43,403 [classy] Setting parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,449 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79399745211575}
 2023-07-02 10:33:43,449 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,450 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00112389
 2023-07-02 10:33:43,451 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,451 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,470 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61488
 2023-07-02 10:33:43,470 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,470 [mcmc] New sample, #159:
   Omega_m:0.3150699, b1:0.5083995
 2023-07-02 10:33:43,470 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': 0.21964820899395604}
 2023-07-02 10:33:43,470 [prior] Evaluating prior at array([0.31637922, 0.21964821])
 2023-07-02 10:33:43,470 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,471 [model] Got input parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.21964820899395604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,471 [classy] Got parameters {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,471 [classy] Re-using computed results
 2023-07-02 10:33:43,471 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79399745211575}
 2023-07-02 10:33:43,471 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,471 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.21964820899395604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,471 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -153.331
 2023-07-02 10:33:43,490 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,490 [model] Posterior to be computed for parameters {'Omega_m': 0.3323390033146361, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,490 [prior] Evaluating prior at array([0.332339  , 0.50839951])
 2023-07-02 10:33:43,490 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,490 [model] Got input parameters: {'Omega_m': 0.3323390033146361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,490 [classy] Got parameters {'Omega_m': 0.3323390033146361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,491 [classy] Computing new state
 2023-07-02 10:33:43,491 [classy] Setting parameters: {'Omega_m': 0.3323390033146361, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,535 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.93623813445927}
 2023-07-02 10:33:43,535 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,537 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0232319
 2023-07-02 10:33:43,537 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,537 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,556 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.05133
 2023-07-02 10:33:43,556 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,556 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': -0.11038986594972411}
 2023-07-02 10:33:43,556 [prior] Evaluating prior at array([ 0.31637922, -0.11038987])
 2023-07-02 10:33:43,557 [prior] Got logpriors (internal) = -inf
 2023-07-02 10:33:43,557 [model] Posterior to be computed for parameters {'Omega_m': 0.3024856187765864, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,557 [prior] Evaluating prior at array([0.30248562, 0.50839951])
 2023-07-02 10:33:43,557 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,557 [model] Got input parameters: {'Omega_m': 0.3024856187765864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,557 [classy] Got parameters {'Omega_m': 0.3024856187765864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,557 [classy] Computing new state
 2023-07-02 10:33:43,557 [classy] Setting parameters: {'Omega_m': 0.3024856187765864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4805602396071}
 2023-07-02 10:33:43,602 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,604 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00648829
 2023-07-02 10:33:43,604 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,604 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,624 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.40423
 2023-07-02 10:33:43,624 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,624 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': 2.01208020692284}
 2023-07-02 10:33:43,624 [prior] Evaluating prior at array([0.31637922, 2.01208021])
 2023-07-02 10:33:43,624 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,624 [model] Got input parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.01208020692284, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,624 [classy] Got parameters {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,624 [classy] Re-using computed results
 2023-07-02 10:33:43,624 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79399745211575}
 2023-07-02 10:33:43,624 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,624 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.01208020692284, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,624 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,644 [fs_likelihood.fslikelihood] Computed log-likelihood = -20601.1
 2023-07-02 10:33:43,644 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,644 [model] Posterior to be computed for parameters {'Omega_m': 0.3136104366949477, 'b1': 0.5083995069720371}
 2023-07-02 10:33:43,644 [prior] Evaluating prior at array([0.31361044, 0.50839951])
 2023-07-02 10:33:43,644 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,644 [model] Got input parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,644 [classy] Got parameters {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,644 [classy] Computing new state
 2023-07-02 10:33:43,644 [classy] Setting parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12479302532236}
 2023-07-02 10:33:43,688 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,690 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00028
 2023-07-02 10:33:43,690 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,690 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,710 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82984
 2023-07-02 10:33:43,710 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,710 [mcmc] New sample, #160:
   Omega_m:0.3163792, b1:0.5083995
 2023-07-02 10:33:43,710 [mcmc] Learn + convergence test @ 160 samples accepted.
 2023-07-02 10:33:43,710 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:33:43,715 [mcmc]  - Acceptance rate: 0.232
 2023-07-02 10:33:43,716 [mcmc]  - Condition number = 12.6013
 2023-07-02 10:33:43,716 [mcmc]  - Eigenvalues = array([0.14963695, 1.88561463])
 2023-07-02 10:33:43,716 [mcmc]  - Convergence of means: R-1 = 1.885615 after 128 accepted steps
 2023-07-02 10:33:43,716 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:33:43,716 [mcmc] array([[ 3.43794894e-05, -2.33629757e-05],
       [-2.33629757e-05,  8.02724856e-05]])
 2023-07-02 10:33:43,726 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:33:43,726 [model] Posterior to be computed for parameters {'Omega_m': 0.3136104366949477, 'b1': 0.5197917763701246}
 2023-07-02 10:33:43,726 [prior] Evaluating prior at array([0.31361044, 0.51979178])
 2023-07-02 10:33:43,726 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,726 [model] Got input parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5197917763701246, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,726 [classy] Got parameters {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,727 [classy] Re-using computed results
 2023-07-02 10:33:43,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12479302532236}
 2023-07-02 10:33:43,727 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5197917763701246, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,727 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,747 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12855
 2023-07-02 10:33:43,747 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,747 [model] Posterior to be computed for parameters {'Omega_m': 0.2878657114872602, 'b1': 0.5258946298130794}
 2023-07-02 10:33:43,747 [prior] Evaluating prior at array([0.28786571, 0.52589463])
 2023-07-02 10:33:43,747 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,747 [model] Got input parameters: {'Omega_m': 0.2878657114872602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5258946298130794, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,747 [classy] Got parameters {'Omega_m': 0.2878657114872602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,747 [classy] Computing new state
 2023-07-02 10:33:43,747 [classy] Setting parameters: {'Omega_m': 0.2878657114872602, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.33038859203214}
 2023-07-02 10:33:43,794 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,795 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0397724
 2023-07-02 10:33:43,796 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5258946298130794, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,796 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,816 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21648
 2023-07-02 10:33:43,816 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,816 [model] Posterior to be computed for parameters {'Omega_m': 0.3136104366949477, 'b1': 0.4906071623484306}
 2023-07-02 10:33:43,816 [prior] Evaluating prior at array([0.31361044, 0.49060716])
 2023-07-02 10:33:43,816 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,816 [model] Got input parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906071623484306, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,816 [classy] Got parameters {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,816 [classy] Re-using computed results
 2023-07-02 10:33:43,817 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12479302532236}
 2023-07-02 10:33:43,817 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,817 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906071623484306, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,817 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,837 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51259
 2023-07-02 10:33:43,837 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,837 [mcmc] New sample, #161:
   Omega_m:0.3136104, b1:0.5083995
 2023-07-02 10:33:43,837 [model] Posterior to be computed for parameters {'Omega_m': 0.2900151599397835, 'b1': 0.5066416028782804}
 2023-07-02 10:33:43,837 [prior] Evaluating prior at array([0.29001516, 0.5066416 ])
 2023-07-02 10:33:43,837 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,837 [model] Got input parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066416028782804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,837 [classy] Got parameters {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,837 [classy] Computing new state
 2023-07-02 10:33:43,837 [classy] Setting parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05338333616066}
 2023-07-02 10:33:43,884 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,886 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0329808
 2023-07-02 10:33:43,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066416028782804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,886 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,906 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.88462
 2023-07-02 10:33:43,906 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,906 [mcmc] New sample, #162:
   Omega_m:0.3136104, b1:0.4906072
 2023-07-02 10:33:43,906 [model] Posterior to be computed for parameters {'Omega_m': 0.2900151599397835, 'b1': 0.5066198345083764}
 2023-07-02 10:33:43,906 [prior] Evaluating prior at array([0.29001516, 0.50661983])
 2023-07-02 10:33:43,906 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,906 [model] Got input parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066198345083764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,906 [classy] Got parameters {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,906 [classy] Re-using computed results
 2023-07-02 10:33:43,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05338333616066}
 2023-07-02 10:33:43,906 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066198345083764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,907 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,927 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.88883
 2023-07-02 10:33:43,927 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,927 [mcmc] New sample, #163:
   Omega_m:0.2900152, b1:0.5066416
 2023-07-02 10:33:43,927 [model] Posterior to be computed for parameters {'Omega_m': 0.2778878170618393, 'b1': 0.5148611092422671}
 2023-07-02 10:33:43,927 [prior] Evaluating prior at array([0.27788782, 0.51486111])
 2023-07-02 10:33:43,927 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,927 [model] Got input parameters: {'Omega_m': 0.2778878170618393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5148611092422671, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,927 [classy] Got parameters {'Omega_m': 0.2778878170618393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,927 [classy] Computing new state
 2023-07-02 10:33:43,927 [classy] Setting parameters: {'Omega_m': 0.2778878170618393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:43,973 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.64020303021948}
 2023-07-02 10:33:43,973 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:43,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0804355
 2023-07-02 10:33:43,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5148611092422671, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,975 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:43,995 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.0431
 2023-07-02 10:33:43,995 [model] Computed derived parameters: {}
 2023-07-02 10:33:43,995 [model] Posterior to be computed for parameters {'Omega_m': 0.2900151599397835, 'b1': 0.5117476044977189}
 2023-07-02 10:33:43,995 [prior] Evaluating prior at array([0.29001516, 0.5117476 ])
 2023-07-02 10:33:43,995 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:43,995 [model] Got input parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117476044977189, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,995 [classy] Got parameters {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:43,995 [classy] Re-using computed results
 2023-07-02 10:33:43,995 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05338333616066}
 2023-07-02 10:33:43,995 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:43,995 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117476044977189, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:43,995 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,015 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.95841
 2023-07-02 10:33:44,015 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,015 [mcmc] New sample, #164:
   Omega_m:0.2900152, b1:0.5066198
 2023-07-02 10:33:44,015 [model] Posterior to be computed for parameters {'Omega_m': 0.30982317975064466, 'b1': 0.49828683779567867}
 2023-07-02 10:33:44,015 [prior] Evaluating prior at array([0.30982318, 0.49828684])
 2023-07-02 10:33:44,015 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,015 [model] Got input parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49828683779567867, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,015 [classy] Got parameters {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,015 [classy] Computing new state
 2023-07-02 10:33:44,015 [classy] Setting parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58151616141933}
 2023-07-02 10:33:44,060 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000639447
 2023-07-02 10:33:44,062 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49828683779567867, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,062 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,082 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4126
 2023-07-02 10:33:44,082 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,082 [mcmc] New sample, #165:
   Omega_m:0.2900152, b1:0.5117476
 2023-07-02 10:33:44,082 [model] Posterior to be computed for parameters {'Omega_m': 0.30982317975064466, 'b1': 0.47652149315782333}
 2023-07-02 10:33:44,082 [prior] Evaluating prior at array([0.30982318, 0.47652149])
 2023-07-02 10:33:44,082 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,082 [model] Got input parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47652149315782333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,082 [classy] Got parameters {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,082 [classy] Re-using computed results
 2023-07-02 10:33:44,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58151616141933}
 2023-07-02 10:33:44,082 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47652149315782333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,083 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,102 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.103254
 2023-07-02 10:33:44,102 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,102 [model] Posterior to be computed for parameters {'Omega_m': 0.3378137036994859, 'b1': 0.4792655567014105}
 2023-07-02 10:33:44,102 [prior] Evaluating prior at array([0.3378137 , 0.47926556])
 2023-07-02 10:33:44,102 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,102 [model] Got input parameters: {'Omega_m': 0.3378137036994859, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4792655567014105, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,102 [classy] Got parameters {'Omega_m': 0.3378137036994859, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,102 [classy] Computing new state
 2023-07-02 10:33:44,102 [classy] Setting parameters: {'Omega_m': 0.3378137036994859, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.31746913060147}
 2023-07-02 10:33:44,149 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,150 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0371962
 2023-07-02 10:33:44,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4792655567014105, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,150 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,170 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.8372
 2023-07-02 10:33:44,170 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,171 [model] Posterior to be computed for parameters {'Omega_m': 0.30982317975064466, 'b1': 0.5015484195655898}
 2023-07-02 10:33:44,171 [prior] Evaluating prior at array([0.30982318, 0.50154842])
 2023-07-02 10:33:44,171 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,171 [model] Got input parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015484195655898, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,171 [classy] Got parameters {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,171 [classy] Re-using computed results
 2023-07-02 10:33:44,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58151616141933}
 2023-07-02 10:33:44,171 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015484195655898, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,171 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58208
 2023-07-02 10:33:44,190 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,190 [mcmc] New sample, #166:
   Omega_m:0.3098232, b1:0.4982868
 2023-07-02 10:33:44,190 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.4943827694473789}
 2023-07-02 10:33:44,190 [prior] Evaluating prior at array([0.3203677 , 0.49438277])
 2023-07-02 10:33:44,190 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,191 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943827694473789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,191 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,191 [classy] Computing new state
 2023-07-02 10:33:44,191 [classy] Setting parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
 2023-07-02 10:33:44,236 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00393985
 2023-07-02 10:33:44,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943827694473789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,237 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,257 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74057
 2023-07-02 10:33:44,257 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,257 [mcmc] New sample, #167:
   Omega_m:0.3098232, b1:0.5015484
 2023-07-02 10:33:44,257 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.510781737072457}
 2023-07-02 10:33:44,257 [prior] Evaluating prior at array([0.3203677 , 0.51078174])
 2023-07-02 10:33:44,257 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,257 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510781737072457, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,257 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,257 [classy] Re-using computed results
 2023-07-02 10:33:44,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
 2023-07-02 10:33:44,257 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510781737072457, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,257 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,277 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65387
 2023-07-02 10:33:44,277 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,277 [model] Posterior to be computed for parameters {'Omega_m': 0.3389682897500448, 'b1': 0.4817425262984541}
 2023-07-02 10:33:44,277 [prior] Evaluating prior at array([0.33896829, 0.48174253])
 2023-07-02 10:33:44,277 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,277 [model] Got input parameters: {'Omega_m': 0.3389682897500448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4817425262984541, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,278 [classy] Got parameters {'Omega_m': 0.3389682897500448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,278 [classy] Computing new state
 2023-07-02 10:33:44,278 [classy] Setting parameters: {'Omega_m': 0.3389682897500448, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.18813249827744}
 2023-07-02 10:33:44,322 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0405352
 2023-07-02 10:33:44,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4817425262984541, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,324 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,344 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.68274
 2023-07-02 10:33:44,344 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,344 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.48397660130391973}
 2023-07-02 10:33:44,344 [prior] Evaluating prior at array([0.3203677, 0.4839766])
 2023-07-02 10:33:44,344 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,344 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48397660130391973, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,344 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,344 [classy] Re-using computed results
 2023-07-02 10:33:44,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
 2023-07-02 10:33:44,344 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48397660130391973, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,344 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,363 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66107
 2023-07-02 10:33:44,363 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,364 [mcmc] New sample, #168:
   Omega_m:0.3203677, b1:0.4943828
 2023-07-02 10:33:44,364 [model] Posterior to be computed for parameters {'Omega_m': 0.30855563200350583, 'b1': 0.49200362800953573}
 2023-07-02 10:33:44,364 [prior] Evaluating prior at array([0.30855563, 0.49200363])
 2023-07-02 10:33:44,364 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,364 [model] Got input parameters: {'Omega_m': 0.30855563200350583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49200362800953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,364 [classy] Got parameters {'Omega_m': 0.30855563200350583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,364 [classy] Computing new state
 2023-07-02 10:33:44,364 [classy] Setting parameters: {'Omega_m': 0.30855563200350583, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73547777731642}
 2023-07-02 10:33:44,409 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,410 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00115809
 2023-07-02 10:33:44,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49200362800953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,410 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61687
 2023-07-02 10:33:44,430 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,431 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.49544414984810053}
 2023-07-02 10:33:44,431 [prior] Evaluating prior at array([0.3203677 , 0.49544415])
 2023-07-02 10:33:44,431 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,431 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49544414984810053, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,431 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,431 [classy] Re-using computed results
 2023-07-02 10:33:44,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
 2023-07-02 10:33:44,431 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49544414984810053, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,431 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,450 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71563
 2023-07-02 10:33:44,450 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,450 [mcmc] New sample, #169:
   Omega_m:0.3203677, b1:0.4839766
 2023-07-02 10:33:44,450 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.4935255503340473}
 2023-07-02 10:33:44,451 [prior] Evaluating prior at array([0.32319099, 0.49352555])
 2023-07-02 10:33:44,451 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,451 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935255503340473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,451 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,451 [classy] Computing new state
 2023-07-02 10:33:44,451 [classy] Setting parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
 2023-07-02 10:33:44,495 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,497 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00704875
 2023-07-02 10:33:44,497 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935255503340473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,497 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,516 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4019
 2023-07-02 10:33:44,516 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,516 [mcmc] New sample, #170:
   Omega_m:0.3203677, b1:0.4954441
 2023-07-02 10:33:44,516 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.48343679506057297}
 2023-07-02 10:33:44,516 [prior] Evaluating prior at array([0.32319099, 0.4834368 ])
 2023-07-02 10:33:44,517 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,517 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48343679506057297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,517 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,517 [classy] Re-using computed results
 2023-07-02 10:33:44,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
 2023-07-02 10:33:44,517 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48343679506057297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,517 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56754
 2023-07-02 10:33:44,536 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,536 [mcmc] New sample, #171:
   Omega_m:0.323191, b1:0.4935256
 2023-07-02 10:33:44,537 [model] Posterior to be computed for parameters {'Omega_m': 0.3354184846828529, 'b1': 0.4751274621111435}
 2023-07-02 10:33:44,537 [prior] Evaluating prior at array([0.33541848, 0.47512746])
 2023-07-02 10:33:44,537 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,537 [model] Got input parameters: {'Omega_m': 0.3354184846828529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4751274621111435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,537 [classy] Got parameters {'Omega_m': 0.3354184846828529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,537 [classy] Computing new state
 2023-07-02 10:33:44,537 [classy] Setting parameters: {'Omega_m': 0.3354184846828529, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.58706332752652}
 2023-07-02 10:33:44,581 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0307037
 2023-07-02 10:33:44,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4751274621111435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,583 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,603 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.430199
 2023-07-02 10:33:44,603 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,603 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.4951233870941862}
 2023-07-02 10:33:44,603 [prior] Evaluating prior at array([0.32319099, 0.49512339])
 2023-07-02 10:33:44,603 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,603 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4951233870941862, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,603 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,603 [classy] Re-using computed results
 2023-07-02 10:33:44,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
 2023-07-02 10:33:44,603 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4951233870941862, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,603 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,623 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32414
 2023-07-02 10:33:44,623 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,623 [mcmc] New sample, #172:
   Omega_m:0.323191, b1:0.4834368
 2023-07-02 10:33:44,623 [model] Posterior to be computed for parameters {'Omega_m': 0.28310417002271976, 'b1': 0.5223648457706341}
 2023-07-02 10:33:44,623 [prior] Evaluating prior at array([0.28310417, 0.52236485])
 2023-07-02 10:33:44,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,623 [model] Got input parameters: {'Omega_m': 0.28310417002271976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5223648457706341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,623 [classy] Got parameters {'Omega_m': 0.28310417002271976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,623 [classy] Computing new state
 2023-07-02 10:33:44,623 [classy] Setting parameters: {'Omega_m': 0.28310417002271976, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.95049170254995}
 2023-07-02 10:33:44,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0572693
 2023-07-02 10:33:44,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5223648457706341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,669 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,688 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.91928
 2023-07-02 10:33:44,688 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,688 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.4838398183623971}
 2023-07-02 10:33:44,689 [prior] Evaluating prior at array([0.32319099, 0.48383982])
 2023-07-02 10:33:44,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,689 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4838398183623971, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,689 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,689 [classy] Re-using computed results
 2023-07-02 10:33:44,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
 2023-07-02 10:33:44,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4838398183623971, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,708 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57158
 2023-07-02 10:33:44,709 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,709 [mcmc] New sample, #173:
   Omega_m:0.323191, b1:0.4951234
 2023-07-02 10:33:44,709 [model] Posterior to be computed for parameters {'Omega_m': 0.323237478975147, 'b1': 0.48380822733736456}
 2023-07-02 10:33:44,709 [prior] Evaluating prior at array([0.32323748, 0.48380823])
 2023-07-02 10:33:44,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,709 [model] Got input parameters: {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48380822733736456, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,709 [classy] Got parameters {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,709 [classy] Computing new state
 2023-07-02 10:33:44,709 [classy] Setting parameters: {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.98562394679985}
 2023-07-02 10:33:44,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00710755
 2023-07-02 10:33:44,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48380822733736456, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,755 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,774 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56805
 2023-07-02 10:33:44,774 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,774 [mcmc] New sample, #174:
   Omega_m:0.323191, b1:0.4838398
 2023-07-02 10:33:44,775 [model] Posterior to be computed for parameters {'Omega_m': 0.323237478975147, 'b1': 0.5096769039263478}
 2023-07-02 10:33:44,775 [prior] Evaluating prior at array([0.32323748, 0.5096769 ])
 2023-07-02 10:33:44,775 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,775 [model] Got input parameters: {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5096769039263478, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,775 [classy] Got parameters {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,775 [classy] Re-using computed results
 2023-07-02 10:33:44,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.98562394679985}
 2023-07-02 10:33:44,775 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,775 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5096769039263478, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,775 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,795 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.934541
 2023-07-02 10:33:44,795 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,795 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4832673394597125}
 2023-07-02 10:33:44,795 [prior] Evaluating prior at array([0.32403342, 0.48326734])
 2023-07-02 10:33:44,795 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,795 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4832673394597125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,795 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,795 [classy] Computing new state
 2023-07-02 10:33:44,795 [classy] Setting parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,839 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:44,839 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,841 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00815219
 2023-07-02 10:33:44,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4832673394597125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,841 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50202
 2023-07-02 10:33:44,861 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,861 [mcmc] New sample, #175:
   Omega_m:0.3232375, b1:0.4838082
 2023-07-02 10:33:44,861 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4719045953670057}
 2023-07-02 10:33:44,861 [prior] Evaluating prior at array([0.32403342, 0.4719046 ])
 2023-07-02 10:33:44,861 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,861 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4719045953670057, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,861 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,861 [classy] Re-using computed results
 2023-07-02 10:33:44,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:44,861 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,861 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4719045953670057, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,861 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,881 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11311
 2023-07-02 10:33:44,881 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,881 [model] Posterior to be computed for parameters {'Omega_m': 0.29946886510556425, 'b1': 0.4999604610883577}
 2023-07-02 10:33:44,881 [prior] Evaluating prior at array([0.29946887, 0.49996046])
 2023-07-02 10:33:44,882 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,882 [model] Got input parameters: {'Omega_m': 0.29946886510556425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4999604610883577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,882 [classy] Got parameters {'Omega_m': 0.29946886510556425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,882 [classy] Computing new state
 2023-07-02 10:33:44,882 [classy] Setting parameters: {'Omega_m': 0.29946886510556425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:44,925 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.85576364630327}
 2023-07-02 10:33:44,926 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:44,927 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0109356
 2023-07-02 10:33:44,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4999604610883577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,928 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,947 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.666096
 2023-07-02 10:33:44,947 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,947 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.45745856973171317}
 2023-07-02 10:33:44,947 [prior] Evaluating prior at array([0.32403342, 0.45745857])
 2023-07-02 10:33:44,947 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,947 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45745856973171317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,947 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,947 [classy] Re-using computed results
 2023-07-02 10:33:44,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:44,948 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:44,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45745856973171317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,948 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:44,967 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.644804
 2023-07-02 10:33:44,967 [model] Computed derived parameters: {}
 2023-07-02 10:33:44,967 [model] Posterior to be computed for parameters {'Omega_m': 0.33046017545727063, 'b1': 0.47889996122930045}
 2023-07-02 10:33:44,967 [prior] Evaluating prior at array([0.33046018, 0.47889996])
 2023-07-02 10:33:44,967 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:44,967 [model] Got input parameters: {'Omega_m': 0.33046017545727063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47889996122930045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:44,967 [classy] Got parameters {'Omega_m': 0.33046017545727063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:44,967 [classy] Computing new state
 2023-07-02 10:33:44,967 [classy] Setting parameters: {'Omega_m': 0.33046017545727063, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15070897663594}
 2023-07-02 10:33:45,011 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0191655
 2023-07-02 10:33:45,013 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47889996122930045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,013 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,033 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57877
 2023-07-02 10:33:45,033 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,033 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.5014362653419473}
 2023-07-02 10:33:45,033 [prior] Evaluating prior at array([0.32403342, 0.50143627])
 2023-07-02 10:33:45,033 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,033 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5014362653419473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,033 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,033 [classy] Re-using computed results
 2023-07-02 10:33:45,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:45,033 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5014362653419473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,033 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,052 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65816
 2023-07-02 10:33:45,053 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,053 [model] Posterior to be computed for parameters {'Omega_m': 0.33653320567807354, 'b1': 0.4747729639949861}
 2023-07-02 10:33:45,053 [prior] Evaluating prior at array([0.33653321, 0.47477296])
 2023-07-02 10:33:45,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,053 [model] Got input parameters: {'Omega_m': 0.33653320567807354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4747729639949861, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,053 [classy] Got parameters {'Omega_m': 0.33653320567807354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,053 [classy] Computing new state
 2023-07-02 10:33:45,053 [classy] Setting parameters: {'Omega_m': 0.33653320567807354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,097 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.46138061245244}
 2023-07-02 10:33:45,097 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,099 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0336519
 2023-07-02 10:33:45,099 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4747729639949861, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,099 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,118 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0847338
 2023-07-02 10:33:45,118 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,119 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4655407750908936}
 2023-07-02 10:33:45,119 [prior] Evaluating prior at array([0.32403342, 0.46554078])
 2023-07-02 10:33:45,119 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,119 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4655407750908936, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,119 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,119 [classy] Re-using computed results
 2023-07-02 10:33:45,119 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:45,119 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,119 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4655407750908936, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,119 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59819
 2023-07-02 10:33:45,141 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,141 [mcmc] New sample, #176:
   Omega_m:0.3240334, b1:0.4832673
 2023-07-02 10:33:45,141 [model] Posterior to be computed for parameters {'Omega_m': 0.34264983332304466, 'b1': 0.4528897752629857}
 2023-07-02 10:33:45,142 [prior] Evaluating prior at array([0.34264983, 0.45288978])
 2023-07-02 10:33:45,142 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,142 [model] Got input parameters: {'Omega_m': 0.34264983332304466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4528897752629857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,142 [classy] Got parameters {'Omega_m': 0.34264983332304466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,142 [classy] Computing new state
 2023-07-02 10:33:45,142 [classy] Setting parameters: {'Omega_m': 0.34264983332304466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.77837329621093}
 2023-07-02 10:33:45,186 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0520767
 2023-07-02 10:33:45,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4528897752629857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,188 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,207 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.864896
 2023-07-02 10:33:45,207 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.46633338289153337}
 2023-07-02 10:33:45,208 [prior] Evaluating prior at array([0.32403342, 0.46633338])
 2023-07-02 10:33:45,208 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,208 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46633338289153337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,208 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,208 [classy] Re-using computed results
 2023-07-02 10:33:45,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:45,208 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46633338289153337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,208 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,227 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67375
 2023-07-02 10:33:45,227 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,227 [mcmc] New sample, #177:
   Omega_m:0.3240334, b1:0.4655408
 2023-07-02 10:33:45,227 [model] Posterior to be computed for parameters {'Omega_m': 0.349705053466263, 'b1': 0.4488879274195876}
 2023-07-02 10:33:45,227 [prior] Evaluating prior at array([0.34970505, 0.44888793])
 2023-07-02 10:33:45,227 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,227 [model] Got input parameters: {'Omega_m': 0.349705053466263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4488879274195876, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,227 [classy] Got parameters {'Omega_m': 0.349705053466263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,227 [classy] Computing new state
 2023-07-02 10:33:45,228 [classy] Setting parameters: {'Omega_m': 0.349705053466263, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.00427919243762}
 2023-07-02 10:33:45,271 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,273 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0778864
 2023-07-02 10:33:45,273 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4488879274195876, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,273 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,293 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21381
 2023-07-02 10:33:45,293 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,293 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4490166800245185}
 2023-07-02 10:33:45,293 [prior] Evaluating prior at array([0.32403342, 0.44901668])
 2023-07-02 10:33:45,293 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,293 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4490166800245185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,294 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,294 [classy] Re-using computed results
 2023-07-02 10:33:45,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:45,294 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4490166800245185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,294 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,313 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.700274
 2023-07-02 10:33:45,313 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,313 [model] Posterior to be computed for parameters {'Omega_m': 0.30947067249780436, 'b1': 0.47622966176702947}
 2023-07-02 10:33:45,313 [prior] Evaluating prior at array([0.30947067, 0.47622966])
 2023-07-02 10:33:45,313 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,313 [model] Got input parameters: {'Omega_m': 0.30947067249780436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47622966176702947, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,313 [classy] Got parameters {'Omega_m': 0.30947067249780436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,313 [classy] Computing new state
 2023-07-02 10:33:45,313 [classy] Setting parameters: {'Omega_m': 0.30947067249780436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6242783322645}
 2023-07-02 10:33:45,357 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000763427
 2023-07-02 10:33:45,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47622966176702947, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,359 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,378 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.28506
 2023-07-02 10:33:45,378 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,378 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4926385457301699}
 2023-07-02 10:33:45,378 [prior] Evaluating prior at array([0.32403342, 0.49263855])
 2023-07-02 10:33:45,378 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,378 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4926385457301699, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,378 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,378 [classy] Re-using computed results
 2023-07-02 10:33:45,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
 2023-07-02 10:33:45,378 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4926385457301699, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,379 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,398 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2967
 2023-07-02 10:33:45,398 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,398 [mcmc] New sample, #178:
   Omega_m:0.3240334, b1:0.4663334
 2023-07-02 10:33:45,398 [model] Posterior to be computed for parameters {'Omega_m': 0.32379923045219844, 'b1': 0.4927976889584669}
 2023-07-02 10:33:45,398 [prior] Evaluating prior at array([0.32379923, 0.49279769])
 2023-07-02 10:33:45,399 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,399 [model] Got input parameters: {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4927976889584669, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,399 [classy] Got parameters {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,399 [classy] Computing new state
 2023-07-02 10:33:45,399 [classy] Setting parameters: {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92008976230795}
 2023-07-02 10:33:45,443 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00783744
 2023-07-02 10:33:45,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4927976889584669, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,445 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,464 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33096
 2023-07-02 10:33:45,464 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,464 [mcmc] New sample, #179:
   Omega_m:0.3240334, b1:0.4926385
 2023-07-02 10:33:45,464 [model] Posterior to be computed for parameters {'Omega_m': 0.32379923045219844, 'b1': 0.5061427863789978}
 2023-07-02 10:33:45,464 [prior] Evaluating prior at array([0.32379923, 0.50614279])
 2023-07-02 10:33:45,465 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,465 [model] Got input parameters: {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061427863789978, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,465 [classy] Got parameters {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,465 [classy] Re-using computed results
 2023-07-02 10:33:45,465 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92008976230795}
 2023-07-02 10:33:45,465 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,465 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061427863789978, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,465 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,484 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20968
 2023-07-02 10:33:45,484 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,484 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5033700069628775}
 2023-07-02 10:33:45,484 [prior] Evaluating prior at array([0.30824167, 0.50337001])
 2023-07-02 10:33:45,484 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,484 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5033700069628775, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,484 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,484 [classy] Computing new state
 2023-07-02 10:33:45,484 [classy] Setting parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
 2023-07-02 10:33:45,528 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00131783
 2023-07-02 10:33:45,530 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5033700069628775, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,530 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,549 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42
 2023-07-02 10:33:45,549 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,550 [mcmc] New sample, #180:
   Omega_m:0.3237992, b1:0.4927977
 2023-07-02 10:33:45,550 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5159399378558468}
 2023-07-02 10:33:45,550 [prior] Evaluating prior at array([0.30824167, 0.51593994])
 2023-07-02 10:33:45,550 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,550 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5159399378558468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,550 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,550 [classy] Re-using computed results
 2023-07-02 10:33:45,550 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
 2023-07-02 10:33:45,550 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,550 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5159399378558468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,550 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,569 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61749
 2023-07-02 10:33:45,570 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,570 [mcmc] New sample, #181:
   Omega_m:0.3082417, b1:0.50337
 2023-07-02 10:33:45,570 [model] Posterior to be computed for parameters {'Omega_m': 0.3015264522590826, 'b1': 0.5205033413383175}
 2023-07-02 10:33:45,570 [prior] Evaluating prior at array([0.30152645, 0.52050334])
 2023-07-02 10:33:45,570 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,570 [model] Got input parameters: {'Omega_m': 0.3015264522590826, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205033413383175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,570 [classy] Got parameters {'Omega_m': 0.3015264522590826, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,570 [classy] Computing new state
 2023-07-02 10:33:45,570 [classy] Setting parameters: {'Omega_m': 0.3015264522590826, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59949013639505}
 2023-07-02 10:33:45,614 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00777038
 2023-07-02 10:33:45,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205033413383175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,616 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,636 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76545
 2023-07-02 10:33:45,636 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,636 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5093262837330818}
 2023-07-02 10:33:45,636 [prior] Evaluating prior at array([0.30824167, 0.50932628])
 2023-07-02 10:33:45,636 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,636 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5093262837330818, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,636 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,636 [classy] Re-using computed results
 2023-07-02 10:33:45,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
 2023-07-02 10:33:45,636 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,636 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5093262837330818, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,636 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,656 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61811
 2023-07-02 10:33:45,656 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,656 [mcmc] New sample, #182:
   Omega_m:0.3082417, b1:0.5159399
 2023-07-02 10:33:45,656 [model] Posterior to be computed for parameters {'Omega_m': 0.33809722395202446, 'b1': 0.489037600506595}
 2023-07-02 10:33:45,656 [prior] Evaluating prior at array([0.33809722, 0.4890376 ])
 2023-07-02 10:33:45,657 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,657 [model] Got input parameters: {'Omega_m': 0.33809722395202446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489037600506595, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,657 [classy] Got parameters {'Omega_m': 0.33809722395202446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,657 [classy] Computing new state
 2023-07-02 10:33:45,657 [classy] Setting parameters: {'Omega_m': 0.33809722395202446, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28567206494165}
 2023-07-02 10:33:45,701 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0380036
 2023-07-02 10:33:45,703 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489037600506595, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,703 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,722 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.39295
 2023-07-02 10:33:45,722 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,722 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5140481896305551}
 2023-07-02 10:33:45,722 [prior] Evaluating prior at array([0.30824167, 0.51404819])
 2023-07-02 10:33:45,722 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,722 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5140481896305551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,722 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,722 [classy] Re-using computed results
 2023-07-02 10:33:45,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
 2023-07-02 10:33:45,722 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,723 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5140481896305551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,723 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,742 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64162
 2023-07-02 10:33:45,742 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,742 [mcmc] New sample, #183:
   Omega_m:0.3082417, b1:0.5093263
 2023-07-02 10:33:45,742 [model] Posterior to be computed for parameters {'Omega_m': 0.297909171408322, 'b1': 0.5210697577399184}
 2023-07-02 10:33:45,742 [prior] Evaluating prior at array([0.29790917, 0.52106976])
 2023-07-02 10:33:45,743 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,743 [model] Got input parameters: {'Omega_m': 0.297909171408322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5210697577399184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,743 [classy] Got parameters {'Omega_m': 0.297909171408322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,743 [classy] Computing new state
 2023-07-02 10:33:45,743 [classy] Setting parameters: {'Omega_m': 0.297909171408322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.05106662635163}
 2023-07-02 10:33:45,786 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,788 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137164
 2023-07-02 10:33:45,788 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5210697577399184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,788 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,808 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.842096
 2023-07-02 10:33:45,808 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,809 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.4909315276001731}
 2023-07-02 10:33:45,809 [prior] Evaluating prior at array([0.30824167, 0.49093153])
 2023-07-02 10:33:45,809 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,809 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4909315276001731, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,809 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,809 [classy] Re-using computed results
 2023-07-02 10:33:45,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
 2023-07-02 10:33:45,809 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,809 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4909315276001731, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,809 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,828 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41428
 2023-07-02 10:33:45,828 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,828 [mcmc] New sample, #184:
   Omega_m:0.3082417, b1:0.5140482
 2023-07-02 10:33:45,828 [model] Posterior to be computed for parameters {'Omega_m': 0.31559667768341493, 'b1': 0.4859333482646479}
 2023-07-02 10:33:45,828 [prior] Evaluating prior at array([0.31559668, 0.48593335])
 2023-07-02 10:33:45,828 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,828 [model] Got input parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4859333482646479, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,828 [classy] Got parameters {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,828 [classy] Computing new state
 2023-07-02 10:33:45,828 [classy] Setting parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88722429362002}
 2023-07-02 10:33:45,873 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,874 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000792015
 2023-07-02 10:33:45,874 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4859333482646479, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,874 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,894 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45277
 2023-07-02 10:33:45,894 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,894 [mcmc] New sample, #185:
   Omega_m:0.3082417, b1:0.4909315
 2023-07-02 10:33:45,894 [model] Posterior to be computed for parameters {'Omega_m': 0.31559667768341493, 'b1': 0.4902753553894143}
 2023-07-02 10:33:45,895 [prior] Evaluating prior at array([0.31559668, 0.49027536])
 2023-07-02 10:33:45,895 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,895 [model] Got input parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4902753553894143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,895 [classy] Got parameters {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,895 [classy] Re-using computed results
 2023-07-02 10:33:45,895 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88722429362002}
 2023-07-02 10:33:45,895 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,895 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4902753553894143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,895 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,914 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70978
 2023-07-02 10:33:45,914 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,914 [mcmc] New sample, #186:
   Omega_m:0.3155967, b1:0.4859333
 2023-07-02 10:33:45,914 [model] Posterior to be computed for parameters {'Omega_m': 0.312544381408393, 'b1': 0.4923495782777137}
 2023-07-02 10:33:45,914 [prior] Evaluating prior at array([0.31254438, 0.49234958])
 2023-07-02 10:33:45,915 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,915 [model] Got input parameters: {'Omega_m': 0.312544381408393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4923495782777137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,915 [classy] Got parameters {'Omega_m': 0.312544381408393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,915 [classy] Computing new state
 2023-07-02 10:33:45,915 [classy] Setting parameters: {'Omega_m': 0.312544381408393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:45,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.252858993582}
 2023-07-02 10:33:45,959 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:45,960 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202597
 2023-07-02 10:33:45,960 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4923495782777137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,960 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:45,980 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47468
 2023-07-02 10:33:45,980 [model] Computed derived parameters: {}
 2023-07-02 10:33:45,980 [model] Posterior to be computed for parameters {'Omega_m': 0.31559667768341493, 'b1': 0.48223637573967726}
 2023-07-02 10:33:45,980 [prior] Evaluating prior at array([0.31559668, 0.48223638])
 2023-07-02 10:33:45,980 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:45,980 [model] Got input parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48223637573967726, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,980 [classy] Got parameters {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:45,980 [classy] Re-using computed results
 2023-07-02 10:33:45,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88722429362002}
 2023-07-02 10:33:45,980 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:45,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48223637573967726, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:45,980 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,000 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1569
 2023-07-02 10:33:46,000 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,000 [model] Posterior to be computed for parameters {'Omega_m': 0.3245382177959482, 'b1': 0.4841990294082706}
 2023-07-02 10:33:46,000 [prior] Evaluating prior at array([0.32453822, 0.48419903])
 2023-07-02 10:33:46,001 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,001 [model] Got input parameters: {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4841990294082706, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,001 [classy] Got parameters {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,001 [classy] Computing new state
 2023-07-02 10:33:46,001 [classy] Setting parameters: {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8340372743711}
 2023-07-02 10:33:46,044 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,046 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00885172
 2023-07-02 10:33:46,046 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4841990294082706, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,046 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,066 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45096
 2023-07-02 10:33:46,066 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,066 [mcmc] New sample, #187:
   Omega_m:0.3155967, b1:0.4902754
 2023-07-02 10:33:46,066 [model] Posterior to be computed for parameters {'Omega_m': 0.3245382177959482, 'b1': 0.48976878495546877}
 2023-07-02 10:33:46,066 [prior] Evaluating prior at array([0.32453822, 0.48976878])
 2023-07-02 10:33:46,066 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,066 [model] Got input parameters: {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48976878495546877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,066 [classy] Got parameters {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,066 [classy] Re-using computed results
 2023-07-02 10:33:46,066 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8340372743711}
 2023-07-02 10:33:46,066 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,066 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48976878495546877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,066 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,086 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33075
 2023-07-02 10:33:46,086 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,086 [mcmc] New sample, #188:
   Omega_m:0.3245382, b1:0.484199
 2023-07-02 10:33:46,086 [model] Posterior to be computed for parameters {'Omega_m': 0.3317922807580645, 'b1': 0.48483920339671965}
 2023-07-02 10:33:46,086 [prior] Evaluating prior at array([0.33179228, 0.4848392 ])
 2023-07-02 10:33:46,086 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,086 [model] Got input parameters: {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48483920339671965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,086 [classy] Got parameters {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,086 [classy] Computing new state
 2023-07-02 10:33:46,086 [classy] Setting parameters: {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99853320467642}
 2023-07-02 10:33:46,132 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0220099
 2023-07-02 10:33:46,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48483920339671965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,134 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,154 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.863038
 2023-07-02 10:33:46,154 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,154 [mcmc] New sample, #189:
   Omega_m:0.3245382, b1:0.4897688
 2023-07-02 10:33:46,154 [model] Posterior to be computed for parameters {'Omega_m': 0.3317922807580645, 'b1': 0.4891198468501226}
 2023-07-02 10:33:46,154 [prior] Evaluating prior at array([0.33179228, 0.48911985])
 2023-07-02 10:33:46,155 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,155 [model] Got input parameters: {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4891198468501226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,155 [classy] Got parameters {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,155 [classy] Re-using computed results
 2023-07-02 10:33:46,155 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99853320467642}
 2023-07-02 10:33:46,155 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,155 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4891198468501226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,155 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,174 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.452556
 2023-07-02 10:33:46,174 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,175 [model] Posterior to be computed for parameters {'Omega_m': 0.315958994636781, 'b1': 0.4955988943017331}
 2023-07-02 10:33:46,175 [prior] Evaluating prior at array([0.31595899, 0.49559889])
 2023-07-02 10:33:46,175 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,175 [model] Got input parameters: {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4955988943017331, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,175 [classy] Got parameters {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,175 [classy] Computing new state
 2023-07-02 10:33:46,175 [classy] Setting parameters: {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84403458031568}
 2023-07-02 10:33:46,219 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,221 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00093658
 2023-07-02 10:33:46,221 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4955988943017331, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,221 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,240 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89909
 2023-07-02 10:33:46,241 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,241 [mcmc] New sample, #190:
   Omega_m:0.3317923, b1:0.4848392
 2023-07-02 10:33:46,241 [model] Posterior to be computed for parameters {'Omega_m': 0.315958994636781, 'b1': 0.5015973502325001}
 2023-07-02 10:33:46,241 [prior] Evaluating prior at array([0.31595899, 0.50159735])
 2023-07-02 10:33:46,241 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,241 [model] Got input parameters: {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015973502325001, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,241 [classy] Got parameters {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,241 [classy] Re-using computed results
 2023-07-02 10:33:46,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84403458031568}
 2023-07-02 10:33:46,241 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,241 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015973502325001, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,241 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89923
 2023-07-02 10:33:46,261 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,261 [mcmc] New sample, #191:
   Omega_m:0.315959, b1:0.4955989
 2023-07-02 10:33:46,261 [model] Posterior to be computed for parameters {'Omega_m': 0.32333359787158017, 'b1': 0.4965858541510335}
 2023-07-02 10:33:46,261 [prior] Evaluating prior at array([0.3233336 , 0.49658585])
 2023-07-02 10:33:46,261 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,261 [model] Got input parameters: {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4965858541510335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,262 [classy] Got parameters {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,262 [classy] Computing new state
 2023-07-02 10:33:46,262 [classy] Setting parameters: {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97440418324368}
 2023-07-02 10:33:46,306 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,307 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00722988
 2023-07-02 10:33:46,307 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4965858541510335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,307 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,327 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21207
 2023-07-02 10:33:46,327 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,327 [mcmc] New sample, #192:
   Omega_m:0.315959, b1:0.5015974
 2023-07-02 10:33:46,327 [model] Posterior to be computed for parameters {'Omega_m': 0.32333359787158017, 'b1': 0.5014256129697636}
 2023-07-02 10:33:46,327 [prior] Evaluating prior at array([0.3233336 , 0.50142561])
 2023-07-02 10:33:46,327 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,327 [model] Got input parameters: {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5014256129697636, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,327 [classy] Got parameters {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,327 [classy] Re-using computed results
 2023-07-02 10:33:46,327 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97440418324368}
 2023-07-02 10:33:46,327 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,327 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5014256129697636, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,327 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,347 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84205
 2023-07-02 10:33:46,347 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,347 [mcmc] New sample, #193:
   Omega_m:0.3233336, b1:0.4965859
 2023-07-02 10:33:46,347 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.5088301309397205}
 2023-07-02 10:33:46,347 [prior] Evaluating prior at array([0.31243757, 0.50883013])
 2023-07-02 10:33:46,347 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,347 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088301309397205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,347 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,348 [classy] Computing new state
 2023-07-02 10:33:46,348 [classy] Setting parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
 2023-07-02 10:33:46,391 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,393 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202499
 2023-07-02 10:33:46,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088301309397205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,393 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,413 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.844
 2023-07-02 10:33:46,413 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,413 [mcmc] New sample, #194:
   Omega_m:0.3233336, b1:0.5014256
 2023-07-02 10:33:46,414 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.521968345890676}
 2023-07-02 10:33:46,414 [prior] Evaluating prior at array([0.31243757, 0.52196835])
 2023-07-02 10:33:46,414 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,414 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521968345890676, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,414 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,414 [classy] Re-using computed results
 2023-07-02 10:33:46,414 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
 2023-07-02 10:33:46,414 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,414 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521968345890676, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,414 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,433 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09608
 2023-07-02 10:33:46,433 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,433 [mcmc] New sample, #195:
   Omega_m:0.3124376, b1:0.5088301
 2023-07-02 10:33:46,434 [model] Posterior to be computed for parameters {'Omega_m': 0.3147140659322394, 'b1': 0.5204213295601626}
 2023-07-02 10:33:46,434 [prior] Evaluating prior at array([0.31471407, 0.52042133])
 2023-07-02 10:33:46,434 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,434 [model] Got input parameters: {'Omega_m': 0.3147140659322394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204213295601626, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,434 [classy] Got parameters {'Omega_m': 0.3147140659322394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,434 [classy] Computing new state
 2023-07-02 10:33:46,434 [classy] Setting parameters: {'Omega_m': 0.3147140659322394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.99262014980707}
 2023-07-02 10:33:46,478 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,480 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00050576
 2023-07-02 10:33:46,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204213295601626, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87451
 2023-07-02 10:33:46,500 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,500 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.536920470219604}
 2023-07-02 10:33:46,500 [prior] Evaluating prior at array([0.31243757, 0.53692047])
 2023-07-02 10:33:46,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,500 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.536920470219604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,500 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,500 [classy] Re-using computed results
 2023-07-02 10:33:46,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
 2023-07-02 10:33:46,500 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.536920470219604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,500 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,520 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0548508
 2023-07-02 10:33:46,520 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,520 [model] Posterior to be computed for parameters {'Omega_m': 0.3003980538281571, 'b1': 0.5301499395311084}
 2023-07-02 10:33:46,520 [prior] Evaluating prior at array([0.30039805, 0.53014994])
 2023-07-02 10:33:46,520 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,520 [model] Got input parameters: {'Omega_m': 0.3003980538281571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5301499395311084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,520 [classy] Got parameters {'Omega_m': 0.3003980538281571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,520 [classy] Computing new state
 2023-07-02 10:33:46,520 [classy] Setting parameters: {'Omega_m': 0.3003980538281571, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73983423792114}
 2023-07-02 10:33:46,564 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,566 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00943565
 2023-07-02 10:33:46,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5301499395311084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,566 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,585 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58847
 2023-07-02 10:33:46,585 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,585 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.5308510091750666}
 2023-07-02 10:33:46,585 [prior] Evaluating prior at array([0.31243757, 0.53085101])
 2023-07-02 10:33:46,586 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,586 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308510091750666, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,586 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,586 [classy] Re-using computed results
 2023-07-02 10:33:46,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
 2023-07-02 10:33:46,586 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,586 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308510091750666, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,586 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,605 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.03948
 2023-07-02 10:33:46,605 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,606 [model] Posterior to be computed for parameters {'Omega_m': 0.30755889902258404, 'b1': 0.5252837051739138}
 2023-07-02 10:33:46,606 [prior] Evaluating prior at array([0.3075589 , 0.52528371])
 2023-07-02 10:33:46,606 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,606 [model] Got input parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5252837051739138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,606 [classy] Got parameters {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,606 [classy] Computing new state
 2023-07-02 10:33:46,606 [classy] Setting parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85693560003128}
 2023-07-02 10:33:46,650 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00170834
 2023-07-02 10:33:46,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5252837051739138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,652 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,672 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23526
 2023-07-02 10:33:46,672 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,672 [mcmc] New sample, #196:
   Omega_m:0.3124376, b1:0.5219683
 2023-07-02 10:33:46,672 [model] Posterior to be computed for parameters {'Omega_m': 0.30755889902258404, 'b1': 0.537709837602294}
 2023-07-02 10:33:46,672 [prior] Evaluating prior at array([0.3075589 , 0.53770984])
 2023-07-02 10:33:46,672 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,672 [model] Got input parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.537709837602294, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,672 [classy] Got parameters {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,672 [classy] Re-using computed results
 2023-07-02 10:33:46,672 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85693560003128}
 2023-07-02 10:33:46,672 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,672 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.537709837602294, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,672 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,691 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.02967
 2023-07-02 10:33:46,691 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3159705894659949, 'b1': 0.5195674446032105}
 2023-07-02 10:33:46,692 [prior] Evaluating prior at array([0.31597059, 0.51956744])
 2023-07-02 10:33:46,692 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,692 [model] Got input parameters: {'Omega_m': 0.3159705894659949, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195674446032105, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,692 [classy] Got parameters {'Omega_m': 0.3159705894659949, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,692 [classy] Computing new state
 2023-07-02 10:33:46,692 [classy] Setting parameters: {'Omega_m': 0.3159705894659949, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84265344702402}
 2023-07-02 10:33:46,736 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,737 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000941463
 2023-07-02 10:33:46,738 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195674446032105, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,738 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,757 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.71018
 2023-07-02 10:33:46,757 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,758 [model] Posterior to be computed for parameters {'Omega_m': 0.30755889902258404, 'b1': 0.47877119370007204}
 2023-07-02 10:33:46,758 [prior] Evaluating prior at array([0.3075589 , 0.47877119])
 2023-07-02 10:33:46,758 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,758 [model] Got input parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47877119370007204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,758 [classy] Got parameters {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,758 [classy] Re-using computed results
 2023-07-02 10:33:46,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85693560003128}
 2023-07-02 10:33:46,758 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,758 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47877119370007204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,758 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,777 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.592756
 2023-07-02 10:33:46,777 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,777 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5205086673979266}
 2023-07-02 10:33:46,778 [prior] Evaluating prior at array([0.31458555, 0.52050867])
 2023-07-02 10:33:46,778 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,778 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205086673979266, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,778 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,778 [classy] Computing new state
 2023-07-02 10:33:46,778 [classy] Setting parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,822 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
 2023-07-02 10:33:46,822 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,824 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000471897
 2023-07-02 10:33:46,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205086673979266, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,824 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.88964
 2023-07-02 10:33:46,843 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,843 [mcmc] New sample, #197:
   Omega_m:0.3075589, b1:0.5252837
 2023-07-02 10:33:46,843 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5282576984998295}
 2023-07-02 10:33:46,843 [prior] Evaluating prior at array([0.31458555, 0.5282577 ])
 2023-07-02 10:33:46,843 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,843 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282576984998295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,843 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,843 [classy] Re-using computed results
 2023-07-02 10:33:46,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
 2023-07-02 10:33:46,844 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,844 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282576984998295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,844 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,863 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.882426
 2023-07-02 10:33:46,864 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,864 [mcmc] New sample, #198:
   Omega_m:0.3145855, b1:0.5205087
 2023-07-02 10:33:46,864 [model] Posterior to be computed for parameters {'Omega_m': 0.2912970619094546, 'b1': 0.5440836539150645}
 2023-07-02 10:33:46,864 [prior] Evaluating prior at array([0.29129706, 0.54408365])
 2023-07-02 10:33:46,864 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,864 [model] Got input parameters: {'Omega_m': 0.2912970619094546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5440836539150645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,864 [classy] Got parameters {'Omega_m': 0.2912970619094546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,864 [classy] Computing new state
 2023-07-02 10:33:46,864 [classy] Setting parameters: {'Omega_m': 0.2912970619094546, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.88902121025848}
 2023-07-02 10:33:46,908 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,910 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292506
 2023-07-02 10:33:46,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5440836539150645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,910 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,929 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.623573
 2023-07-02 10:33:46,929 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5314675612698608}
 2023-07-02 10:33:46,929 [prior] Evaluating prior at array([0.31458555, 0.53146756])
 2023-07-02 10:33:46,930 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,930 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5314675612698608, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,930 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,930 [classy] Re-using computed results
 2023-07-02 10:33:46,930 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
 2023-07-02 10:33:46,930 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:46,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5314675612698608, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,930 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:46,949 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.362962
 2023-07-02 10:33:46,949 [model] Computed derived parameters: {}
 2023-07-02 10:33:46,949 [model] Posterior to be computed for parameters {'Omega_m': 0.34437280067575454, 'b1': 0.5080154278180846}
 2023-07-02 10:33:46,949 [prior] Evaluating prior at array([0.3443728 , 0.50801543])
 2023-07-02 10:33:46,949 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:46,949 [model] Got input parameters: {'Omega_m': 0.34437280067575454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080154278180846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,949 [classy] Got parameters {'Omega_m': 0.34437280067575454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:46,949 [classy] Computing new state
 2023-07-02 10:33:46,949 [classy] Setting parameters: {'Omega_m': 0.34437280067575454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:46,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.58797985775968}
 2023-07-02 10:33:46,993 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:46,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0579384
 2023-07-02 10:33:46,995 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080154278180846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:46,995 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,015 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.1712
 2023-07-02 10:33:47,015 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,015 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5852542050246913}
 2023-07-02 10:33:47,016 [prior] Evaluating prior at array([0.31458555, 0.58525421])
 2023-07-02 10:33:47,016 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,016 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5852542050246913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,016 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,016 [classy] Re-using computed results
 2023-07-02 10:33:47,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
 2023-07-02 10:33:47,016 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,016 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5852542050246913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,016 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,037 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.8195
 2023-07-02 10:33:47,037 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,037 [model] Posterior to be computed for parameters {'Omega_m': 0.3150821857730402, 'b1': 0.5279202006085758}
 2023-07-02 10:33:47,037 [prior] Evaluating prior at array([0.31508219, 0.5279202 ])
 2023-07-02 10:33:47,038 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,038 [model] Got input parameters: {'Omega_m': 0.3150821857730402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5279202006085758, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,038 [classy] Got parameters {'Omega_m': 0.3150821857730402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,038 [classy] Computing new state
 2023-07-02 10:33:47,038 [classy] Setting parameters: {'Omega_m': 0.3150821857730402, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.948627650425}
 2023-07-02 10:33:47,082 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,084 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000613784
 2023-07-02 10:33:47,084 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5279202006085758, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,084 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,103 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.796471
 2023-07-02 10:33:47,103 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,103 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.521609772966243}
 2023-07-02 10:33:47,103 [prior] Evaluating prior at array([0.31458555, 0.52160977])
 2023-07-02 10:33:47,103 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,103 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521609772966243, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,104 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,104 [classy] Re-using computed results
 2023-07-02 10:33:47,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
 2023-07-02 10:33:47,104 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,104 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521609772966243, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,104 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,125 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76759
 2023-07-02 10:33:47,125 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,125 [mcmc] New sample, #199:
   Omega_m:0.3145855, b1:0.5282577
 2023-07-02 10:33:47,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3299036991105662, 'b1': 0.5112001459519045}
 2023-07-02 10:33:47,125 [prior] Evaluating prior at array([0.3299037 , 0.51120015])
 2023-07-02 10:33:47,125 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,125 [model] Got input parameters: {'Omega_m': 0.3299036991105662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112001459519045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,125 [classy] Got parameters {'Omega_m': 0.3299036991105662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,125 [classy] Computing new state
 2023-07-02 10:33:47,125 [classy] Setting parameters: {'Omega_m': 0.3299036991105662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.21443943641063}
 2023-07-02 10:33:47,176 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,178 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0180338
 2023-07-02 10:33:47,178 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112001459519045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,178 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,202 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.28858
 2023-07-02 10:33:47,203 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,203 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5230157272131382}
 2023-07-02 10:33:47,203 [prior] Evaluating prior at array([0.31458555, 0.52301573])
 2023-07-02 10:33:47,203 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,203 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5230157272131382, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,203 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,203 [classy] Re-using computed results
 2023-07-02 10:33:47,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
 2023-07-02 10:33:47,203 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5230157272131382, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,203 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,228 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60166
 2023-07-02 10:33:47,228 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,228 [mcmc] New sample, #200:
   Omega_m:0.3145855, b1:0.5216098
 2023-07-02 10:33:47,228 [model] Posterior to be computed for parameters {'Omega_m': 0.31839181004470785, 'b1': 0.5204291362465686}
 2023-07-02 10:33:47,228 [prior] Evaluating prior at array([0.31839181, 0.52042914])
 2023-07-02 10:33:47,228 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,228 [model] Got input parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204291362465686, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,228 [classy] Got parameters {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,228 [classy] Computing new state
 2023-07-02 10:33:47,228 [classy] Setting parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5551759235056}
 2023-07-02 10:33:47,273 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00231137
 2023-07-02 10:33:47,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204291362465686, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,275 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,295 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.958418
 2023-07-02 10:33:47,295 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,295 [mcmc] New sample, #201:
   Omega_m:0.3145855, b1:0.5230157
 2023-07-02 10:33:47,295 [model] Posterior to be computed for parameters {'Omega_m': 0.31839181004470785, 'b1': 0.518784933095138}
 2023-07-02 10:33:47,295 [prior] Evaluating prior at array([0.31839181, 0.51878493])
 2023-07-02 10:33:47,295 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,295 [model] Got input parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.518784933095138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,295 [classy] Got parameters {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,295 [classy] Re-using computed results
 2023-07-02 10:33:47,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5551759235056}
 2023-07-02 10:33:47,296 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,296 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.518784933095138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,296 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,316 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.19324
 2023-07-02 10:33:47,316 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,316 [mcmc] New sample, #202:
   Omega_m:0.3183918, b1:0.5204291
 2023-07-02 10:33:47,317 [model] Posterior to be computed for parameters {'Omega_m': 0.33039425861795846, 'b1': 0.5106285317162795}
 2023-07-02 10:33:47,317 [prior] Evaluating prior at array([0.33039426, 0.51062853])
 2023-07-02 10:33:47,317 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,317 [model] Got input parameters: {'Omega_m': 0.33039425861795846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5106285317162795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,317 [classy] Got parameters {'Omega_m': 0.33039425861795846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,317 [classy] Computing new state
 2023-07-02 10:33:47,317 [classy] Setting parameters: {'Omega_m': 0.33039425861795846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15825337803395}
 2023-07-02 10:33:47,362 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,364 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0190297
 2023-07-02 10:33:47,364 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5106285317162795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,364 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,384 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.43489
 2023-07-02 10:33:47,384 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,384 [model] Posterior to be computed for parameters {'Omega_m': 0.31839181004470785, 'b1': 0.5251480918402662}
 2023-07-02 10:33:47,385 [prior] Evaluating prior at array([0.31839181, 0.52514809])
 2023-07-02 10:33:47,385 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,385 [model] Got input parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5251480918402662, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,385 [classy] Got parameters {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,385 [classy] Re-using computed results
 2023-07-02 10:33:47,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5551759235056}
 2023-07-02 10:33:47,385 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,385 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5251480918402662, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,385 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,405 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.196455
 2023-07-02 10:33:47,405 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,405 [mcmc] New sample, #203:
   Omega_m:0.3183918, b1:0.5187849
 2023-07-02 10:33:47,405 [model] Posterior to be computed for parameters {'Omega_m': 0.3199697709779786, 'b1': 0.5240757704174027}
 2023-07-02 10:33:47,405 [prior] Evaluating prior at array([0.31996977, 0.52407577])
 2023-07-02 10:33:47,405 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,405 [model] Got input parameters: {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5240757704174027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,405 [classy] Got parameters {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,405 [classy] Computing new state
 2023-07-02 10:33:47,405 [classy] Setting parameters: {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,454 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36886004629972}
 2023-07-02 10:33:47,454 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,456 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00357535
 2023-07-02 10:33:47,456 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5240757704174027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,456 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,476 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.200604
 2023-07-02 10:33:47,476 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,476 [mcmc] New sample, #204:
   Omega_m:0.3183918, b1:0.5251481
 2023-07-02 10:33:47,477 [model] Posterior to be computed for parameters {'Omega_m': 0.3199697709779786, 'b1': 0.5099238262714798}
 2023-07-02 10:33:47,477 [prior] Evaluating prior at array([0.31996977, 0.50992383])
 2023-07-02 10:33:47,477 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,477 [model] Got input parameters: {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5099238262714798, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,477 [classy] Got parameters {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,477 [classy] Re-using computed results
 2023-07-02 10:33:47,477 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36886004629972}
 2023-07-02 10:33:47,477 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,477 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5099238262714798, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,477 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,496 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84667
 2023-07-02 10:33:47,496 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,496 [mcmc] New sample, #205:
   Omega_m:0.3199698, b1:0.5240758
 2023-07-02 10:33:47,496 [model] Posterior to be computed for parameters {'Omega_m': 0.32083490541726734, 'b1': 0.5093359142558234}
 2023-07-02 10:33:47,496 [prior] Evaluating prior at array([0.32083491, 0.50933591])
 2023-07-02 10:33:47,496 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,496 [model] Got input parameters: {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5093359142558234, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,497 [classy] Got parameters {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,497 [classy] Computing new state
 2023-07-02 10:33:47,497 [classy] Setting parameters: {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,541 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26705808246697}
 2023-07-02 10:33:47,541 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,543 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00439115
 2023-07-02 10:33:47,543 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5093359142558234, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,543 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,563 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.69235
 2023-07-02 10:33:47,563 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,563 [mcmc] New sample, #206:
   Omega_m:0.3199698, b1:0.5099238
 2023-07-02 10:33:47,563 [model] Posterior to be computed for parameters {'Omega_m': 0.32083490541726734, 'b1': 0.5278993397793454}
 2023-07-02 10:33:47,563 [prior] Evaluating prior at array([0.32083491, 0.52789934])
 2023-07-02 10:33:47,564 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,564 [model] Got input parameters: {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5278993397793454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,564 [classy] Got parameters {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,564 [classy] Re-using computed results
 2023-07-02 10:33:47,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26705808246697}
 2023-07-02 10:33:47,564 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5278993397793454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,564 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,583 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.34489
 2023-07-02 10:33:47,583 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,583 [model] Posterior to be computed for parameters {'Omega_m': 0.3132794584049812, 'b1': 0.5144703047972871}
 2023-07-02 10:33:47,584 [prior] Evaluating prior at array([0.31327946, 0.5144703 ])
 2023-07-02 10:33:47,584 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,584 [model] Got input parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5144703047972871, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,584 [classy] Got parameters {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,584 [classy] Computing new state
 2023-07-02 10:33:47,584 [classy] Setting parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16451229452576}
 2023-07-02 10:33:47,628 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000241119
 2023-07-02 10:33:47,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5144703047972871, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,630 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57683
 2023-07-02 10:33:47,650 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,650 [mcmc] New sample, #207:
   Omega_m:0.3208349, b1:0.5093359
 2023-07-02 10:33:47,650 [model] Posterior to be computed for parameters {'Omega_m': 0.3132794584049812, 'b1': 0.5013918815809042}
 2023-07-02 10:33:47,650 [prior] Evaluating prior at array([0.31327946, 0.50139188])
 2023-07-02 10:33:47,650 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,650 [model] Got input parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5013918815809042, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,650 [classy] Got parameters {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,650 [classy] Re-using computed results
 2023-07-02 10:33:47,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16451229452576}
 2023-07-02 10:33:47,650 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,650 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5013918815809042, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,650 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,670 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89439
 2023-07-02 10:33:47,670 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,670 [mcmc] New sample, #208:
   Omega_m:0.3132795, b1:0.5144703
 2023-07-02 10:33:47,670 [model] Posterior to be computed for parameters {'Omega_m': 0.30605036779004235, 'b1': 0.5063044928951479}
 2023-07-02 10:33:47,670 [prior] Evaluating prior at array([0.30605037, 0.50630449])
 2023-07-02 10:33:47,670 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,670 [model] Got input parameters: {'Omega_m': 0.30605036779004235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5063044928951479, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,670 [classy] Got parameters {'Omega_m': 0.30605036779004235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,670 [classy] Computing new state
 2023-07-02 10:33:47,670 [classy] Setting parameters: {'Omega_m': 0.30605036779004235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,715 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.04141972644808}
 2023-07-02 10:33:47,715 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00278188
 2023-07-02 10:33:47,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5063044928951479, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,717 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15808
 2023-07-02 10:33:47,736 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,736 [model] Posterior to be computed for parameters {'Omega_m': 0.3132794584049812, 'b1': 0.4985827829275823}
 2023-07-02 10:33:47,736 [prior] Evaluating prior at array([0.31327946, 0.49858278])
 2023-07-02 10:33:47,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,736 [model] Got input parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4985827829275823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,736 [classy] Got parameters {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,737 [classy] Re-using computed results
 2023-07-02 10:33:47,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16451229452576}
 2023-07-02 10:33:47,737 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,737 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4985827829275823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,737 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.84198
 2023-07-02 10:33:47,756 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,756 [mcmc] New sample, #209:
   Omega_m:0.3132795, b1:0.5013919
 2023-07-02 10:33:47,756 [model] Posterior to be computed for parameters {'Omega_m': 0.3079158712041842, 'b1': 0.5022276700331774}
 2023-07-02 10:33:47,756 [prior] Evaluating prior at array([0.30791587, 0.50222767])
 2023-07-02 10:33:47,756 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,756 [model] Got input parameters: {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5022276700331774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,756 [classy] Got parameters {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,756 [classy] Computing new state
 2023-07-02 10:33:47,756 [classy] Setting parameters: {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.81339363227545}
 2023-07-02 10:33:47,801 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,803 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00149677
 2023-07-02 10:33:47,803 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5022276700331774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,803 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,823 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30029
 2023-07-02 10:33:47,823 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,823 [mcmc] New sample, #210:
   Omega_m:0.3132795, b1:0.4985828
 2023-07-02 10:33:47,823 [model] Posterior to be computed for parameters {'Omega_m': 0.3079158712041842, 'b1': 0.5037090939988291}
 2023-07-02 10:33:47,823 [prior] Evaluating prior at array([0.30791587, 0.50370909])
 2023-07-02 10:33:47,823 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,823 [model] Got input parameters: {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5037090939988291, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,823 [classy] Got parameters {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,823 [classy] Re-using computed results
 2023-07-02 10:33:47,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.81339363227545}
 2023-07-02 10:33:47,824 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5037090939988291, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,824 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38031
 2023-07-02 10:33:47,843 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,843 [mcmc] New sample, #211:
   Omega_m:0.3079159, b1:0.5022277
 2023-07-02 10:33:47,843 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5027747430758734}
 2023-07-02 10:33:47,843 [prior] Evaluating prior at array([0.3092908 , 0.50277474])
 2023-07-02 10:33:47,843 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,843 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5027747430758734, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,843 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,843 [classy] Computing new state
 2023-07-02 10:33:47,843 [classy] Setting parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:47,888 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,890 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000832691
 2023-07-02 10:33:47,890 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5027747430758734, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,890 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,909 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55831
 2023-07-02 10:33:47,909 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,909 [mcmc] New sample, #212:
   Omega_m:0.3079159, b1:0.5037091
 2023-07-02 10:33:47,909 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5183259710157854}
 2023-07-02 10:33:47,909 [prior] Evaluating prior at array([0.3092908 , 0.51832597])
 2023-07-02 10:33:47,910 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,910 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183259710157854, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,910 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,910 [classy] Re-using computed results
 2023-07-02 10:33:47,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:47,910 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183259710157854, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,910 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,930 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56956
 2023-07-02 10:33:47,930 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,930 [mcmc] New sample, #213:
   Omega_m:0.3092908, b1:0.5027747
 2023-07-02 10:33:47,930 [model] Posterior to be computed for parameters {'Omega_m': 0.32684718515277833, 'b1': 0.506395330745357}
 2023-07-02 10:33:47,930 [prior] Evaluating prior at array([0.32684719, 0.50639533])
 2023-07-02 10:33:47,930 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,930 [model] Got input parameters: {'Omega_m': 0.32684718515277833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.506395330745357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,930 [classy] Got parameters {'Omega_m': 0.32684718515277833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,930 [classy] Computing new state
 2023-07-02 10:33:47,930 [classy] Setting parameters: {'Omega_m': 0.32684718515277833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:47,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.56628048370587}
 2023-07-02 10:33:47,974 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:47,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0124145
 2023-07-02 10:33:47,976 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.506395330745357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,976 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:47,995 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.075312
 2023-07-02 10:33:47,995 [model] Computed derived parameters: {}
 2023-07-02 10:33:47,996 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5375783600707323}
 2023-07-02 10:33:47,996 [prior] Evaluating prior at array([0.3092908 , 0.53757836])
 2023-07-02 10:33:47,996 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:47,996 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375783600707323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,996 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:47,996 [classy] Re-using computed results
 2023-07-02 10:33:47,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:47,996 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:47,996 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375783600707323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:47,996 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,015 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.738898
 2023-07-02 10:33:48,015 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,015 [model] Posterior to be computed for parameters {'Omega_m': 0.260666717629516, 'b1': 0.5513690253432451}
 2023-07-02 10:33:48,015 [prior] Evaluating prior at array([0.26066672, 0.55136903])
 2023-07-02 10:33:48,016 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,016 [model] Got input parameters: {'Omega_m': 0.260666717629516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5513690253432451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,016 [classy] Got parameters {'Omega_m': 0.260666717629516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,016 [classy] Computing new state
 2023-07-02 10:33:48,016 [classy] Setting parameters: {'Omega_m': 0.260666717629516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.99819759562462}
 2023-07-02 10:33:48,059 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,061 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.188808
 2023-07-02 10:33:48,061 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5513690253432451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,061 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,081 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.3825
 2023-07-02 10:33:48,081 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,082 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5049129415629607}
 2023-07-02 10:33:48,082 [prior] Evaluating prior at array([0.3092908 , 0.50491294])
 2023-07-02 10:33:48,082 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,082 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5049129415629607, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,082 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,082 [classy] Re-using computed results
 2023-07-02 10:33:48,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:48,082 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5049129415629607, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,082 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,101 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63628
 2023-07-02 10:33:48,101 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,101 [mcmc] New sample, #214:
   Omega_m:0.3092908, b1:0.518326
 2023-07-02 10:33:48,101 [model] Posterior to be computed for parameters {'Omega_m': 0.32773616619630447, 'b1': 0.49237818404387734}
 2023-07-02 10:33:48,102 [prior] Evaluating prior at array([0.32773617, 0.49237818])
 2023-07-02 10:33:48,102 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,102 [model] Got input parameters: {'Omega_m': 0.32773616619630447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49237818404387734, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,102 [classy] Got parameters {'Omega_m': 0.32773616619630447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,102 [classy] Computing new state
 2023-07-02 10:33:48,102 [classy] Setting parameters: {'Omega_m': 0.32773616619630447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,148 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46364286228786}
 2023-07-02 10:33:48,148 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,150 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0139436
 2023-07-02 10:33:48,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49237818404387734, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,150 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,170 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45386
 2023-07-02 10:33:48,170 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,171 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5276538864123546}
 2023-07-02 10:33:48,171 [prior] Evaluating prior at array([0.3092908 , 0.52765389])
 2023-07-02 10:33:48,171 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,171 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5276538864123546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,171 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,171 [classy] Re-using computed results
 2023-07-02 10:33:48,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:48,171 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5276538864123546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,171 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94371
 2023-07-02 10:33:48,190 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,190 [mcmc] New sample, #215:
   Omega_m:0.3092908, b1:0.5049129
 2023-07-02 10:33:48,191 [model] Posterior to be computed for parameters {'Omega_m': 0.2837102899127549, 'b1': 0.5450374173019288}
 2023-07-02 10:33:48,191 [prior] Evaluating prior at array([0.28371029, 0.54503742])
 2023-07-02 10:33:48,191 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,191 [model] Got input parameters: {'Omega_m': 0.2837102899127549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5450374173019288, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,191 [classy] Got parameters {'Omega_m': 0.2837102899127549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,191 [classy] Computing new state
 2023-07-02 10:33:48,191 [classy] Setting parameters: {'Omega_m': 0.2837102899127549, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.8710573594621}
 2023-07-02 10:33:48,236 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0548514
 2023-07-02 10:33:48,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5450374173019288, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,238 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.8058
 2023-07-02 10:33:48,257 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,257 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.549124949207475}
 2023-07-02 10:33:48,257 [prior] Evaluating prior at array([0.3092908 , 0.54912495])
 2023-07-02 10:33:48,257 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,257 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.549124949207475, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,257 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,257 [classy] Re-using computed results
 2023-07-02 10:33:48,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:48,257 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.549124949207475, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,257 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,277 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.38324
 2023-07-02 10:33:48,277 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,277 [model] Posterior to be computed for parameters {'Omega_m': 0.28046606256753515, 'b1': 0.5472420691469576}
 2023-07-02 10:33:48,277 [prior] Evaluating prior at array([0.28046606, 0.54724207])
 2023-07-02 10:33:48,277 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,277 [model] Got input parameters: {'Omega_m': 0.28046606256753515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5472420691469576, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,278 [classy] Got parameters {'Omega_m': 0.28046606256753515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,278 [classy] Computing new state
 2023-07-02 10:33:48,278 [classy] Setting parameters: {'Omega_m': 0.28046606256753515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.29793596217513}
 2023-07-02 10:33:48,322 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684531
 2023-07-02 10:33:48,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5472420691469576, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,324 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,343 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.54491
 2023-07-02 10:33:48,343 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,343 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.520638579663175}
 2023-07-02 10:33:48,344 [prior] Evaluating prior at array([0.3092908 , 0.52063858])
 2023-07-02 10:33:48,344 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,344 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520638579663175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,344 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,344 [classy] Re-using computed results
 2023-07-02 10:33:48,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
 2023-07-02 10:33:48,344 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520638579663175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,344 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,363 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45941
 2023-07-02 10:33:48,363 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,363 [mcmc] New sample, #216:
   Omega_m:0.3092908, b1:0.5276539
 2023-07-02 10:33:48,363 [model] Posterior to be computed for parameters {'Omega_m': 0.2995279194396347, 'b1': 0.5272730592657606}
 2023-07-02 10:33:48,363 [prior] Evaluating prior at array([0.29952792, 0.52727306])
 2023-07-02 10:33:48,363 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,363 [model] Got input parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5272730592657606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,363 [classy] Got parameters {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,363 [classy] Computing new state
 2023-07-02 10:33:48,364 [classy] Setting parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8483878984982}
 2023-07-02 10:33:48,408 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,409 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108368
 2023-07-02 10:33:48,409 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5272730592657606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,409 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44969
 2023-07-02 10:33:48,430 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,430 [mcmc] New sample, #217:
   Omega_m:0.3092908, b1:0.5206386
 2023-07-02 10:33:48,430 [model] Posterior to be computed for parameters {'Omega_m': 0.2995279194396347, 'b1': 0.520632928917912}
 2023-07-02 10:33:48,430 [prior] Evaluating prior at array([0.29952792, 0.52063293])
 2023-07-02 10:33:48,430 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,430 [model] Got input parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520632928917912, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,430 [classy] Got parameters {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,431 [classy] Re-using computed results
 2023-07-02 10:33:48,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8483878984982}
 2023-07-02 10:33:48,431 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520632928917912, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,431 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,450 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29271
 2023-07-02 10:33:48,450 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,450 [mcmc] New sample, #218:
   Omega_m:0.2995279, b1:0.5272731
 2023-07-02 10:33:48,450 [model] Posterior to be computed for parameters {'Omega_m': 0.2885895918898879, 'b1': 0.528066194669035}
 2023-07-02 10:33:48,450 [prior] Evaluating prior at array([0.28858959, 0.52806619])
 2023-07-02 10:33:48,450 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,450 [model] Got input parameters: {'Omega_m': 0.2885895918898879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.528066194669035, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,450 [classy] Got parameters {'Omega_m': 0.2885895918898879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,450 [classy] Computing new state
 2023-07-02 10:33:48,450 [classy] Setting parameters: {'Omega_m': 0.2885895918898879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.23690185949303}
 2023-07-02 10:33:48,495 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0374095
 2023-07-02 10:33:48,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.528066194669035, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,496 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,516 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.5706
 2023-07-02 10:33:48,516 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,516 [model] Posterior to be computed for parameters {'Omega_m': 0.2995279194396347, 'b1': 0.48429283709579285}
 2023-07-02 10:33:48,516 [prior] Evaluating prior at array([0.29952792, 0.48429284])
 2023-07-02 10:33:48,516 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,516 [model] Got input parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48429283709579285, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,516 [classy] Got parameters {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,516 [classy] Re-using computed results
 2023-07-02 10:33:48,516 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8483878984982}
 2023-07-02 10:33:48,516 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,516 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48429283709579285, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,516 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,536 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.49582
 2023-07-02 10:33:48,536 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,536 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5078535696259842}
 2023-07-02 10:33:48,536 [prior] Evaluating prior at array([0.31833322, 0.50785357])
 2023-07-02 10:33:48,536 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,536 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5078535696259842, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,536 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,536 [classy] Computing new state
 2023-07-02 10:33:48,536 [classy] Setting parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
 2023-07-02 10:33:48,581 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00227009
 2023-07-02 10:33:48,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5078535696259842, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,583 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,602 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36819
 2023-07-02 10:33:48,602 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,602 [mcmc] New sample, #219:
   Omega_m:0.2995279, b1:0.5206329
 2023-07-02 10:33:48,602 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5462994189438529}
 2023-07-02 10:33:48,602 [prior] Evaluating prior at array([0.31833322, 0.54629942])
 2023-07-02 10:33:48,602 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,602 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5462994189438529, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,603 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,603 [classy] Re-using computed results
 2023-07-02 10:33:48,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
 2023-07-02 10:33:48,603 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5462994189438529, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,603 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.83087
 2023-07-02 10:33:48,622 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,622 [model] Posterior to be computed for parameters {'Omega_m': 0.29900780881540995, 'b1': 0.5209863760488616}
 2023-07-02 10:33:48,622 [prior] Evaluating prior at array([0.29900781, 0.52098638])
 2023-07-02 10:33:48,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,623 [model] Got input parameters: {'Omega_m': 0.29900780881540995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5209863760488616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,623 [classy] Got parameters {'Omega_m': 0.29900780881540995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,623 [classy] Computing new state
 2023-07-02 10:33:48,623 [classy] Setting parameters: {'Omega_m': 0.29900780881540995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91340568421296}
 2023-07-02 10:33:48,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117232
 2023-07-02 10:33:48,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5209863760488616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,669 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,689 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16481
 2023-07-02 10:33:48,689 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,689 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5031986233872454}
 2023-07-02 10:33:48,689 [prior] Evaluating prior at array([0.31833322, 0.50319862])
 2023-07-02 10:33:48,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,689 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5031986233872454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,689 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,689 [classy] Re-using computed results
 2023-07-02 10:33:48,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
 2023-07-02 10:33:48,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5031986233872454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,709 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65579
 2023-07-02 10:33:48,709 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,709 [mcmc] New sample, #220:
   Omega_m:0.3183332, b1:0.5078536
 2023-07-02 10:33:48,709 [model] Posterior to be computed for parameters {'Omega_m': 0.3197925788746206, 'b1': 0.5022069012911652}
 2023-07-02 10:33:48,709 [prior] Evaluating prior at array([0.31979258, 0.5022069 ])
 2023-07-02 10:33:48,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,709 [model] Got input parameters: {'Omega_m': 0.3197925788746206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5022069012911652, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,709 [classy] Got parameters {'Omega_m': 0.3197925788746206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,709 [classy] Computing new state
 2023-07-02 10:33:48,709 [classy] Setting parameters: {'Omega_m': 0.3197925788746206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3897420806043}
 2023-07-02 10:33:48,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00341893
 2023-07-02 10:33:48,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5022069012911652, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,755 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,774 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50495
 2023-07-02 10:33:48,774 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,774 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5358416770493034}
 2023-07-02 10:33:48,774 [prior] Evaluating prior at array([0.31833322, 0.53584168])
 2023-07-02 10:33:48,774 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,774 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5358416770493034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,774 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,774 [classy] Re-using computed results
 2023-07-02 10:33:48,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
 2023-07-02 10:33:48,774 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5358416770493034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,774 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.99356
 2023-07-02 10:33:48,794 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,794 [model] Posterior to be computed for parameters {'Omega_m': 0.3158407582257441, 'b1': 0.5048924062689856}
 2023-07-02 10:33:48,794 [prior] Evaluating prior at array([0.31584076, 0.50489241])
 2023-07-02 10:33:48,794 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,794 [model] Got input parameters: {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5048924062689856, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,794 [classy] Got parameters {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,794 [classy] Computing new state
 2023-07-02 10:33:48,794 [classy] Setting parameters: {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.85812140684394}
 2023-07-02 10:33:48,839 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000887703
 2023-07-02 10:33:48,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5048924062689856, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,840 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,860 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82433
 2023-07-02 10:33:48,860 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,860 [mcmc] New sample, #221:
   Omega_m:0.3183332, b1:0.5031986
 2023-07-02 10:33:48,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3158407582257441, 'b1': 0.5083164458527899}
 2023-07-02 10:33:48,860 [prior] Evaluating prior at array([0.31584076, 0.50831645])
 2023-07-02 10:33:48,860 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,860 [model] Got input parameters: {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083164458527899, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,860 [classy] Got parameters {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,860 [classy] Re-using computed results
 2023-07-02 10:33:48,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.85812140684394}
 2023-07-02 10:33:48,860 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083164458527899, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,860 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,880 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67881
 2023-07-02 10:33:48,880 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,880 [mcmc] New sample, #222:
   Omega_m:0.3158408, b1:0.5048924
 2023-07-02 10:33:48,880 [model] Posterior to be computed for parameters {'Omega_m': 0.3162428082794476, 'b1': 0.5080432281345565}
 2023-07-02 10:33:48,880 [prior] Evaluating prior at array([0.31624281, 0.50804323])
 2023-07-02 10:33:48,880 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,880 [model] Got input parameters: {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080432281345565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,880 [classy] Got parameters {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,880 [classy] Computing new state
 2023-07-02 10:33:48,880 [classy] Setting parameters: {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:48,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.81023501004276}
 2023-07-02 10:33:48,924 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:48,926 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00106076
 2023-07-02 10:33:48,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080432281345565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,926 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,945 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65057
 2023-07-02 10:33:48,945 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,945 [mcmc] New sample, #223:
   Omega_m:0.3158408, b1:0.5083164
 2023-07-02 10:33:48,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3162428082794476, 'b1': 0.5216074106776183}
 2023-07-02 10:33:48,946 [prior] Evaluating prior at array([0.31624281, 0.52160741])
 2023-07-02 10:33:48,946 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,946 [model] Got input parameters: {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5216074106776183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,946 [classy] Got parameters {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,946 [classy] Re-using computed results
 2023-07-02 10:33:48,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.81023501004276}
 2023-07-02 10:33:48,946 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:48,946 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5216074106776183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,946 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:48,965 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39239
 2023-07-02 10:33:48,965 [model] Computed derived parameters: {}
 2023-07-02 10:33:48,965 [mcmc] New sample, #224:
   Omega_m:0.3162428, b1:0.5080432
 2023-07-02 10:33:48,965 [model] Posterior to be computed for parameters {'Omega_m': 0.3052770838808455, 'b1': 0.5290592942711271}
 2023-07-02 10:33:48,965 [prior] Evaluating prior at array([0.30527708, 0.52905929])
 2023-07-02 10:33:48,966 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:48,966 [model] Got input parameters: {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5290592942711271, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:48,966 [classy] Got parameters {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:48,966 [classy] Computing new state
 2023-07-02 10:33:48,966 [classy] Setting parameters: {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,009 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.13629762813025}
 2023-07-02 10:33:49,010 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,011 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0034455
 2023-07-02 10:33:49,011 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5290592942711271, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,011 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,031 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0206
 2023-07-02 10:33:49,032 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,032 [mcmc] New sample, #225:
   Omega_m:0.3162428, b1:0.5216074
 2023-07-02 10:33:49,032 [model] Posterior to be computed for parameters {'Omega_m': 0.3052770838808455, 'b1': 0.5182963940106264}
 2023-07-02 10:33:49,032 [prior] Evaluating prior at array([0.30527708, 0.51829639])
 2023-07-02 10:33:49,032 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,032 [model] Got input parameters: {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5182963940106264, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,032 [classy] Got parameters {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,032 [classy] Re-using computed results
 2023-07-02 10:33:49,032 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.13629762813025}
 2023-07-02 10:33:49,032 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5182963940106264, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,032 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,052 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35027
 2023-07-02 10:33:49,052 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,052 [mcmc] New sample, #226:
   Omega_m:0.3052771, b1:0.5290593
 2023-07-02 10:33:49,052 [model] Posterior to be computed for parameters {'Omega_m': 0.3159723928377348, 'b1': 0.5110282743273056}
 2023-07-02 10:33:49,052 [prior] Evaluating prior at array([0.31597239, 0.51102827])
 2023-07-02 10:33:49,052 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,052 [model] Got input parameters: {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5110282743273056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,052 [classy] Got parameters {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,052 [classy] Computing new state
 2023-07-02 10:33:49,052 [classy] Setting parameters: {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8424401880562}
 2023-07-02 10:33:49,096 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000942208
 2023-07-02 10:33:49,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5110282743273056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,098 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5001
 2023-07-02 10:33:49,117 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,117 [mcmc] New sample, #227:
   Omega_m:0.3052771, b1:0.5182964
 2023-07-02 10:33:49,117 [model] Posterior to be computed for parameters {'Omega_m': 0.3159723928377348, 'b1': 0.5174522627693926}
 2023-07-02 10:33:49,117 [prior] Evaluating prior at array([0.31597239, 0.51745226])
 2023-07-02 10:33:49,118 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,118 [model] Got input parameters: {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5174522627693926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,118 [classy] Got parameters {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,118 [classy] Re-using computed results
 2023-07-02 10:33:49,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8424401880562}
 2023-07-02 10:33:49,118 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5174522627693926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,118 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94416
 2023-07-02 10:33:49,140 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,140 [mcmc] New sample, #228:
   Omega_m:0.3159724, b1:0.5110283
 2023-07-02 10:33:49,140 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5158865759179162}
 2023-07-02 10:33:49,140 [prior] Evaluating prior at array([0.31827636, 0.51588658])
 2023-07-02 10:33:49,140 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,141 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5158865759179162, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,141 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,141 [classy] Computing new state
 2023-07-02 10:33:49,141 [classy] Setting parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
 2023-07-02 10:33:49,185 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,186 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00223036
 2023-07-02 10:33:49,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5158865759179162, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,206 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59833
 2023-07-02 10:33:49,206 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,206 [mcmc] New sample, #229:
   Omega_m:0.3159724, b1:0.5174523
 2023-07-02 10:33:49,206 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5094458228165901}
 2023-07-02 10:33:49,206 [prior] Evaluating prior at array([0.31827636, 0.50944582])
 2023-07-02 10:33:49,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,206 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5094458228165901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,206 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,206 [classy] Re-using computed results
 2023-07-02 10:33:49,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
 2023-07-02 10:33:49,206 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5094458228165901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,207 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,226 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25249
 2023-07-02 10:33:49,226 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,226 [mcmc] New sample, #230:
   Omega_m:0.3182764, b1:0.5158866
 2023-07-02 10:33:49,226 [model] Posterior to be computed for parameters {'Omega_m': 0.3277631378551154, 'b1': 0.5029989738650087}
 2023-07-02 10:33:49,226 [prior] Evaluating prior at array([0.32776314, 0.50299897])
 2023-07-02 10:33:49,227 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,227 [model] Got input parameters: {'Omega_m': 0.3277631378551154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029989738650087, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,227 [classy] Got parameters {'Omega_m': 0.3277631378551154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,227 [classy] Computing new state
 2023-07-02 10:33:49,227 [classy] Setting parameters: {'Omega_m': 0.3277631378551154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4605346942738}
 2023-07-02 10:33:49,270 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,272 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0139913
 2023-07-02 10:33:49,272 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029989738650087, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,272 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,292 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.221182
 2023-07-02 10:33:49,292 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,292 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5662847766367575}
 2023-07-02 10:33:49,292 [prior] Evaluating prior at array([0.31827636, 0.56628478])
 2023-07-02 10:33:49,292 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,292 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5662847766367575, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,292 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,292 [classy] Re-using computed results
 2023-07-02 10:33:49,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
 2023-07-02 10:33:49,292 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5662847766367575, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,292 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,311 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.1358
 2023-07-02 10:33:49,312 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,312 [model] Posterior to be computed for parameters {'Omega_m': 0.2900484016656151, 'b1': 0.5286284547481757}
 2023-07-02 10:33:49,312 [prior] Evaluating prior at array([0.2900484 , 0.52862845])
 2023-07-02 10:33:49,312 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,312 [model] Got input parameters: {'Omega_m': 0.2900484016656151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5286284547481757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,312 [classy] Got parameters {'Omega_m': 0.2900484016656151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,312 [classy] Computing new state
 2023-07-02 10:33:49,312 [classy] Setting parameters: {'Omega_m': 0.2900484016656151, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,356 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.04911288589634}
 2023-07-02 10:33:49,356 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,357 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.032881
 2023-07-02 10:33:49,357 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5286284547481757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,358 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,377 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.76947
 2023-07-02 10:33:49,377 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,377 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5092265797852127}
 2023-07-02 10:33:49,377 [prior] Evaluating prior at array([0.31827636, 0.50922658])
 2023-07-02 10:33:49,377 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,377 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5092265797852127, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,377 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,377 [classy] Re-using computed results
 2023-07-02 10:33:49,377 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
 2023-07-02 10:33:49,377 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,377 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5092265797852127, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,377 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,397 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2706
 2023-07-02 10:33:49,397 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,397 [mcmc] New sample, #231:
   Omega_m:0.3182764, b1:0.5094458
 2023-07-02 10:33:49,397 [model] Posterior to be computed for parameters {'Omega_m': 0.3282200456929302, 'b1': 0.5024692338799789}
 2023-07-02 10:33:49,397 [prior] Evaluating prior at array([0.32822005, 0.50246923])
 2023-07-02 10:33:49,398 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,398 [model] Got input parameters: {'Omega_m': 0.3282200456929302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5024692338799789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,398 [classy] Got parameters {'Omega_m': 0.3282200456929302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,398 [classy] Computing new state
 2023-07-02 10:33:49,398 [classy] Setting parameters: {'Omega_m': 0.3282200456929302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.40788419294526}
 2023-07-02 10:33:49,442 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0148123
 2023-07-02 10:33:49,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5024692338799789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,443 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,463 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.116006
 2023-07-02 10:33:49,463 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,463 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5068114980934646}
 2023-07-02 10:33:49,463 [prior] Evaluating prior at array([0.31827636, 0.5068115 ])
 2023-07-02 10:33:49,463 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,463 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5068114980934646, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,463 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,463 [classy] Re-using computed results
 2023-07-02 10:33:49,463 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
 2023-07-02 10:33:49,463 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,463 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5068114980934646, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,463 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,482 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45217
 2023-07-02 10:33:49,482 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,483 [mcmc] New sample, #232:
   Omega_m:0.3182764, b1:0.5092266
 2023-07-02 10:33:49,483 [model] Posterior to be computed for parameters {'Omega_m': 0.3109455218059237, 'b1': 0.5117932527218599}
 2023-07-02 10:33:49,483 [prior] Evaluating prior at array([0.31094552, 0.51179325])
 2023-07-02 10:33:49,483 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,483 [model] Got input parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117932527218599, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,483 [classy] Got parameters {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,483 [classy] Computing new state
 2023-07-02 10:33:49,483 [classy] Setting parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,527 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4456581783046}
 2023-07-02 10:33:49,527 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,528 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000348079
 2023-07-02 10:33:49,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117932527218599, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,529 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,548 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77858
 2023-07-02 10:33:49,548 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,548 [mcmc] New sample, #233:
   Omega_m:0.3182764, b1:0.5068115
 2023-07-02 10:33:49,549 [model] Posterior to be computed for parameters {'Omega_m': 0.3109455218059237, 'b1': 0.5061447730998416}
 2023-07-02 10:33:49,549 [prior] Evaluating prior at array([0.31094552, 0.50614477])
 2023-07-02 10:33:49,549 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,549 [model] Got input parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061447730998416, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,549 [classy] Got parameters {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,549 [classy] Re-using computed results
 2023-07-02 10:33:49,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4456581783046}
 2023-07-02 10:33:49,549 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,549 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061447730998416, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,549 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,568 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81696
 2023-07-02 10:33:49,568 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,568 [mcmc] New sample, #234:
   Omega_m:0.3109455, b1:0.5117933
 2023-07-02 10:33:49,569 [model] Posterior to be computed for parameters {'Omega_m': 0.2927909853804227, 'b1': 0.5184818962318251}
 2023-07-02 10:33:49,569 [prior] Evaluating prior at array([0.29279099, 0.5184819 ])
 2023-07-02 10:33:49,569 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,569 [model] Got input parameters: {'Omega_m': 0.2927909853804227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5184818962318251, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,569 [classy] Got parameters {'Omega_m': 0.2927909853804227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,569 [classy] Computing new state
 2023-07-02 10:33:49,569 [classy] Setting parameters: {'Omega_m': 0.2927909853804227, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,613 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.6982631267611}
 2023-07-02 10:33:49,613 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,614 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0252018
 2023-07-02 10:33:49,615 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5184818962318251, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,615 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,634 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.44026
 2023-07-02 10:33:49,634 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,635 [model] Posterior to be computed for parameters {'Omega_m': 0.3109455218059237, 'b1': 0.5052567977639995}
 2023-07-02 10:33:49,635 [prior] Evaluating prior at array([0.31094552, 0.5052568 ])
 2023-07-02 10:33:49,635 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,635 [model] Got input parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5052567977639995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,635 [classy] Got parameters {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,635 [classy] Re-using computed results
 2023-07-02 10:33:49,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4456581783046}
 2023-07-02 10:33:49,635 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5052567977639995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,635 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,655 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80741
 2023-07-02 10:33:49,655 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,655 [mcmc] New sample, #235:
   Omega_m:0.3109455, b1:0.5061448
 2023-07-02 10:33:49,655 [model] Posterior to be computed for parameters {'Omega_m': 0.321569154386066, 'b1': 0.4980373865833282}
 2023-07-02 10:33:49,655 [prior] Evaluating prior at array([0.32156915, 0.49803739])
 2023-07-02 10:33:49,655 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,655 [model] Got input parameters: {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4980373865833282, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,655 [classy] Got parameters {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,655 [classy] Computing new state
 2023-07-02 10:33:49,655 [classy] Setting parameters: {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,699 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1808502939914}
 2023-07-02 10:33:49,699 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,701 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00515123
 2023-07-02 10:33:49,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4980373865833282, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45117
 2023-07-02 10:33:49,720 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,721 [mcmc] New sample, #236:
   Omega_m:0.3109455, b1:0.5052568
 2023-07-02 10:33:49,721 [model] Posterior to be computed for parameters {'Omega_m': 0.321569154386066, 'b1': 0.4982091241827604}
 2023-07-02 10:33:49,721 [prior] Evaluating prior at array([0.32156915, 0.49820912])
 2023-07-02 10:33:49,721 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,721 [model] Got input parameters: {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4982091241827604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,721 [classy] Got parameters {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,721 [classy] Re-using computed results
 2023-07-02 10:33:49,721 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1808502939914}
 2023-07-02 10:33:49,721 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4982091241827604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,721 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,740 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.442
 2023-07-02 10:33:49,740 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,740 [mcmc] New sample, #237:
   Omega_m:0.3215692, b1:0.4980374
 2023-07-02 10:33:49,741 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5045312849027467}
 2023-07-02 10:33:49,741 [prior] Evaluating prior at array([0.31226586, 0.50453128])
 2023-07-02 10:33:49,741 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,741 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5045312849027467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,741 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,741 [classy] Computing new state
 2023-07-02 10:33:49,741 [classy] Setting parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:49,784 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,786 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000205289
 2023-07-02 10:33:49,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5045312849027467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,786 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,806 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87637
 2023-07-02 10:33:49,806 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,806 [mcmc] New sample, #238:
   Omega_m:0.3215692, b1:0.4982091
 2023-07-02 10:33:49,806 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.43937782890161314}
 2023-07-02 10:33:49,806 [prior] Evaluating prior at array([0.31226586, 0.43937783])
 2023-07-02 10:33:49,806 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,807 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43937782890161314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,807 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,807 [classy] Re-using computed results
 2023-07-02 10:33:49,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:49,807 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,807 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43937782890161314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,807 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,827 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.05725
 2023-07-02 10:33:49,827 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,827 [model] Posterior to be computed for parameters {'Omega_m': 0.33161555747267324, 'b1': 0.49138197591479843}
 2023-07-02 10:33:49,827 [prior] Evaluating prior at array([0.33161556, 0.49138198])
 2023-07-02 10:33:49,827 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,827 [model] Got input parameters: {'Omega_m': 0.33161555747267324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49138197591479843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,827 [classy] Got parameters {'Omega_m': 0.33161555747267324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,827 [classy] Computing new state
 2023-07-02 10:33:49,827 [classy] Setting parameters: {'Omega_m': 0.33161555747267324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01868928366534}
 2023-07-02 10:33:49,871 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,872 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0216216
 2023-07-02 10:33:49,873 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49138197591479843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,873 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,892 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.261042
 2023-07-02 10:33:49,892 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,892 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5708744575215448}
 2023-07-02 10:33:49,892 [prior] Evaluating prior at array([0.31226586, 0.57087446])
 2023-07-02 10:33:49,893 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,893 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5708744575215448, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,893 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,893 [classy] Re-using computed results
 2023-07-02 10:33:49,893 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:49,893 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5708744575215448, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,893 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,912 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.45656
 2023-07-02 10:33:49,913 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,913 [model] Posterior to be computed for parameters {'Omega_m': 0.30800791597884786, 'b1': 0.5074248190444052}
 2023-07-02 10:33:49,913 [prior] Evaluating prior at array([0.30800792, 0.50742482])
 2023-07-02 10:33:49,913 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,913 [model] Got input parameters: {'Omega_m': 0.30800791597884786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5074248190444052, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,913 [classy] Got parameters {'Omega_m': 0.30800791597884786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,913 [classy] Computing new state
 2023-07-02 10:33:49,913 [classy] Setting parameters: {'Omega_m': 0.30800791597884786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:49,957 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80217753036325}
 2023-07-02 10:33:49,957 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:49,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00144487
 2023-07-02 10:33:49,959 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5074248190444052, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,959 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,978 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54355
 2023-07-02 10:33:49,978 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,978 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5372879803879943}
 2023-07-02 10:33:49,978 [prior] Evaluating prior at array([0.31226586, 0.53728798])
 2023-07-02 10:33:49,978 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,978 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5372879803879943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,978 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,978 [classy] Re-using computed results
 2023-07-02 10:33:49,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:49,978 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:49,978 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5372879803879943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,979 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:49,998 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0397168
 2023-07-02 10:33:49,998 [model] Computed derived parameters: {}
 2023-07-02 10:33:49,998 [mcmc] New sample, #239:
   Omega_m:0.3122659, b1:0.5045313
 2023-07-02 10:33:49,998 [model] Posterior to be computed for parameters {'Omega_m': 0.3388729996660182, 'b1': 0.5192067934460168}
 2023-07-02 10:33:49,998 [prior] Evaluating prior at array([0.338873  , 0.51920679])
 2023-07-02 10:33:49,998 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:49,998 [model] Got input parameters: {'Omega_m': 0.3388729996660182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5192067934460168, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:49,998 [classy] Got parameters {'Omega_m': 0.3388729996660182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:49,998 [classy] Computing new state
 2023-07-02 10:33:49,998 [classy] Setting parameters: {'Omega_m': 0.3388729996660182, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.198790172366}
 2023-07-02 10:33:50,043 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,044 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0402547
 2023-07-02 10:33:50,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5192067934460168, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,044 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,064 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2207
 2023-07-02 10:33:50,064 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,064 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.518637203147961}
 2023-07-02 10:33:50,064 [prior] Evaluating prior at array([0.31226586, 0.5186372 ])
 2023-07-02 10:33:50,064 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,064 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.518637203147961, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,064 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,064 [classy] Re-using computed results
 2023-07-02 10:33:50,064 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:50,064 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,064 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.518637203147961, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,064 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,084 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.3942
 2023-07-02 10:33:50,084 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,084 [mcmc] New sample, #240:
   Omega_m:0.3122659, b1:0.537288
 2023-07-02 10:33:50,084 [mcmc] Learn + convergence test @ 240 samples accepted.
 2023-07-02 10:33:50,084 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:33:50,089 [mcmc]  - Acceptance rate: 0.298
 2023-07-02 10:33:50,089 [mcmc]  - Condition number = 5.34158
 2023-07-02 10:33:50,089 [mcmc]  - Eigenvalues = array([0.11773969, 0.62891615])
 2023-07-02 10:33:50,089 [mcmc]  - Convergence of means: R-1 = 0.628916 after 192 accepted steps
 2023-07-02 10:33:50,090 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:33:50,090 [mcmc] array([[ 3.58509594e-05, -1.86866609e-05],
       [-1.86866609e-05,  6.58047122e-05]])
 2023-07-02 10:33:50,100 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:33:50,100 [model] Posterior to be computed for parameters {'Omega_m': 0.31990844627854803, 'b1': 0.5146536436049877}
 2023-07-02 10:33:50,100 [prior] Evaluating prior at array([0.31990845, 0.51465364])
 2023-07-02 10:33:50,100 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,100 [model] Got input parameters: {'Omega_m': 0.31990844627854803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5146536436049877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,100 [classy] Got parameters {'Omega_m': 0.31990844627854803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,100 [classy] Computing new state
 2023-07-02 10:33:50,100 [classy] Setting parameters: {'Omega_m': 0.31990844627854803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.37608405371185}
 2023-07-02 10:33:50,147 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00352083
 2023-07-02 10:33:50,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5146536436049877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,149 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.31016
 2023-07-02 10:33:50,170 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,170 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5278459261278375}
 2023-07-02 10:33:50,170 [prior] Evaluating prior at array([0.31226586, 0.52784593])
 2023-07-02 10:33:50,170 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,170 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5278459261278375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,170 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,170 [classy] Re-using computed results
 2023-07-02 10:33:50,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:50,170 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,170 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5278459261278375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,170 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.48164
 2023-07-02 10:33:50,190 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,190 [model] Posterior to be computed for parameters {'Omega_m': 0.2846997088089088, 'b1': 0.5330055580070654}
 2023-07-02 10:33:50,190 [prior] Evaluating prior at array([0.28469971, 0.53300556])
 2023-07-02 10:33:50,190 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,190 [model] Got input parameters: {'Omega_m': 0.2846997088089088, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330055580070654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,190 [classy] Got parameters {'Omega_m': 0.2846997088089088, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,190 [classy] Computing new state
 2023-07-02 10:33:50,190 [classy] Setting parameters: {'Omega_m': 0.2846997088089088, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.74170121702863}
 2023-07-02 10:33:50,235 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0510247
 2023-07-02 10:33:50,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330055580070654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,237 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.28239
 2023-07-02 10:33:50,257 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,257 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5692318241211897}
 2023-07-02 10:33:50,257 [prior] Evaluating prior at array([0.31226586, 0.56923182])
 2023-07-02 10:33:50,257 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,257 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5692318241211897, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,257 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,257 [classy] Re-using computed results
 2023-07-02 10:33:50,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
 2023-07-02 10:33:50,257 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5692318241211897, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,257 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,276 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.82733
 2023-07-02 10:33:50,277 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,277 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.5195853811504594}
 2023-07-02 10:33:50,277 [prior] Evaluating prior at array([0.31044675, 0.51958538])
 2023-07-02 10:33:50,277 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,277 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195853811504594, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,277 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,277 [classy] Computing new state
 2023-07-02 10:33:50,277 [classy] Setting parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
 2023-07-02 10:33:50,322 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000458192
 2023-07-02 10:33:50,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195853811504594, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,324 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,343 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47107
 2023-07-02 10:33:50,343 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,343 [mcmc] New sample, #241:
   Omega_m:0.3122659, b1:0.5186372
 2023-07-02 10:33:50,343 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.49637575802326056}
 2023-07-02 10:33:50,344 [prior] Evaluating prior at array([0.31044675, 0.49637576])
 2023-07-02 10:33:50,344 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,344 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49637575802326056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,344 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,344 [classy] Re-using computed results
 2023-07-02 10:33:50,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
 2023-07-02 10:33:50,344 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49637575802326056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,344 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40034
 2023-07-02 10:33:50,364 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,364 [mcmc] New sample, #242:
   Omega_m:0.3104467, b1:0.5195854
 2023-07-02 10:33:50,364 [model] Posterior to be computed for parameters {'Omega_m': 0.2925248739989793, 'b1': 0.5057172097658483}
 2023-07-02 10:33:50,364 [prior] Evaluating prior at array([0.29252487, 0.50571721])
 2023-07-02 10:33:50,364 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,364 [model] Got input parameters: {'Omega_m': 0.2925248739989793, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5057172097658483, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,364 [classy] Got parameters {'Omega_m': 0.2925248739989793, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,364 [classy] Computing new state
 2023-07-02 10:33:50,364 [classy] Setting parameters: {'Omega_m': 0.2925248739989793, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,409 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7321800975787}
 2023-07-02 10:33:50,409 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,410 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0258996
 2023-07-02 10:33:50,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5057172097658483, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,411 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,431 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.44041
 2023-07-02 10:33:50,431 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,431 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.4987342841705211}
 2023-07-02 10:33:50,431 [prior] Evaluating prior at array([0.31044675, 0.49873428])
 2023-07-02 10:33:50,431 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,431 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4987342841705211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,431 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,431 [classy] Re-using computed results
 2023-07-02 10:33:50,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
 2023-07-02 10:33:50,431 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4987342841705211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,431 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,451 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53806
 2023-07-02 10:33:50,451 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,451 [mcmc] New sample, #243:
   Omega_m:0.3104467, b1:0.4963758
 2023-07-02 10:33:50,451 [model] Posterior to be computed for parameters {'Omega_m': 0.2850362418228118, 'b1': 0.5119790493109317}
 2023-07-02 10:33:50,451 [prior] Evaluating prior at array([0.28503624, 0.51197905])
 2023-07-02 10:33:50,451 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,451 [model] Got input parameters: {'Omega_m': 0.2850362418228118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119790493109317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,451 [classy] Got parameters {'Omega_m': 0.2850362418228118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,451 [classy] Computing new state
 2023-07-02 10:33:50,451 [classy] Setting parameters: {'Omega_m': 0.2850362418228118, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.69779080134344}
 2023-07-02 10:33:50,495 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.049757
 2023-07-02 10:33:50,497 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119790493109317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,497 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,516 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.43901
 2023-07-02 10:33:50,516 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,517 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.49630269103171}
 2023-07-02 10:33:50,517 [prior] Evaluating prior at array([0.31044675, 0.49630269])
 2023-07-02 10:33:50,517 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,517 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49630269103171, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,517 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,517 [classy] Re-using computed results
 2023-07-02 10:33:50,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
 2023-07-02 10:33:50,517 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49630269103171, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,517 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39561
 2023-07-02 10:33:50,536 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,537 [model] Posterior to be computed for parameters {'Omega_m': 0.3296439143958108, 'b1': 0.4887281108346089}
 2023-07-02 10:33:50,537 [prior] Evaluating prior at array([0.32964391, 0.48872811])
 2023-07-02 10:33:50,537 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,537 [model] Got input parameters: {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4887281108346089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,537 [classy] Got parameters {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,537 [classy] Computing new state
 2023-07-02 10:33:50,537 [classy] Setting parameters: {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2442271859258}
 2023-07-02 10:33:50,581 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0175167
 2023-07-02 10:33:50,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4887281108346089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,583 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,602 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20364
 2023-07-02 10:33:50,602 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,602 [mcmc] New sample, #244:
   Omega_m:0.3104467, b1:0.4987343
 2023-07-02 10:33:50,603 [model] Posterior to be computed for parameters {'Omega_m': 0.3296439143958108, 'b1': 0.49681951733074364}
 2023-07-02 10:33:50,603 [prior] Evaluating prior at array([0.32964391, 0.49681952])
 2023-07-02 10:33:50,603 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,603 [model] Got input parameters: {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49681951733074364, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,603 [classy] Got parameters {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,603 [classy] Re-using computed results
 2023-07-02 10:33:50,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2442271859258}
 2023-07-02 10:33:50,603 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49681951733074364, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,603 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.339908
 2023-07-02 10:33:50,622 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,623 [mcmc] New sample, #245:
   Omega_m:0.3296439, b1:0.4887281
 2023-07-02 10:33:50,623 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.49400726090743}
 2023-07-02 10:33:50,623 [prior] Evaluating prior at array([0.33503932, 0.49400726])
 2023-07-02 10:33:50,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,623 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49400726090743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,623 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,623 [classy] Computing new state
 2023-07-02 10:33:50,623 [classy] Setting parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
 2023-07-02 10:33:50,668 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0297304
 2023-07-02 10:33:50,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49400726090743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,670 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,689 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.64975
 2023-07-02 10:33:50,689 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,689 [mcmc] New sample, #246:
   Omega_m:0.3296439, b1:0.4968195
 2023-07-02 10:33:50,689 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.4673758432115313}
 2023-07-02 10:33:50,689 [prior] Evaluating prior at array([0.33503932, 0.46737584])
 2023-07-02 10:33:50,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,689 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4673758432115313, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,689 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,689 [classy] Re-using computed results
 2023-07-02 10:33:50,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
 2023-07-02 10:33:50,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4673758432115313, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,690 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,709 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.85974
 2023-07-02 10:33:50,709 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,709 [mcmc] New sample, #247:
   Omega_m:0.3350393, b1:0.4940073
 2023-07-02 10:33:50,709 [model] Posterior to be computed for parameters {'Omega_m': 0.34527463262703534, 'b1': 0.46204087188293297}
 2023-07-02 10:33:50,709 [prior] Evaluating prior at array([0.34527463, 0.46204087])
 2023-07-02 10:33:50,710 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,710 [model] Got input parameters: {'Omega_m': 0.34527463262703534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46204087188293297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,710 [classy] Got parameters {'Omega_m': 0.34527463262703534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,710 [classy] Computing new state
 2023-07-02 10:33:50,710 [classy] Setting parameters: {'Omega_m': 0.34527463262703534, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.488679549445}
 2023-07-02 10:33:50,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0611211
 2023-07-02 10:33:50,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46204087188293297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,755 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,775 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.31346
 2023-07-02 10:33:50,775 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,775 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.4531453533363623}
 2023-07-02 10:33:50,775 [prior] Evaluating prior at array([0.33503932, 0.45314535])
 2023-07-02 10:33:50,775 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,775 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4531453533363623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,775 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,775 [classy] Re-using computed results
 2023-07-02 10:33:50,776 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
 2023-07-02 10:33:50,776 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,776 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4531453533363623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,776 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,795 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.568389
 2023-07-02 10:33:50,795 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,795 [mcmc] New sample, #248:
   Omega_m:0.3350393, b1:0.4673758
 2023-07-02 10:33:50,795 [model] Posterior to be computed for parameters {'Omega_m': 0.3148651931816438, 'b1': 0.46366074955355335}
 2023-07-02 10:33:50,795 [prior] Evaluating prior at array([0.31486519, 0.46366075])
 2023-07-02 10:33:50,795 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,795 [model] Got input parameters: {'Omega_m': 0.3148651931816438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46366074955355335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,795 [classy] Got parameters {'Omega_m': 0.3148651931816438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,795 [classy] Computing new state
 2023-07-02 10:33:50,795 [classy] Setting parameters: {'Omega_m': 0.3148651931816438, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9745537903658}
 2023-07-02 10:33:50,840 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,841 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000548134
 2023-07-02 10:33:50,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46366074955355335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,841 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,861 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.616224
 2023-07-02 10:33:50,861 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,861 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.47282944921484393}
 2023-07-02 10:33:50,861 [prior] Evaluating prior at array([0.33503932, 0.47282945])
 2023-07-02 10:33:50,862 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,862 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47282944921484393, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,862 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,862 [classy] Re-using computed results
 2023-07-02 10:33:50,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
 2023-07-02 10:33:50,862 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,862 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47282944921484393, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,862 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,881 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.676453
 2023-07-02 10:33:50,882 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,882 [mcmc] New sample, #249:
   Omega_m:0.3350393, b1:0.4531454
 2023-07-02 10:33:50,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3605098197317599, 'b1': 0.45955341354428675}
 2023-07-02 10:33:50,882 [prior] Evaluating prior at array([0.36050982, 0.45955341])
 2023-07-02 10:33:50,882 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,882 [model] Got input parameters: {'Omega_m': 0.3605098197317599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45955341354428675, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,882 [classy] Got parameters {'Omega_m': 0.3605098197317599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,882 [classy] Computing new state
 2023-07-02 10:33:50,882 [classy] Setting parameters: {'Omega_m': 0.3605098197317599, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:50,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.8461063868818}
 2023-07-02 10:33:50,926 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:50,928 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.126362
 2023-07-02 10:33:50,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45955341354428675, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,928 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,947 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.5591
 2023-07-02 10:33:50,947 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,947 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.46441434597773756}
 2023-07-02 10:33:50,947 [prior] Evaluating prior at array([0.33503932, 0.46441435])
 2023-07-02 10:33:50,947 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,947 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46441434597773756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,948 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,948 [classy] Re-using computed results
 2023-07-02 10:33:50,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
 2023-07-02 10:33:50,948 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:50,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46441434597773756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,948 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:50,967 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.890018
 2023-07-02 10:33:50,967 [model] Computed derived parameters: {}
 2023-07-02 10:33:50,968 [mcmc] New sample, #250:
   Omega_m:0.3350393, b1:0.4728294
 2023-07-02 10:33:50,968 [model] Posterior to be computed for parameters {'Omega_m': 0.316968585480722, 'b1': 0.47383338719327717}
 2023-07-02 10:33:50,968 [prior] Evaluating prior at array([0.31696859, 0.47383339])
 2023-07-02 10:33:50,968 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:50,968 [model] Got input parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47383338719327717, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:50,968 [classy] Got parameters {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:50,968 [classy] Computing new state
 2023-07-02 10:33:50,968 [classy] Setting parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,012 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72392161231042}
 2023-07-02 10:33:51,012 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00142199
 2023-07-02 10:33:51,013 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47383338719327717, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,013 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,033 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.52007
 2023-07-02 10:33:51,033 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,033 [mcmc] New sample, #251:
   Omega_m:0.3350393, b1:0.4644143
 2023-07-02 10:33:51,033 [model] Posterior to be computed for parameters {'Omega_m': 0.316968585480722, 'b1': 0.43877750695983925}
 2023-07-02 10:33:51,034 [prior] Evaluating prior at array([0.31696859, 0.43877751])
 2023-07-02 10:33:51,034 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,034 [model] Got input parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43877750695983925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,034 [classy] Got parameters {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,034 [classy] Re-using computed results
 2023-07-02 10:33:51,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72392161231042}
 2023-07-02 10:33:51,034 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,034 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43877750695983925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,034 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,054 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.6577
 2023-07-02 10:33:51,054 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,054 [model] Posterior to be computed for parameters {'Omega_m': 0.3011351132781472, 'b1': 0.48208629676721154}
 2023-07-02 10:33:51,054 [prior] Evaluating prior at array([0.30113511, 0.4820863 ])
 2023-07-02 10:33:51,054 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,054 [model] Got input parameters: {'Omega_m': 0.3011351132781472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48208629676721154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,054 [classy] Got parameters {'Omega_m': 0.3011351132781472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,054 [classy] Computing new state
 2023-07-02 10:33:51,054 [classy] Setting parameters: {'Omega_m': 0.3011351132781472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.64811168487412}
 2023-07-02 10:33:51,098 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,100 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00832866
 2023-07-02 10:33:51,100 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48208629676721154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,100 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,120 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.05454
 2023-07-02 10:33:51,121 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,121 [model] Posterior to be computed for parameters {'Omega_m': 0.316968585480722, 'b1': 0.4747005287375945}
 2023-07-02 10:33:51,121 [prior] Evaluating prior at array([0.31696859, 0.47470053])
 2023-07-02 10:33:51,122 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,122 [model] Got input parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4747005287375945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,122 [classy] Got parameters {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,122 [classy] Re-using computed results
 2023-07-02 10:33:51,122 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72392161231042}
 2023-07-02 10:33:51,122 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,122 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4747005287375945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,122 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,150 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62197
 2023-07-02 10:33:51,150 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,150 [mcmc] New sample, #252:
   Omega_m:0.3169686, b1:0.4738334
 2023-07-02 10:33:51,150 [model] Posterior to be computed for parameters {'Omega_m': 0.31256139265984656, 'b1': 0.47699769788408547}
 2023-07-02 10:33:51,150 [prior] Evaluating prior at array([0.31256139, 0.4769977 ])
 2023-07-02 10:33:51,150 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,150 [model] Got input parameters: {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47699769788408547, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,150 [classy] Got parameters {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,150 [classy] Computing new state
 2023-07-02 10:33:51,150 [classy] Setting parameters: {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,196 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25081219144346}
 2023-07-02 10:33:51,196 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,198 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202741
 2023-07-02 10:33:51,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47699769788408547, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,198 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,217 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.869153
 2023-07-02 10:33:51,218 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,218 [mcmc] New sample, #253:
   Omega_m:0.3169686, b1:0.4747005
 2023-07-02 10:33:51,218 [model] Posterior to be computed for parameters {'Omega_m': 0.31256139265984656, 'b1': 0.5074853598968554}
 2023-07-02 10:33:51,218 [prior] Evaluating prior at array([0.31256139, 0.50748536])
 2023-07-02 10:33:51,218 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,218 [model] Got input parameters: {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5074853598968554, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,218 [classy] Got parameters {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,218 [classy] Re-using computed results
 2023-07-02 10:33:51,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25081219144346}
 2023-07-02 10:33:51,218 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5074853598968554, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,218 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,240 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8676
 2023-07-02 10:33:51,240 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,240 [mcmc] New sample, #254:
   Omega_m:0.3125614, b1:0.4769977
 2023-07-02 10:33:51,240 [model] Posterior to be computed for parameters {'Omega_m': 0.31793550913875046, 'b1': 0.5046841993697935}
 2023-07-02 10:33:51,240 [prior] Evaluating prior at array([0.31793551, 0.5046842 ])
 2023-07-02 10:33:51,240 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,240 [model] Got input parameters: {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5046841993697935, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,240 [classy] Got parameters {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,240 [classy] Computing new state
 2023-07-02 10:33:51,240 [classy] Setting parameters: {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60920122997302}
 2023-07-02 10:33:51,285 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00200026
 2023-07-02 10:33:51,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5046841993697935, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,287 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,306 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62991
 2023-07-02 10:33:51,306 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,307 [mcmc] New sample, #255:
   Omega_m:0.3125614, b1:0.5074854
 2023-07-02 10:33:51,307 [model] Posterior to be computed for parameters {'Omega_m': 0.31793550913875046, 'b1': 0.5119266389463657}
 2023-07-02 10:33:51,307 [prior] Evaluating prior at array([0.31793551, 0.51192664])
 2023-07-02 10:33:51,307 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,307 [model] Got input parameters: {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119266389463657, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,307 [classy] Got parameters {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,307 [classy] Re-using computed results
 2023-07-02 10:33:51,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60920122997302}
 2023-07-02 10:33:51,307 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,307 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119266389463657, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,307 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,327 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09888
 2023-07-02 10:33:51,327 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,327 [mcmc] New sample, #256:
   Omega_m:0.3179355, b1:0.5046842
 2023-07-02 10:33:51,327 [model] Posterior to be computed for parameters {'Omega_m': 0.3151987641590579, 'b1': 0.5133531175200704}
 2023-07-02 10:33:51,327 [prior] Evaluating prior at array([0.31519876, 0.51335312])
 2023-07-02 10:33:51,327 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,328 [model] Got input parameters: {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133531175200704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,328 [classy] Got parameters {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,328 [classy] Computing new state
 2023-07-02 10:33:51,328 [classy] Setting parameters: {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9347050679899}
 2023-07-02 10:33:51,371 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,373 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000651397
 2023-07-02 10:33:51,373 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133531175200704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,373 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,392 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.43851
 2023-07-02 10:33:51,392 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,392 [mcmc] New sample, #257:
   Omega_m:0.3179355, b1:0.5119266
 2023-07-02 10:33:51,393 [model] Posterior to be computed for parameters {'Omega_m': 0.3151987641590579, 'b1': 0.5060283679983525}
 2023-07-02 10:33:51,393 [prior] Evaluating prior at array([0.31519876, 0.50602837])
 2023-07-02 10:33:51,393 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,393 [model] Got input parameters: {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5060283679983525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,393 [classy] Got parameters {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,393 [classy] Re-using computed results
 2023-07-02 10:33:51,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9347050679899}
 2023-07-02 10:33:51,393 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5060283679983525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,393 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,412 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82773
 2023-07-02 10:33:51,412 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,412 [mcmc] New sample, #258:
   Omega_m:0.3151988, b1:0.5133531
 2023-07-02 10:33:51,412 [model] Posterior to be computed for parameters {'Omega_m': 0.3034299824285535, 'b1': 0.5121626315493019}
 2023-07-02 10:33:51,412 [prior] Evaluating prior at array([0.30342998, 0.51216263])
 2023-07-02 10:33:51,412 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,413 [model] Got input parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5121626315493019, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,413 [classy] Got parameters {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,413 [classy] Computing new state
 2023-07-02 10:33:51,413 [classy] Setting parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,456 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3637826342507}
 2023-07-02 10:33:51,456 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,458 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00534468
 2023-07-02 10:33:51,458 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5121626315493019, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,458 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,478 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.88614
 2023-07-02 10:33:51,478 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,479 [mcmc] New sample, #259:
   Omega_m:0.3151988, b1:0.5060284
 2023-07-02 10:33:51,479 [model] Posterior to be computed for parameters {'Omega_m': 0.3034299824285535, 'b1': 0.5090286399546369}
 2023-07-02 10:33:51,479 [prior] Evaluating prior at array([0.30342998, 0.50902864])
 2023-07-02 10:33:51,479 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,479 [model] Got input parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5090286399546369, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,479 [classy] Got parameters {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,479 [classy] Re-using computed results
 2023-07-02 10:33:51,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3637826342507}
 2023-07-02 10:33:51,479 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,479 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5090286399546369, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,479 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70925
 2023-07-02 10:33:51,499 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,499 [mcmc] New sample, #260:
   Omega_m:0.30343, b1:0.5121626
 2023-07-02 10:33:51,499 [model] Posterior to be computed for parameters {'Omega_m': 0.294686603893143, 'b1': 0.5135859670841649}
 2023-07-02 10:33:51,499 [prior] Evaluating prior at array([0.2946866 , 0.51358597])
 2023-07-02 10:33:51,499 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,500 [model] Got input parameters: {'Omega_m': 0.294686603893143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135859670841649, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,500 [classy] Got parameters {'Omega_m': 0.294686603893143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,500 [classy] Computing new state
 2023-07-02 10:33:51,500 [classy] Setting parameters: {'Omega_m': 0.294686603893143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4574244897901}
 2023-07-02 10:33:51,545 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.020521
 2023-07-02 10:33:51,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135859670841649, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,547 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.09068
 2023-07-02 10:33:51,566 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,567 [model] Posterior to be computed for parameters {'Omega_m': 0.3034299824285535, 'b1': 0.49951998768077804}
 2023-07-02 10:33:51,567 [prior] Evaluating prior at array([0.30342998, 0.49951999])
 2023-07-02 10:33:51,567 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,567 [model] Got input parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49951998768077804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,567 [classy] Got parameters {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,567 [classy] Re-using computed results
 2023-07-02 10:33:51,567 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3637826342507}
 2023-07-02 10:33:51,567 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,567 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49951998768077804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,567 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.865897
 2023-07-02 10:33:51,587 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,587 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5083627023752767}
 2023-07-02 10:33:51,587 [prior] Evaluating prior at array([0.30470761, 0.5083627 ])
 2023-07-02 10:33:51,587 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,587 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083627023752767, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,587 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,588 [classy] Computing new state
 2023-07-02 10:33:51,588 [classy] Setting parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
 2023-07-02 10:33:51,632 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,634 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00398367
 2023-07-02 10:33:51,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083627023752767, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,634 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,654 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.97991
 2023-07-02 10:33:51,655 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,655 [mcmc] New sample, #261:
   Omega_m:0.30343, b1:0.5090286
 2023-07-02 10:33:51,655 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5061663527968823}
 2023-07-02 10:33:51,655 [prior] Evaluating prior at array([0.30470761, 0.50616635])
 2023-07-02 10:33:51,655 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,655 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061663527968823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,655 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,655 [classy] Re-using computed results
 2023-07-02 10:33:51,655 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
 2023-07-02 10:33:51,655 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,655 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061663527968823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,655 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,676 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84431
 2023-07-02 10:33:51,676 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,677 [mcmc] New sample, #262:
   Omega_m:0.3047076, b1:0.5083627
 2023-07-02 10:33:51,677 [model] Posterior to be computed for parameters {'Omega_m': 0.2991917314083716, 'b1': 0.5090414016800479}
 2023-07-02 10:33:51,677 [prior] Evaluating prior at array([0.29919173, 0.5090414 ])
 2023-07-02 10:33:51,677 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,677 [model] Got input parameters: {'Omega_m': 0.2991917314083716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5090414016800479, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,677 [classy] Got parameters {'Omega_m': 0.2991917314083716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,677 [classy] Computing new state
 2023-07-02 10:33:51,677 [classy] Setting parameters: {'Omega_m': 0.2991917314083716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89040133711921}
 2023-07-02 10:33:51,722 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,724 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114056
 2023-07-02 10:33:51,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5090414016800479, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,724 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,744 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.34586
 2023-07-02 10:33:51,744 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,744 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5206023742577697}
 2023-07-02 10:33:51,744 [prior] Evaluating prior at array([0.30470761, 0.52060237])
 2023-07-02 10:33:51,745 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,745 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5206023742577697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,745 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,745 [classy] Re-using computed results
 2023-07-02 10:33:51,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
 2023-07-02 10:33:51,745 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5206023742577697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,745 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,764 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27432
 2023-07-02 10:33:51,765 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,765 [mcmc] New sample, #263:
   Omega_m:0.3047076, b1:0.5061664
 2023-07-02 10:33:51,765 [model] Posterior to be computed for parameters {'Omega_m': 0.3294451439792615, 'b1': 0.5077083817673139}
 2023-07-02 10:33:51,765 [prior] Evaluating prior at array([0.32944514, 0.50770838])
 2023-07-02 10:33:51,765 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,765 [model] Got input parameters: {'Omega_m': 0.3294451439792615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5077083817673139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,765 [classy] Got parameters {'Omega_m': 0.3294451439792615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,765 [classy] Computing new state
 2023-07-02 10:33:51,765 [classy] Setting parameters: {'Omega_m': 0.3294451439792615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26703386139386}
 2023-07-02 10:33:51,810 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.017126
 2023-07-02 10:33:51,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5077083817673139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,812 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,831 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.32922
 2023-07-02 10:33:51,832 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,832 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5005226842047796}
 2023-07-02 10:33:51,832 [prior] Evaluating prior at array([0.30470761, 0.50052268])
 2023-07-02 10:33:51,832 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,832 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5005226842047796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,832 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,832 [classy] Re-using computed results
 2023-07-02 10:33:51,832 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
 2023-07-02 10:33:51,832 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,832 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5005226842047796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,832 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,853 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38272
 2023-07-02 10:33:51,853 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,853 [mcmc] New sample, #264:
   Omega_m:0.3047076, b1:0.5206024
 2023-07-02 10:33:51,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3239347229402879, 'b1': 0.49050089851565704}
 2023-07-02 10:33:51,854 [prior] Evaluating prior at array([0.32393472, 0.4905009 ])
 2023-07-02 10:33:51,854 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,854 [model] Got input parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49050089851565704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,854 [classy] Got parameters {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,854 [classy] Computing new state
 2023-07-02 10:33:51,854 [classy] Setting parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90429938749142}
 2023-07-02 10:33:51,899 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,901 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00801879
 2023-07-02 10:33:51,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49050089851565704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,901 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,921 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40176
 2023-07-02 10:33:51,921 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,921 [mcmc] New sample, #265:
   Omega_m:0.3047076, b1:0.5005227
 2023-07-02 10:33:51,921 [model] Posterior to be computed for parameters {'Omega_m': 0.3239347229402879, 'b1': 0.5150284660701672}
 2023-07-02 10:33:51,921 [prior] Evaluating prior at array([0.32393472, 0.51502847])
 2023-07-02 10:33:51,921 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,921 [model] Got input parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150284660701672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,921 [classy] Got parameters {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,921 [classy] Re-using computed results
 2023-07-02 10:33:51,921 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90429938749142}
 2023-07-02 10:33:51,921 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:51,921 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150284660701672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,921 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:51,942 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.16309
 2023-07-02 10:33:51,942 [model] Computed derived parameters: {}
 2023-07-02 10:33:51,942 [model] Posterior to be computed for parameters {'Omega_m': 0.33775322712757355, 'b1': 0.4832982543927743}
 2023-07-02 10:33:51,942 [prior] Evaluating prior at array([0.33775323, 0.48329825])
 2023-07-02 10:33:51,942 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:51,942 [model] Got input parameters: {'Omega_m': 0.33775322712757355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4832982543927743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,942 [classy] Got parameters {'Omega_m': 0.33775322712757355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:51,942 [classy] Computing new state
 2023-07-02 10:33:51,942 [classy] Setting parameters: {'Omega_m': 0.33775322712757355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:51,987 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.32425508865623}
 2023-07-02 10:33:51,987 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:51,989 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.037025
 2023-07-02 10:33:51,989 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4832982543927743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:51,989 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,008 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.31929
 2023-07-02 10:33:52,008 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,008 [model] Posterior to be computed for parameters {'Omega_m': 0.3239347229402879, 'b1': 0.4766887309920851}
 2023-07-02 10:33:52,008 [prior] Evaluating prior at array([0.32393472, 0.47668873])
 2023-07-02 10:33:52,009 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,009 [model] Got input parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4766887309920851, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,009 [classy] Got parameters {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,009 [classy] Re-using computed results
 2023-07-02 10:33:52,009 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90429938749142}
 2023-07-02 10:33:52,009 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,009 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4766887309920851, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,009 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,030 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36286
 2023-07-02 10:33:52,030 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,031 [mcmc] New sample, #266:
   Omega_m:0.3239347, b1:0.4905009
 2023-07-02 10:33:52,031 [model] Posterior to be computed for parameters {'Omega_m': 0.32678787981476004, 'b1': 0.4752015748342943}
 2023-07-02 10:33:52,031 [prior] Evaluating prior at array([0.32678788, 0.47520157])
 2023-07-02 10:33:52,031 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,031 [model] Got input parameters: {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4752015748342943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,031 [classy] Got parameters {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,031 [classy] Computing new state
 2023-07-02 10:33:52,031 [classy] Setting parameters: {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57313708182923}
 2023-07-02 10:33:52,077 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123156
 2023-07-02 10:33:52,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4752015748342943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,078 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,098 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.16836
 2023-07-02 10:33:52,098 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,098 [mcmc] New sample, #267:
   Omega_m:0.3239347, b1:0.4766887
 2023-07-02 10:33:52,099 [model] Posterior to be computed for parameters {'Omega_m': 0.32678787981476004, 'b1': 0.4384108036318327}
 2023-07-02 10:33:52,099 [prior] Evaluating prior at array([0.32678788, 0.4384108 ])
 2023-07-02 10:33:52,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,099 [model] Got input parameters: {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4384108036318327, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,099 [classy] Got parameters {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,099 [classy] Re-using computed results
 2023-07-02 10:33:52,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57313708182923}
 2023-07-02 10:33:52,099 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,099 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4384108036318327, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,099 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,119 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.09442
 2023-07-02 10:33:52,119 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,119 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.4775949210401899}
 2023-07-02 10:33:52,119 [prior] Evaluating prior at array([0.32219617, 0.47759492])
 2023-07-02 10:33:52,119 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,119 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4775949210401899, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,119 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,119 [classy] Computing new state
 2023-07-02 10:33:52,119 [classy] Setting parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,165 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,165 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,167 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00584926
 2023-07-02 10:33:52,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4775949210401899, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,167 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,187 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40633
 2023-07-02 10:33:52,187 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,188 [mcmc] New sample, #268:
   Omega_m:0.3267879, b1:0.4752016
 2023-07-02 10:33:52,188 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.420251498500124}
 2023-07-02 10:33:52,188 [prior] Evaluating prior at array([0.32219617, 0.4202515 ])
 2023-07-02 10:33:52,188 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,188 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.420251498500124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,188 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,188 [classy] Re-using computed results
 2023-07-02 10:33:52,188 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,188 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.420251498500124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,188 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,207 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.73415
 2023-07-02 10:33:52,207 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,208 [model] Posterior to be computed for parameters {'Omega_m': 0.3151207404439022, 'b1': 0.48128285915287367}
 2023-07-02 10:33:52,208 [prior] Evaluating prior at array([0.31512074, 0.48128286])
 2023-07-02 10:33:52,208 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,208 [model] Got input parameters: {'Omega_m': 0.3151207404439022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48128285915287367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,208 [classy] Got parameters {'Omega_m': 0.3151207404439022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,208 [classy] Computing new state
 2023-07-02 10:33:52,208 [classy] Setting parameters: {'Omega_m': 0.3151207404439022, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,254 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94402197317447}
 2023-07-02 10:33:52,254 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,255 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000626048
 2023-07-02 10:33:52,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48128285915287367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,255 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,275 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.98703
 2023-07-02 10:33:52,275 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,275 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.47325021735174155}
 2023-07-02 10:33:52,275 [prior] Evaluating prior at array([0.32219617, 0.47325022])
 2023-07-02 10:33:52,276 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,276 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47325021735174155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,276 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,276 [classy] Re-using computed results
 2023-07-02 10:33:52,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,276 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,276 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47325021735174155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,276 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,295 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1315
 2023-07-02 10:33:52,295 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,296 [model] Posterior to be computed for parameters {'Omega_m': 0.3388016961071284, 'b1': 0.4689395914720693}
 2023-07-02 10:33:52,296 [prior] Evaluating prior at array([0.3388017 , 0.46893959])
 2023-07-02 10:33:52,296 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,296 [model] Got input parameters: {'Omega_m': 0.3388016961071284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4689395914720693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,296 [classy] Got parameters {'Omega_m': 0.3388016961071284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,296 [classy] Computing new state
 2023-07-02 10:33:52,296 [classy] Setting parameters: {'Omega_m': 0.3388016961071284, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,341 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.20677032157133}
 2023-07-02 10:33:52,341 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,343 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0400451
 2023-07-02 10:33:52,343 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4689395914720693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,343 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,362 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.289883
 2023-07-02 10:33:52,362 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,362 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.46871344119895875}
 2023-07-02 10:33:52,362 [prior] Evaluating prior at array([0.32219617, 0.46871344])
 2023-07-02 10:33:52,362 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,362 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46871344119895875, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,362 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,362 [classy] Re-using computed results
 2023-07-02 10:33:52,363 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,363 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,363 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46871344119895875, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,363 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,383 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.73979
 2023-07-02 10:33:52,383 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,383 [mcmc] New sample, #269:
   Omega_m:0.3221962, b1:0.4775949
 2023-07-02 10:33:52,383 [model] Posterior to be computed for parameters {'Omega_m': 0.38406238523667957, 'b1': 0.436466800144568}
 2023-07-02 10:33:52,383 [prior] Evaluating prior at array([0.38406239, 0.4364668 ])
 2023-07-02 10:33:52,383 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,383 [model] Got input parameters: {'Omega_m': 0.38406238523667957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.436466800144568, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,383 [classy] Got parameters {'Omega_m': 0.38406238523667957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,383 [classy] Computing new state
 2023-07-02 10:33:52,383 [classy] Setting parameters: {'Omega_m': 0.38406238523667957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.4293326830357}
 2023-07-02 10:33:52,428 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.266085
 2023-07-02 10:33:52,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.436466800144568, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,430 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,451 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.7362
 2023-07-02 10:33:52,451 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,451 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.46689188054913966}
 2023-07-02 10:33:52,451 [prior] Evaluating prior at array([0.32219617, 0.46689188])
 2023-07-02 10:33:52,452 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,452 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46689188054913966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,452 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,452 [classy] Re-using computed results
 2023-07-02 10:33:52,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,452 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46689188054913966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,452 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.55274
 2023-07-02 10:33:52,471 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,471 [mcmc] New sample, #270:
   Omega_m:0.3221962, b1:0.4687134
 2023-07-02 10:33:52,471 [model] Posterior to be computed for parameters {'Omega_m': 0.3474133490134868, 'b1': 0.4537478834412025}
 2023-07-02 10:33:52,471 [prior] Evaluating prior at array([0.34741335, 0.45374788])
 2023-07-02 10:33:52,471 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,471 [model] Got input parameters: {'Omega_m': 0.3474133490134868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4537478834412025, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,471 [classy] Got parameters {'Omega_m': 0.3474133490134868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,471 [classy] Computing new state
 2023-07-02 10:33:52,471 [classy] Setting parameters: {'Omega_m': 0.3474133490134868, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,516 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2541400395014}
 2023-07-02 10:33:52,516 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,517 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0689812
 2023-07-02 10:33:52,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4537478834412025, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,517 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,538 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.56898
 2023-07-02 10:33:52,538 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,538 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.48387743862284194}
 2023-07-02 10:33:52,538 [prior] Evaluating prior at array([0.32219617, 0.48387744])
 2023-07-02 10:33:52,538 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,538 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48387743862284194, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,538 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,538 [classy] Re-using computed results
 2023-07-02 10:33:52,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,538 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,538 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48387743862284194, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,538 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,558 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62744
 2023-07-02 10:33:52,558 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,558 [mcmc] New sample, #271:
   Omega_m:0.3221962, b1:0.4668919
 2023-07-02 10:33:52,558 [model] Posterior to be computed for parameters {'Omega_m': 0.35777925040914815, 'b1': 0.4653304038377488}
 2023-07-02 10:33:52,558 [prior] Evaluating prior at array([0.35777925, 0.4653304 ])
 2023-07-02 10:33:52,559 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,559 [model] Got input parameters: {'Omega_m': 0.35777925040914815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4653304038377488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,559 [classy] Got parameters {'Omega_m': 0.35777925040914815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,559 [classy] Computing new state
 2023-07-02 10:33:52,559 [classy] Setting parameters: {'Omega_m': 0.35777925040914815, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.13574901602055}
 2023-07-02 10:33:52,603 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,605 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113125
 2023-07-02 10:33:52,605 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4653304038377488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,605 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,625 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.7601
 2023-07-02 10:33:52,625 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,625 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.493659325340613}
 2023-07-02 10:33:52,625 [prior] Evaluating prior at array([0.32219617, 0.49365933])
 2023-07-02 10:33:52,625 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,625 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.493659325340613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,625 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,625 [classy] Re-using computed results
 2023-07-02 10:33:52,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,625 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,625 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.493659325340613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,625 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,647 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5481
 2023-07-02 10:33:52,647 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,647 [mcmc] New sample, #272:
   Omega_m:0.3221962, b1:0.4838774
 2023-07-02 10:33:52,647 [model] Posterior to be computed for parameters {'Omega_m': 0.33969278009441306, 'b1': 0.48453953444172726}
 2023-07-02 10:33:52,647 [prior] Evaluating prior at array([0.33969278, 0.48453953])
 2023-07-02 10:33:52,648 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,648 [model] Got input parameters: {'Omega_m': 0.33969278009441306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48453953444172726, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,648 [classy] Got parameters {'Omega_m': 0.33969278009441306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,648 [classy] Computing new state
 2023-07-02 10:33:52,648 [classy] Setting parameters: {'Omega_m': 0.33969278009441306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1071784963586}
 2023-07-02 10:33:52,692 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,694 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0426993
 2023-07-02 10:33:52,694 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48453953444172726, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,694 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,713 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.48427
 2023-07-02 10:33:52,713 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,713 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.5047649480853185}
 2023-07-02 10:33:52,714 [prior] Evaluating prior at array([0.32219617, 0.50476495])
 2023-07-02 10:33:52,714 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,714 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5047649480853185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,714 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,714 [classy] Re-using computed results
 2023-07-02 10:33:52,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,714 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5047649480853185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,714 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,733 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81541
 2023-07-02 10:33:52,734 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,734 [model] Posterior to be computed for parameters {'Omega_m': 0.3506521754071579, 'b1': 0.4788271488484791}
 2023-07-02 10:33:52,734 [prior] Evaluating prior at array([0.35065218, 0.47882715])
 2023-07-02 10:33:52,734 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,734 [model] Got input parameters: {'Omega_m': 0.3506521754071579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4788271488484791, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,734 [classy] Got parameters {'Omega_m': 0.3506521754071579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,734 [classy] Computing new state
 2023-07-02 10:33:52,734 [classy] Setting parameters: {'Omega_m': 0.3506521754071579, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9014544066976}
 2023-07-02 10:33:52,778 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0817106
 2023-07-02 10:33:52,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4788271488484791, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,780 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,800 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.49312
 2023-07-02 10:33:52,800 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,800 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.5099723525119436}
 2023-07-02 10:33:52,800 [prior] Evaluating prior at array([0.32219617, 0.50997235])
 2023-07-02 10:33:52,800 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,800 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5099723525119436, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,800 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,801 [classy] Re-using computed results
 2023-07-02 10:33:52,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
 2023-07-02 10:33:52,801 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,801 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5099723525119436, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,801 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,820 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23036
 2023-07-02 10:33:52,820 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,820 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.492942895323409}
 2023-07-02 10:33:52,820 [prior] Evaluating prior at array([0.32357066, 0.4929429 ])
 2023-07-02 10:33:52,820 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,820 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.492942895323409, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,821 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,821 [classy] Computing new state
 2023-07-02 10:33:52,821 [classy] Setting parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
 2023-07-02 10:33:52,866 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,868 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00753615
 2023-07-02 10:33:52,868 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.492942895323409, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,868 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,888 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36395
 2023-07-02 10:33:52,888 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,888 [mcmc] New sample, #273:
   Omega_m:0.3221962, b1:0.4936593
 2023-07-02 10:33:52,888 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.5077432334076324}
 2023-07-02 10:33:52,888 [prior] Evaluating prior at array([0.32357066, 0.50774323])
 2023-07-02 10:33:52,888 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,888 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5077432334076324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,888 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,888 [classy] Re-using computed results
 2023-07-02 10:33:52,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
 2023-07-02 10:33:52,888 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,888 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5077432334076324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,888 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,908 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08162
 2023-07-02 10:33:52,908 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,908 [model] Posterior to be computed for parameters {'Omega_m': 0.3304213804879385, 'b1': 0.48937208295648715}
 2023-07-02 10:33:52,908 [prior] Evaluating prior at array([0.33042138, 0.48937208])
 2023-07-02 10:33:52,909 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,909 [model] Got input parameters: {'Omega_m': 0.3304213804879385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48937208295648715, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,909 [classy] Got parameters {'Omega_m': 0.3304213804879385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,909 [classy] Computing new state
 2023-07-02 10:33:52,909 [classy] Setting parameters: {'Omega_m': 0.3304213804879385, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:52,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15514703239165}
 2023-07-02 10:33:52,953 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:52,954 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0190856
 2023-07-02 10:33:52,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48937208295648715, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,955 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,974 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.901907
 2023-07-02 10:33:52,974 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,974 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.49237970773026063}
 2023-07-02 10:33:52,974 [prior] Evaluating prior at array([0.32357066, 0.49237971])
 2023-07-02 10:33:52,974 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,975 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49237970773026063, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,975 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,975 [classy] Re-using computed results
 2023-07-02 10:33:52,975 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
 2023-07-02 10:33:52,975 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:52,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49237970773026063, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,975 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:52,995 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38831
 2023-07-02 10:33:52,995 [model] Computed derived parameters: {}
 2023-07-02 10:33:52,995 [mcmc] New sample, #274:
   Omega_m:0.3235707, b1:0.4929429
 2023-07-02 10:33:52,995 [model] Posterior to be computed for parameters {'Omega_m': 0.3034602817719684, 'b1': 0.5028618779858514}
 2023-07-02 10:33:52,995 [prior] Evaluating prior at array([0.30346028, 0.50286188])
 2023-07-02 10:33:52,995 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:52,995 [model] Got input parameters: {'Omega_m': 0.3034602817719684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5028618779858514, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:52,995 [classy] Got parameters {'Omega_m': 0.3034602817719684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:52,995 [classy] Computing new state
 2023-07-02 10:33:52,995 [classy] Setting parameters: {'Omega_m': 0.3034602817719684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3600428845973}
 2023-07-02 10:33:53,039 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,041 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00530996
 2023-07-02 10:33:53,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5028618779858514, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,042 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,062 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22392
 2023-07-02 10:33:53,063 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,063 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.4833014673971425}
 2023-07-02 10:33:53,063 [prior] Evaluating prior at array([0.32357066, 0.48330147])
 2023-07-02 10:33:53,063 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,063 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4833014673971425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,063 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,063 [classy] Re-using computed results
 2023-07-02 10:33:53,063 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
 2023-07-02 10:33:53,063 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4833014673971425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,063 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53966
 2023-07-02 10:33:53,083 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,083 [mcmc] New sample, #275:
   Omega_m:0.3235707, b1:0.4923797
 2023-07-02 10:33:53,083 [model] Posterior to be computed for parameters {'Omega_m': 0.32356006392974085, 'b1': 0.48330699156515555}
 2023-07-02 10:33:53,083 [prior] Evaluating prior at array([0.32356006, 0.48330699])
 2023-07-02 10:33:53,083 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,083 [model] Got input parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48330699156515555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,083 [classy] Got parameters {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,083 [classy] Computing new state
 2023-07-02 10:33:53,083 [classy] Setting parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94797900491105}
 2023-07-02 10:33:53,128 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,130 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00752231
 2023-07-02 10:33:53,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48330699156515555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,131 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,152 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5405
 2023-07-02 10:33:53,152 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,152 [mcmc] New sample, #276:
   Omega_m:0.3235707, b1:0.4833015
 2023-07-02 10:33:53,152 [model] Posterior to be computed for parameters {'Omega_m': 0.32356006392974085, 'b1': 0.4906896996698696}
 2023-07-02 10:33:53,152 [prior] Evaluating prior at array([0.32356006, 0.4906897 ])
 2023-07-02 10:33:53,152 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,152 [model] Got input parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906896996698696, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,152 [classy] Got parameters {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,152 [classy] Re-using computed results
 2023-07-02 10:33:53,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94797900491105}
 2023-07-02 10:33:53,152 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906896996698696, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,153 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,172 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45239
 2023-07-02 10:33:53,172 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,172 [mcmc] New sample, #277:
   Omega_m:0.3235601, b1:0.483307
 2023-07-02 10:33:53,172 [model] Posterior to be computed for parameters {'Omega_m': 0.3315251115912112, 'b1': 0.4865380633603365}
 2023-07-02 10:33:53,172 [prior] Evaluating prior at array([0.33152511, 0.48653806])
 2023-07-02 10:33:53,173 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,173 [model] Got input parameters: {'Omega_m': 0.3315251115912112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4865380633603365, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,173 [classy] Got parameters {'Omega_m': 0.3315251115912112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,173 [classy] Computing new state
 2023-07-02 10:33:53,173 [classy] Setting parameters: {'Omega_m': 0.3315251115912112, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,217 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0290090570606}
 2023-07-02 10:33:53,217 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,219 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0214242
 2023-07-02 10:33:53,219 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4865380633603365, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,219 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,238 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.801885
 2023-07-02 10:33:53,238 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,238 [model] Posterior to be computed for parameters {'Omega_m': 0.32356006392974085, 'b1': 0.4956688030054077}
 2023-07-02 10:33:53,238 [prior] Evaluating prior at array([0.32356006, 0.4956688 ])
 2023-07-02 10:33:53,239 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,239 [model] Got input parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4956688030054077, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,239 [classy] Got parameters {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,239 [classy] Re-using computed results
 2023-07-02 10:33:53,239 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94797900491105}
 2023-07-02 10:33:53,239 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,239 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4956688030054077, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,239 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,260 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.22314
 2023-07-02 10:33:53,260 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,260 [mcmc] New sample, #278:
   Omega_m:0.3235601, b1:0.4906897
 2023-07-02 10:33:53,260 [model] Posterior to be computed for parameters {'Omega_m': 0.31822054808823197, 'b1': 0.49845192857917775}
 2023-07-02 10:33:53,260 [prior] Evaluating prior at array([0.31822055, 0.49845193])
 2023-07-02 10:33:53,261 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,261 [model] Got input parameters: {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49845192857917775, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,261 [classy] Got parameters {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,261 [classy] Computing new state
 2023-07-02 10:33:53,261 [classy] Setting parameters: {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5754415837184}
 2023-07-02 10:33:53,305 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00219179
 2023-07-02 10:33:53,307 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49845192857917775, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,307 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,326 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83346
 2023-07-02 10:33:53,326 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,326 [mcmc] New sample, #279:
   Omega_m:0.3235601, b1:0.4956688
 2023-07-02 10:33:53,326 [model] Posterior to be computed for parameters {'Omega_m': 0.31822054808823197, 'b1': 0.48610974002033136}
 2023-07-02 10:33:53,326 [prior] Evaluating prior at array([0.31822055, 0.48610974])
 2023-07-02 10:33:53,327 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,327 [model] Got input parameters: {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48610974002033136, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,327 [classy] Got parameters {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,327 [classy] Re-using computed results
 2023-07-02 10:33:53,327 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5754415837184}
 2023-07-02 10:33:53,327 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,327 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48610974002033136, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,327 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,346 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68695
 2023-07-02 10:33:53,347 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,347 [mcmc] New sample, #280:
   Omega_m:0.3182205, b1:0.4984519
 2023-07-02 10:33:53,347 [model] Posterior to be computed for parameters {'Omega_m': 0.32109346218620616, 'b1': 0.4846122857689255}
 2023-07-02 10:33:53,347 [prior] Evaluating prior at array([0.32109346, 0.48461229])
 2023-07-02 10:33:53,347 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,347 [model] Got input parameters: {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4846122857689255, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,347 [classy] Got parameters {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,347 [classy] Computing new state
 2023-07-02 10:33:53,347 [classy] Setting parameters: {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,390 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23668157389145}
 2023-07-02 10:33:53,391 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,392 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00465172
 2023-07-02 10:33:53,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4846122857689255, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,393 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,412 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67669
 2023-07-02 10:33:53,412 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,412 [mcmc] New sample, #281:
   Omega_m:0.3182205, b1:0.4861097
 2023-07-02 10:33:53,412 [model] Posterior to be computed for parameters {'Omega_m': 0.32109346218620616, 'b1': 0.4710120966171956}
 2023-07-02 10:33:53,412 [prior] Evaluating prior at array([0.32109346, 0.4710121 ])
 2023-07-02 10:33:53,413 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,413 [model] Got input parameters: {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4710120966171956, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,413 [classy] Got parameters {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,413 [classy] Re-using computed results
 2023-07-02 10:33:53,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23668157389145}
 2023-07-02 10:33:53,413 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4710120966171956, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,413 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84651
 2023-07-02 10:33:53,432 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,432 [mcmc] New sample, #282:
   Omega_m:0.3210935, b1:0.4846123
 2023-07-02 10:33:53,432 [model] Posterior to be computed for parameters {'Omega_m': 0.3104378725197752, 'b1': 0.4765661290397052}
 2023-07-02 10:33:53,432 [prior] Evaluating prior at array([0.31043787, 0.47656613])
 2023-07-02 10:33:53,432 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,432 [model] Got input parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4765661290397052, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,432 [classy] Got parameters {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,432 [classy] Computing new state
 2023-07-02 10:33:53,432 [classy] Setting parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50705443581444}
 2023-07-02 10:33:53,478 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,480 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000460432
 2023-07-02 10:33:53,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4765661290397052, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.124793
 2023-07-02 10:33:53,500 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,500 [mcmc] New sample, #283:
   Omega_m:0.3210935, b1:0.4710121
 2023-07-02 10:33:53,500 [model] Posterior to be computed for parameters {'Omega_m': 0.3104378725197752, 'b1': 0.5145979134099927}
 2023-07-02 10:33:53,500 [prior] Evaluating prior at array([0.31043787, 0.51459791])
 2023-07-02 10:33:53,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,500 [model] Got input parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5145979134099927, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,500 [classy] Got parameters {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,500 [classy] Re-using computed results
 2023-07-02 10:33:53,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50705443581444}
 2023-07-02 10:33:53,500 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5145979134099927, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,500 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,519 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70101
 2023-07-02 10:33:53,519 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,520 [mcmc] New sample, #284:
   Omega_m:0.3104379, b1:0.4765661
 2023-07-02 10:33:53,520 [model] Posterior to be computed for parameters {'Omega_m': 0.2798918689187615, 'b1': 0.5305194625395163}
 2023-07-02 10:33:53,520 [prior] Evaluating prior at array([0.27989187, 0.53051946])
 2023-07-02 10:33:53,520 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,520 [model] Got input parameters: {'Omega_m': 0.2798918689187615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305194625395163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,520 [classy] Got parameters {'Omega_m': 0.2798918689187615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,520 [classy] Computing new state
 2023-07-02 10:33:53,520 [classy] Setting parameters: {'Omega_m': 0.2798918689187615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3739294115847}
 2023-07-02 10:33:53,564 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,566 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.071031
 2023-07-02 10:33:53,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305194625395163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,566 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,586 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.00385
 2023-07-02 10:33:53,586 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,586 [model] Posterior to be computed for parameters {'Omega_m': 0.3104378725197752, 'b1': 0.5201523104871444}
 2023-07-02 10:33:53,586 [prior] Evaluating prior at array([0.31043787, 0.52015231])
 2023-07-02 10:33:53,586 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,586 [model] Got input parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5201523104871444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,586 [classy] Got parameters {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,586 [classy] Re-using computed results
 2023-07-02 10:33:53,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50705443581444}
 2023-07-02 10:33:53,586 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,586 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5201523104871444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,586 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,606 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.43677
 2023-07-02 10:33:53,607 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,607 [mcmc] New sample, #285:
   Omega_m:0.3104379, b1:0.5145979
 2023-07-02 10:33:53,607 [model] Posterior to be computed for parameters {'Omega_m': 0.3138812107630452, 'b1': 0.5183575330188418}
 2023-07-02 10:33:53,607 [prior] Evaluating prior at array([0.31388121, 0.51835753])
 2023-07-02 10:33:53,607 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,607 [model] Got input parameters: {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183575330188418, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,607 [classy] Got parameters {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,607 [classy] Computing new state
 2023-07-02 10:33:53,607 [classy] Setting parameters: {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,652 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0923279065068}
 2023-07-02 10:33:53,652 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,654 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000321711
 2023-07-02 10:33:53,654 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183575330188418, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,654 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,673 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21838
 2023-07-02 10:33:53,674 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,674 [mcmc] New sample, #286:
   Omega_m:0.3104379, b1:0.5201523
 2023-07-02 10:33:53,674 [model] Posterior to be computed for parameters {'Omega_m': 0.3138812107630452, 'b1': 0.5003344783234781}
 2023-07-02 10:33:53,674 [prior] Evaluating prior at array([0.31388121, 0.50033448])
 2023-07-02 10:33:53,674 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,674 [model] Got input parameters: {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5003344783234781, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,674 [classy] Got parameters {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,674 [classy] Re-using computed results
 2023-07-02 10:33:53,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0923279065068}
 2023-07-02 10:33:53,674 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,674 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5003344783234781, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,674 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,693 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90579
 2023-07-02 10:33:53,693 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,693 [mcmc] New sample, #287:
   Omega_m:0.3138812, b1:0.5183575
 2023-07-02 10:33:53,693 [model] Posterior to be computed for parameters {'Omega_m': 0.31571756183507443, 'b1': 0.49937731370730565}
 2023-07-02 10:33:53,694 [prior] Evaluating prior at array([0.31571756, 0.49937731])
 2023-07-02 10:33:53,694 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,694 [model] Got input parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49937731370730565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,694 [classy] Got parameters {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,694 [classy] Computing new state
 2023-07-02 10:33:53,694 [classy] Setting parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,738 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87280901139144}
 2023-07-02 10:33:53,738 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,740 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000838507
 2023-07-02 10:33:53,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49937731370730565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,740 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,760 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92489
 2023-07-02 10:33:53,760 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,760 [mcmc] New sample, #288:
   Omega_m:0.3138812, b1:0.5003345
 2023-07-02 10:33:53,760 [model] Posterior to be computed for parameters {'Omega_m': 0.31571756183507443, 'b1': 0.4904828326846904}
 2023-07-02 10:33:53,760 [prior] Evaluating prior at array([0.31571756, 0.49048283])
 2023-07-02 10:33:53,760 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,761 [model] Got input parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904828326846904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,761 [classy] Got parameters {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,761 [classy] Re-using computed results
 2023-07-02 10:33:53,761 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87280901139144}
 2023-07-02 10:33:53,761 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,761 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904828326846904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,761 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,780 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72908
 2023-07-02 10:33:53,780 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,780 [model] Posterior to be computed for parameters {'Omega_m': 0.32685227335624856, 'b1': 0.4935735477272099}
 2023-07-02 10:33:53,780 [prior] Evaluating prior at array([0.32685227, 0.49357355])
 2023-07-02 10:33:53,780 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,780 [model] Got input parameters: {'Omega_m': 0.32685227335624856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935735477272099, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,780 [classy] Got parameters {'Omega_m': 0.32685227335624856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,780 [classy] Computing new state
 2023-07-02 10:33:53,780 [classy] Setting parameters: {'Omega_m': 0.32685227335624856, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.56569204959635}
 2023-07-02 10:33:53,824 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,826 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.012423
 2023-07-02 10:33:53,826 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935735477272099, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,826 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,845 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59945
 2023-07-02 10:33:53,846 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,846 [model] Posterior to be computed for parameters {'Omega_m': 0.31571756183507443, 'b1': 0.4926862475308918}
 2023-07-02 10:33:53,846 [prior] Evaluating prior at array([0.31571756, 0.49268625])
 2023-07-02 10:33:53,846 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,846 [model] Got input parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4926862475308918, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,846 [classy] Got parameters {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,846 [classy] Re-using computed results
 2023-07-02 10:33:53,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87280901139144}
 2023-07-02 10:33:53,846 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4926862475308918, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,846 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,866 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81678
 2023-07-02 10:33:53,866 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,866 [mcmc] New sample, #289:
   Omega_m:0.3157176, b1:0.4993773
 2023-07-02 10:33:53,866 [model] Posterior to be computed for parameters {'Omega_m': 0.3087804174416922, 'b1': 0.4963021079465623}
 2023-07-02 10:33:53,866 [prior] Evaluating prior at array([0.30878042, 0.49630211])
 2023-07-02 10:33:53,866 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,867 [model] Got input parameters: {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4963021079465623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,867 [classy] Got parameters {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,867 [classy] Computing new state
 2023-07-02 10:33:53,867 [classy] Setting parameters: {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,911 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.70813435248712}
 2023-07-02 10:33:53,911 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,913 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00105137
 2023-07-02 10:33:53,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4963021079465623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,913 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,932 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06832
 2023-07-02 10:33:53,932 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,932 [mcmc] New sample, #290:
   Omega_m:0.3157176, b1:0.4926862
 2023-07-02 10:33:53,932 [model] Posterior to be computed for parameters {'Omega_m': 0.3087804174416922, 'b1': 0.5026915201143093}
 2023-07-02 10:33:53,932 [prior] Evaluating prior at array([0.30878042, 0.50269152])
 2023-07-02 10:33:53,933 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,933 [model] Got input parameters: {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5026915201143093, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,933 [classy] Got parameters {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,933 [classy] Re-using computed results
 2023-07-02 10:33:53,933 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.70813435248712}
 2023-07-02 10:33:53,933 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:53,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5026915201143093, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,933 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:53,953 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47652
 2023-07-02 10:33:53,953 [model] Computed derived parameters: {}
 2023-07-02 10:33:53,953 [mcmc] New sample, #291:
   Omega_m:0.3087804, b1:0.4963021
 2023-07-02 10:33:53,953 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.49927247431574345}
 2023-07-02 10:33:53,953 [prior] Evaluating prior at array([0.31533997, 0.49927247])
 2023-07-02 10:33:53,953 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:53,953 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49927247431574345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,953 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:53,953 [classy] Computing new state
 2023-07-02 10:33:53,953 [classy] Setting parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:53,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
 2023-07-02 10:33:53,997 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:53,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000699118
 2023-07-02 10:33:53,998 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49927247431574345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:53,998 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,018 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92605
 2023-07-02 10:33:54,018 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,018 [mcmc] New sample, #292:
   Omega_m:0.3087804, b1:0.5026915
 2023-07-02 10:33:54,018 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5070957576836143}
 2023-07-02 10:33:54,018 [prior] Evaluating prior at array([0.31533997, 0.50709576])
 2023-07-02 10:33:54,019 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,019 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070957576836143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,019 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,019 [classy] Re-using computed results
 2023-07-02 10:33:54,019 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
 2023-07-02 10:33:54,019 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,019 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070957576836143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,019 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,038 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77924
 2023-07-02 10:33:54,038 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,038 [mcmc] New sample, #293:
   Omega_m:0.31534, b1:0.4992725
 2023-07-02 10:33:54,038 [model] Posterior to be computed for parameters {'Omega_m': 0.29701083859785266, 'b1': 0.5166494825139659}
 2023-07-02 10:33:54,038 [prior] Evaluating prior at array([0.29701084, 0.51664948])
 2023-07-02 10:33:54,039 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,039 [model] Got input parameters: {'Omega_m': 0.29701083859785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166494825139659, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,039 [classy] Got parameters {'Omega_m': 0.29701083859785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,039 [classy] Computing new state
 2023-07-02 10:33:54,039 [classy] Setting parameters: {'Omega_m': 0.29701083859785266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1639564575107}
 2023-07-02 10:33:54,083 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,085 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0154688
 2023-07-02 10:33:54,085 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166494825139659, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,085 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,105 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.223758
 2023-07-02 10:33:54,105 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,105 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5295800300586563}
 2023-07-02 10:33:54,105 [prior] Evaluating prior at array([0.31533997, 0.52958003])
 2023-07-02 10:33:54,105 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,105 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5295800300586563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,105 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,105 [classy] Re-using computed results
 2023-07-02 10:33:54,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
 2023-07-02 10:33:54,105 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,105 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5295800300586563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,105 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,126 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.450993
 2023-07-02 10:33:54,126 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,126 [mcmc] New sample, #294:
   Omega_m:0.31534, b1:0.5070958
 2023-07-02 10:33:54,126 [model] Posterior to be computed for parameters {'Omega_m': 0.2785021323362605, 'b1': 0.5487810815873548}
 2023-07-02 10:33:54,126 [prior] Evaluating prior at array([0.27850213, 0.54878108])
 2023-07-02 10:33:54,127 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,127 [model] Got input parameters: {'Omega_m': 0.2785021323362605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5487810815873548, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,127 [classy] Got parameters {'Omega_m': 0.2785021323362605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,127 [classy] Computing new state
 2023-07-02 10:33:54,127 [classy] Setting parameters: {'Omega_m': 0.2785021323362605, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.5584082539434}
 2023-07-02 10:33:54,171 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0774851
 2023-07-02 10:33:54,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5487810815873548, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,173 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,192 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.69579
 2023-07-02 10:33:54,193 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,193 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5119890209164148}
 2023-07-02 10:33:54,193 [prior] Evaluating prior at array([0.31533997, 0.51198902])
 2023-07-02 10:33:54,193 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,193 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119890209164148, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,193 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,193 [classy] Re-using computed results
 2023-07-02 10:33:54,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
 2023-07-02 10:33:54,193 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,193 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119890209164148, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,193 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,213 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51636
 2023-07-02 10:33:54,213 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,213 [mcmc] New sample, #295:
   Omega_m:0.31534, b1:0.52958
 2023-07-02 10:33:54,213 [model] Posterior to be computed for parameters {'Omega_m': 0.33270362042687757, 'b1': 0.5029385320210362}
 2023-07-02 10:33:54,213 [prior] Evaluating prior at array([0.33270362, 0.50293853])
 2023-07-02 10:33:54,213 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,213 [model] Got input parameters: {'Omega_m': 0.33270362042687757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029385320210362, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,213 [classy] Got parameters {'Omega_m': 0.33270362042687757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,213 [classy] Computing new state
 2023-07-02 10:33:54,213 [classy] Setting parameters: {'Omega_m': 0.33270362042687757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.89474106101568}
 2023-07-02 10:33:54,257 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,259 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0240647
 2023-07-02 10:33:54,259 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029385320210362, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,259 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,279 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.08507
 2023-07-02 10:33:54,279 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,279 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5178938228650387}
 2023-07-02 10:33:54,279 [prior] Evaluating prior at array([0.31533997, 0.51789382])
 2023-07-02 10:33:54,279 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,279 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5178938228650387, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,279 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,279 [classy] Re-using computed results
 2023-07-02 10:33:54,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
 2023-07-02 10:33:54,279 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,279 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5178938228650387, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,279 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,298 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0206
 2023-07-02 10:33:54,298 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,298 [mcmc] New sample, #296:
   Omega_m:0.31534, b1:0.511989
 2023-07-02 10:33:54,299 [model] Posterior to be computed for parameters {'Omega_m': 0.3070165101603717, 'b1': 0.5222322732707112}
 2023-07-02 10:33:54,299 [prior] Evaluating prior at array([0.30701651, 0.52223227])
 2023-07-02 10:33:54,299 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,299 [model] Got input parameters: {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5222322732707112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,299 [classy] Got parameters {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,299 [classy] Computing new state
 2023-07-02 10:33:54,299 [classy] Setting parameters: {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92317361251105}
 2023-07-02 10:33:54,343 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00206081
 2023-07-02 10:33:54,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5222322732707112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,345 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39079
 2023-07-02 10:33:54,365 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,365 [mcmc] New sample, #297:
   Omega_m:0.31534, b1:0.5178938
 2023-07-02 10:33:54,365 [model] Posterior to be computed for parameters {'Omega_m': 0.3070165101603717, 'b1': 0.5204710226153965}
 2023-07-02 10:33:54,365 [prior] Evaluating prior at array([0.30701651, 0.52047102])
 2023-07-02 10:33:54,365 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,365 [model] Got input parameters: {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204710226153965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,365 [classy] Got parameters {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,365 [classy] Re-using computed results
 2023-07-02 10:33:54,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92317361251105}
 2023-07-02 10:33:54,365 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204710226153965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,365 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,384 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45269
 2023-07-02 10:33:54,385 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,385 [mcmc] New sample, #298:
   Omega_m:0.3070165, b1:0.5222323
 2023-07-02 10:33:54,385 [model] Posterior to be computed for parameters {'Omega_m': 0.30954623856111213, 'b1': 0.5191524476704434}
 2023-07-02 10:33:54,385 [prior] Evaluating prior at array([0.30954624, 0.51915245])
 2023-07-02 10:33:54,385 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,385 [model] Got input parameters: {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191524476704434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,385 [classy] Got parameters {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,385 [classy] Computing new state
 2023-07-02 10:33:54,385 [classy] Setting parameters: {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61510711278612}
 2023-07-02 10:33:54,429 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000735535
 2023-07-02 10:33:54,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191524476704434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,430 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,450 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52887
 2023-07-02 10:33:54,450 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,450 [mcmc] New sample, #299:
   Omega_m:0.3070165, b1:0.520471
 2023-07-02 10:33:54,450 [model] Posterior to be computed for parameters {'Omega_m': 0.30954623856111213, 'b1': 0.523789316435705}
 2023-07-02 10:33:54,450 [prior] Evaluating prior at array([0.30954624, 0.52378932])
 2023-07-02 10:33:54,450 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,450 [model] Got input parameters: {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523789316435705, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,450 [classy] Got parameters {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,450 [classy] Re-using computed results
 2023-07-02 10:33:54,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61510711278612}
 2023-07-02 10:33:54,450 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,450 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523789316435705, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,451 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.24507
 2023-07-02 10:33:54,471 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,471 [mcmc] New sample, #300:
   Omega_m:0.3095462, b1:0.5191524
 2023-07-02 10:33:54,471 [model] Posterior to be computed for parameters {'Omega_m': 0.3039649582293687, 'b1': 0.5266984573553555}
 2023-07-02 10:33:54,471 [prior] Evaluating prior at array([0.30396496, 0.52669846])
 2023-07-02 10:33:54,471 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,471 [model] Got input parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5266984573553555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,471 [classy] Got parameters {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,471 [classy] Computing new state
 2023-07-02 10:33:54,471 [classy] Setting parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2977695222496}
 2023-07-02 10:33:54,515 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,517 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00474881
 2023-07-02 10:33:54,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5266984573553555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,517 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07693
 2023-07-02 10:33:54,536 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,536 [mcmc] New sample, #301:
   Omega_m:0.3095462, b1:0.5237893
 2023-07-02 10:33:54,536 [model] Posterior to be computed for parameters {'Omega_m': 0.3039649582293687, 'b1': 0.5182656511445677}
 2023-07-02 10:33:54,536 [prior] Evaluating prior at array([0.30396496, 0.51826565])
 2023-07-02 10:33:54,536 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,536 [model] Got input parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5182656511445677, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,536 [classy] Got parameters {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,536 [classy] Re-using computed results
 2023-07-02 10:33:54,536 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2977695222496}
 2023-07-02 10:33:54,536 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,536 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5182656511445677, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,536 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,556 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17182
 2023-07-02 10:33:54,556 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,556 [mcmc] New sample, #302:
   Omega_m:0.303965, b1:0.5266985
 2023-07-02 10:33:54,556 [model] Posterior to be computed for parameters {'Omega_m': 0.2973586174868648, 'b1': 0.5217090861703744}
 2023-07-02 10:33:54,556 [prior] Evaluating prior at array([0.29735862, 0.52170909])
 2023-07-02 10:33:54,556 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,556 [model] Got input parameters: {'Omega_m': 0.2973586174868648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5217090861703744, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,556 [classy] Got parameters {'Omega_m': 0.2973586174868648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,556 [classy] Computing new state
 2023-07-02 10:33:54,556 [classy] Setting parameters: {'Omega_m': 0.2973586174868648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.12021896301644}
 2023-07-02 10:33:54,600 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,602 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0147773
 2023-07-02 10:33:54,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5217090861703744, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,602 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.701275
 2023-07-02 10:33:54,622 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,622 [model] Posterior to be computed for parameters {'Omega_m': 0.3039649582293687, 'b1': 0.5241807035549605}
 2023-07-02 10:33:54,622 [prior] Evaluating prior at array([0.30396496, 0.5241807 ])
 2023-07-02 10:33:54,622 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,622 [model] Got input parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241807035549605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,622 [classy] Got parameters {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,622 [classy] Re-using computed results
 2023-07-02 10:33:54,622 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2977695222496}
 2023-07-02 10:33:54,622 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,622 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241807035549605, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,622 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,641 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14529
 2023-07-02 10:33:54,641 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,642 [mcmc] New sample, #303:
   Omega_m:0.303965, b1:0.5182657
 2023-07-02 10:33:54,642 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5258892738121356}
 2023-07-02 10:33:54,642 [prior] Evaluating prior at array([0.30068701, 0.52588927])
 2023-07-02 10:33:54,642 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,642 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5258892738121356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,642 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,642 [classy] Computing new state
 2023-07-02 10:33:54,642 [classy] Setting parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,687 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
 2023-07-02 10:33:54,687 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,688 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00899303
 2023-07-02 10:33:54,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5258892738121356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,708 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.6689
 2023-07-02 10:33:54,708 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,708 [mcmc] New sample, #304:
   Omega_m:0.303965, b1:0.5241807
 2023-07-02 10:33:54,708 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5210397981399907}
 2023-07-02 10:33:54,708 [prior] Evaluating prior at array([0.30068701, 0.5210398 ])
 2023-07-02 10:33:54,708 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,708 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5210397981399907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,708 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,708 [classy] Re-using computed results
 2023-07-02 10:33:54,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
 2023-07-02 10:33:54,708 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,708 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5210397981399907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,708 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,728 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59522
 2023-07-02 10:33:54,728 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,728 [mcmc] New sample, #305:
   Omega_m:0.300687, b1:0.5258893
 2023-07-02 10:33:54,728 [model] Posterior to be computed for parameters {'Omega_m': 0.281742076150132, 'b1': 0.5309145012119798}
 2023-07-02 10:33:54,728 [prior] Evaluating prior at array([0.28174208, 0.5309145 ])
 2023-07-02 10:33:54,728 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,728 [model] Got input parameters: {'Omega_m': 0.281742076150132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5309145012119798, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,728 [classy] Got parameters {'Omega_m': 0.281742076150132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,729 [classy] Computing new state
 2023-07-02 10:33:54,729 [classy] Setting parameters: {'Omega_m': 0.281742076150132, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.12953556129196}
 2023-07-02 10:33:54,772 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0629091
 2023-07-02 10:33:54,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5309145012119798, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,774 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.54089
 2023-07-02 10:33:54,794 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,794 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5295228180476761}
 2023-07-02 10:33:54,794 [prior] Evaluating prior at array([0.30068701, 0.52952282])
 2023-07-02 10:33:54,794 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,794 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5295228180476761, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,794 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,794 [classy] Re-using computed results
 2023-07-02 10:33:54,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
 2023-07-02 10:33:54,794 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5295228180476761, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,794 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,814 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64241
 2023-07-02 10:33:54,814 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,814 [mcmc] New sample, #306:
   Omega_m:0.300687, b1:0.5210398
 2023-07-02 10:33:54,814 [model] Posterior to be computed for parameters {'Omega_m': 0.28175254188471854, 'b1': 0.5393920660457521}
 2023-07-02 10:33:54,814 [prior] Evaluating prior at array([0.28175254, 0.53939207])
 2023-07-02 10:33:54,814 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,814 [model] Got input parameters: {'Omega_m': 0.28175254188471854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5393920660457521, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,814 [classy] Got parameters {'Omega_m': 0.28175254188471854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,814 [classy] Computing new state
 2023-07-02 10:33:54,814 [classy] Setting parameters: {'Omega_m': 0.28175254188471854, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.1281553621312}
 2023-07-02 10:33:54,858 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0628645
 2023-07-02 10:33:54,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5393920660457521, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,860 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,880 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.45313
 2023-07-02 10:33:54,880 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,880 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5339742265212681}
 2023-07-02 10:33:54,880 [prior] Evaluating prior at array([0.30068701, 0.53397423])
 2023-07-02 10:33:54,880 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,880 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5339742265212681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,880 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,880 [classy] Re-using computed results
 2023-07-02 10:33:54,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
 2023-07-02 10:33:54,880 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5339742265212681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,880 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,900 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51335
 2023-07-02 10:33:54,900 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,900 [mcmc] New sample, #307:
   Omega_m:0.300687, b1:0.5295228
 2023-07-02 10:33:54,900 [model] Posterior to be computed for parameters {'Omega_m': 0.30970707221789884, 'b1': 0.5292726837243834}
 2023-07-02 10:33:54,900 [prior] Evaluating prior at array([0.30970707, 0.52927268])
 2023-07-02 10:33:54,900 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,900 [model] Got input parameters: {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5292726837243834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,900 [classy] Got parameters {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,900 [classy] Computing new state
 2023-07-02 10:33:54,900 [classy] Setting parameters: {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:54,944 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.595597667278}
 2023-07-02 10:33:54,944 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:54,945 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000678569
 2023-07-02 10:33:54,946 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5292726837243834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,946 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,965 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.73376
 2023-07-02 10:33:54,965 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,965 [mcmc] New sample, #308:
   Omega_m:0.300687, b1:0.5339742
 2023-07-02 10:33:54,966 [model] Posterior to be computed for parameters {'Omega_m': 0.30970707221789884, 'b1': 0.539721980067217}
 2023-07-02 10:33:54,966 [prior] Evaluating prior at array([0.30970707, 0.53972198])
 2023-07-02 10:33:54,966 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,966 [model] Got input parameters: {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.539721980067217, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,966 [classy] Got parameters {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,966 [classy] Re-using computed results
 2023-07-02 10:33:54,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.595597667278}
 2023-07-02 10:33:54,966 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:54,966 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.539721980067217, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,966 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:54,985 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.306318
 2023-07-02 10:33:54,986 [model] Computed derived parameters: {}
 2023-07-02 10:33:54,986 [model] Posterior to be computed for parameters {'Omega_m': 0.3012228524191634, 'b1': 0.5336949290732564}
 2023-07-02 10:33:54,986 [prior] Evaluating prior at array([0.30122285, 0.53369493])
 2023-07-02 10:33:54,986 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:54,986 [model] Got input parameters: {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5336949290732564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:54,986 [classy] Got parameters {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:54,986 [classy] Computing new state
 2023-07-02 10:33:54,986 [classy] Setting parameters: {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,030 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.63720674656156}
 2023-07-02 10:33:55,030 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,032 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00820173
 2023-07-02 10:33:55,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5336949290732564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,032 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,051 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57727
 2023-07-02 10:33:55,051 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,051 [mcmc] New sample, #309:
   Omega_m:0.3097071, b1:0.5292727
 2023-07-02 10:33:55,051 [model] Posterior to be computed for parameters {'Omega_m': 0.3012228524191634, 'b1': 0.5366407623995789}
 2023-07-02 10:33:55,051 [prior] Evaluating prior at array([0.30122285, 0.53664076])
 2023-07-02 10:33:55,051 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,051 [model] Got input parameters: {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366407623995789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,051 [classy] Got parameters {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,052 [classy] Re-using computed results
 2023-07-02 10:33:55,052 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.63720674656156}
 2023-07-02 10:33:55,052 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,052 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366407623995789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,052 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,072 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42146
 2023-07-02 10:33:55,072 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,072 [mcmc] New sample, #310:
   Omega_m:0.3012229, b1:0.5336949
 2023-07-02 10:33:55,072 [model] Posterior to be computed for parameters {'Omega_m': 0.30372827428679394, 'b1': 0.5353348567931795}
 2023-07-02 10:33:55,072 [prior] Evaluating prior at array([0.30372827, 0.53533486])
 2023-07-02 10:33:55,072 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,072 [model] Got input parameters: {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5353348567931795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,072 [classy] Got parameters {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,072 [classy] Computing new state
 2023-07-02 10:33:55,072 [classy] Setting parameters: {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.32696375338492}
 2023-07-02 10:33:55,117 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00500783
 2023-07-02 10:33:55,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5353348567931795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,119 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58137
 2023-07-02 10:33:55,140 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,140 [mcmc] New sample, #311:
   Omega_m:0.3012229, b1:0.5366408
 2023-07-02 10:33:55,140 [model] Posterior to be computed for parameters {'Omega_m': 0.30372827428679394, 'b1': 0.5466944657130917}
 2023-07-02 10:33:55,140 [prior] Evaluating prior at array([0.30372827, 0.54669447])
 2023-07-02 10:33:55,140 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,140 [model] Got input parameters: {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5466944657130917, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,140 [classy] Got parameters {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,140 [classy] Re-using computed results
 2023-07-02 10:33:55,140 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.32696375338492}
 2023-07-02 10:33:55,140 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,140 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5466944657130917, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,141 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,160 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.319833
 2023-07-02 10:33:55,160 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,160 [mcmc] New sample, #312:
   Omega_m:0.3037283, b1:0.5353349
 2023-07-02 10:33:55,160 [model] Posterior to be computed for parameters {'Omega_m': 0.29223895052786464, 'b1': 0.5526830668761821}
 2023-07-02 10:33:55,160 [prior] Evaluating prior at array([0.29223895, 0.55268307])
 2023-07-02 10:33:55,160 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,160 [model] Got input parameters: {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5526830668761821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,160 [classy] Got parameters {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,160 [classy] Computing new state
 2023-07-02 10:33:55,160 [classy] Setting parameters: {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,204 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.76865251727406}
 2023-07-02 10:33:55,204 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,206 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0266607
 2023-07-02 10:33:55,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5526830668761821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,226 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.65835
 2023-07-02 10:33:55,226 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,226 [mcmc] New sample, #313:
   Omega_m:0.3037283, b1:0.5466945
 2023-07-02 10:33:55,226 [model] Posterior to be computed for parameters {'Omega_m': 0.29223895052786464, 'b1': 0.5112531706938764}
 2023-07-02 10:33:55,226 [prior] Evaluating prior at array([0.29223895, 0.51125317])
 2023-07-02 10:33:55,226 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,226 [model] Got input parameters: {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112531706938764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,226 [classy] Got parameters {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,226 [classy] Re-using computed results
 2023-07-02 10:33:55,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.76865251727406}
 2023-07-02 10:33:55,226 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112531706938764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,226 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,245 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.69637
 2023-07-02 10:33:55,245 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,246 [model] Posterior to be computed for parameters {'Omega_m': 0.3042367539641901, 'b1': 0.546429429924097}
 2023-07-02 10:33:55,246 [prior] Evaluating prior at array([0.30423675, 0.54642943])
 2023-07-02 10:33:55,246 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,246 [model] Got input parameters: {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.546429429924097, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,246 [classy] Got parameters {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,246 [classy] Computing new state
 2023-07-02 10:33:55,246 [classy] Setting parameters: {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.26427327932936}
 2023-07-02 10:33:55,290 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,292 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00446046
 2023-07-02 10:33:55,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.546429429924097, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,292 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,311 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.291939
 2023-07-02 10:33:55,311 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,311 [mcmc] New sample, #314:
   Omega_m:0.292239, b1:0.5526831
 2023-07-02 10:33:55,312 [model] Posterior to be computed for parameters {'Omega_m': 0.3042367539641901, 'b1': 0.55796251155958}
 2023-07-02 10:33:55,312 [prior] Evaluating prior at array([0.30423675, 0.55796251])
 2023-07-02 10:33:55,312 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,312 [model] Got input parameters: {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.55796251155958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,312 [classy] Got parameters {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,312 [classy] Re-using computed results
 2023-07-02 10:33:55,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.26427327932936}
 2023-07-02 10:33:55,312 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.55796251155958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,312 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.79386
 2023-07-02 10:33:55,332 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,332 [model] Posterior to be computed for parameters {'Omega_m': 0.30051760779687337, 'b1': 0.5483679672593329}
 2023-07-02 10:33:55,332 [prior] Evaluating prior at array([0.30051761, 0.54836797])
 2023-07-02 10:33:55,332 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,332 [model] Got input parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483679672593329, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,332 [classy] Got parameters {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,332 [classy] Computing new state
 2023-07-02 10:33:55,332 [classy] Setting parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,376 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72494291031444}
 2023-07-02 10:33:55,376 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,378 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00925114
 2023-07-02 10:33:55,378 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483679672593329, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,378 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,397 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.358181
 2023-07-02 10:33:55,397 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,397 [mcmc] New sample, #315:
   Omega_m:0.3042368, b1:0.5464294
 2023-07-02 10:33:55,398 [model] Posterior to be computed for parameters {'Omega_m': 0.30051760779687337, 'b1': 0.5517616534781751}
 2023-07-02 10:33:55,398 [prior] Evaluating prior at array([0.30051761, 0.55176165])
 2023-07-02 10:33:55,398 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,398 [model] Got input parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5517616534781751, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,398 [classy] Got parameters {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,398 [classy] Re-using computed results
 2023-07-02 10:33:55,398 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72494291031444}
 2023-07-02 10:33:55,398 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,398 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5517616534781751, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,398 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,417 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0790448
 2023-07-02 10:33:55,417 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,417 [mcmc] New sample, #316:
   Omega_m:0.3005176, b1:0.548368
 2023-07-02 10:33:55,417 [model] Posterior to be computed for parameters {'Omega_m': 0.315347735905794, 'b1': 0.544031718774852}
 2023-07-02 10:33:55,418 [prior] Evaluating prior at array([0.31534774, 0.54403172])
 2023-07-02 10:33:55,418 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,418 [model] Got input parameters: {'Omega_m': 0.315347735905794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.544031718774852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,418 [classy] Got parameters {'Omega_m': 0.315347735905794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,418 [classy] Computing new state
 2023-07-02 10:33:55,418 [classy] Setting parameters: {'Omega_m': 0.315347735905794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,462 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91692184847935}
 2023-07-02 10:33:55,462 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000701826
 2023-07-02 10:33:55,463 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.544031718774852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,463 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,483 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60892
 2023-07-02 10:33:55,483 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,483 [model] Posterior to be computed for parameters {'Omega_m': 0.30051760779687337, 'b1': 0.5578986133933553}
 2023-07-02 10:33:55,483 [prior] Evaluating prior at array([0.30051761, 0.55789861])
 2023-07-02 10:33:55,484 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,484 [model] Got input parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5578986133933553, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,484 [classy] Got parameters {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,484 [classy] Re-using computed results
 2023-07-02 10:33:55,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72494291031444}
 2023-07-02 10:33:55,484 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,484 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5578986133933553, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,484 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,503 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.03738
 2023-07-02 10:33:55,503 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,503 [model] Posterior to be computed for parameters {'Omega_m': 0.28880168848417864, 'b1': 0.5578683634547434}
 2023-07-02 10:33:55,503 [prior] Evaluating prior at array([0.28880169, 0.55786836])
 2023-07-02 10:33:55,504 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,504 [model] Got input parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5578683634547434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,504 [classy] Got parameters {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,504 [classy] Computing new state
 2023-07-02 10:33:55,504 [classy] Setting parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.2095494159752}
 2023-07-02 10:33:55,548 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,549 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0367318
 2023-07-02 10:33:55,549 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5578683634547434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,549 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,569 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.71142
 2023-07-02 10:33:55,569 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,569 [mcmc] New sample, #317:
   Omega_m:0.3005176, b1:0.5517617
 2023-07-02 10:33:55,569 [model] Posterior to be computed for parameters {'Omega_m': 0.28880168848417864, 'b1': 0.5920363514992295}
 2023-07-02 10:33:55,569 [prior] Evaluating prior at array([0.28880169, 0.59203635])
 2023-07-02 10:33:55,569 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,569 [model] Got input parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5920363514992295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,569 [classy] Got parameters {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,569 [classy] Re-using computed results
 2023-07-02 10:33:55,569 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.2095494159752}
 2023-07-02 10:33:55,569 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,569 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5920363514992295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,569 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,589 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.78404
 2023-07-02 10:33:55,589 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,589 [model] Posterior to be computed for parameters {'Omega_m': 0.3155220090936905, 'b1': 0.5439408820434977}
 2023-07-02 10:33:55,589 [prior] Evaluating prior at array([0.31552201, 0.54394088])
 2023-07-02 10:33:55,590 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,590 [model] Got input parameters: {'Omega_m': 0.3155220090936905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5439408820434977, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,590 [classy] Got parameters {'Omega_m': 0.3155220090936905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,590 [classy] Computing new state
 2023-07-02 10:33:55,590 [classy] Setting parameters: {'Omega_m': 0.3155220090936905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,633 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8961298863702}
 2023-07-02 10:33:55,634 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,635 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000764182
 2023-07-02 10:33:55,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5439408820434977, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,635 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,655 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.66808
 2023-07-02 10:33:55,655 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,655 [model] Posterior to be computed for parameters {'Omega_m': 0.28880168848417864, 'b1': 0.5427010827084139}
 2023-07-02 10:33:55,655 [prior] Evaluating prior at array([0.28880169, 0.54270108])
 2023-07-02 10:33:55,655 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,655 [model] Got input parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5427010827084139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,655 [classy] Got parameters {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,655 [classy] Re-using computed results
 2023-07-02 10:33:55,655 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.2095494159752}
 2023-07-02 10:33:55,655 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,655 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5427010827084139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,655 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,675 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.51765
 2023-07-02 10:33:55,676 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,676 [mcmc] New sample, #318:
   Omega_m:0.2888017, b1:0.5578684
 2023-07-02 10:33:55,676 [model] Posterior to be computed for parameters {'Omega_m': 0.31252902824332013, 'b1': 0.5303336381607568}
 2023-07-02 10:33:55,676 [prior] Evaluating prior at array([0.31252903, 0.53033364])
 2023-07-02 10:33:55,676 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,676 [model] Got input parameters: {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5303336381607568, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,676 [classy] Got parameters {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,676 [classy] Computing new state
 2023-07-02 10:33:55,676 [classy] Setting parameters: {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,719 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25470681884383}
 2023-07-02 10:33:55,719 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,721 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202495
 2023-07-02 10:33:55,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5303336381607568, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,721 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,741 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09256
 2023-07-02 10:33:55,741 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,741 [mcmc] New sample, #319:
   Omega_m:0.2888017, b1:0.5427011
 2023-07-02 10:33:55,741 [model] Posterior to be computed for parameters {'Omega_m': 0.31252902824332013, 'b1': 0.5349969847240742}
 2023-07-02 10:33:55,741 [prior] Evaluating prior at array([0.31252903, 0.53499698])
 2023-07-02 10:33:55,741 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,741 [model] Got input parameters: {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5349969847240742, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,741 [classy] Got parameters {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,742 [classy] Re-using computed results
 2023-07-02 10:33:55,742 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25470681884383}
 2023-07-02 10:33:55,742 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,742 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5349969847240742, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,742 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,761 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.364768
 2023-07-02 10:33:55,761 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,761 [mcmc] New sample, #320:
   Omega_m:0.312529, b1:0.5303336
 2023-07-02 10:33:55,761 [mcmc] Learn + convergence test @ 320 samples accepted.
 2023-07-02 10:33:55,761 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:33:55,766 [mcmc]  - Acceptance rate: 0.368
 2023-07-02 10:33:55,766 [mcmc]  - Condition number = 5.35886
 2023-07-02 10:33:55,767 [mcmc]  - Eigenvalues = array([0.02628313, 0.14084773])
 2023-07-02 10:33:55,767 [mcmc]  - Convergence of means: R-1 = 0.140848 after 256 accepted steps
 2023-07-02 10:33:55,767 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:33:55,767 [mcmc] array([[ 5.83849144e-05, -8.25621038e-05],
       [-8.25621038e-05,  2.49234300e-04]])
 2023-07-02 10:33:55,777 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:33:55,777 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.5360462540036722}
 2023-07-02 10:33:55,777 [prior] Evaluating prior at array([0.31178702, 0.53604625])
 2023-07-02 10:33:55,777 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,778 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5360462540036722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,778 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,778 [classy] Computing new state
 2023-07-02 10:33:55,778 [classy] Setting parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,822 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
 2023-07-02 10:33:55,822 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,824 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000232208
 2023-07-02 10:33:55,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5360462540036722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,824 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,845 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.39113
 2023-07-02 10:33:55,845 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,845 [mcmc] New sample, #321:
   Omega_m:0.312529, b1:0.534997
 2023-07-02 10:33:55,845 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.4810306514882249}
 2023-07-02 10:33:55,846 [prior] Evaluating prior at array([0.31178702, 0.48103065])
 2023-07-02 10:33:55,846 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,846 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4810306514882249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,846 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,846 [classy] Re-using computed results
 2023-07-02 10:33:55,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
 2023-07-02 10:33:55,846 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4810306514882249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,846 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,867 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20285
 2023-07-02 10:33:55,867 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,867 [mcmc] New sample, #322:
   Omega_m:0.311787, b1:0.5360463
 2023-07-02 10:33:55,867 [model] Posterior to be computed for parameters {'Omega_m': 0.28176681452625685, 'b1': 0.5234822266581105}
 2023-07-02 10:33:55,867 [prior] Evaluating prior at array([0.28176681, 0.52348223])
 2023-07-02 10:33:55,867 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,867 [model] Got input parameters: {'Omega_m': 0.28176681452625685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5234822266581105, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,867 [classy] Got parameters {'Omega_m': 0.28176681452625685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,868 [classy] Computing new state
 2023-07-02 10:33:55,868 [classy] Setting parameters: {'Omega_m': 0.28176681452625685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:55,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.12627460344692}
 2023-07-02 10:33:55,913 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:55,915 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0628039
 2023-07-02 10:33:55,915 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5234822266581105, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,915 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,936 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.7502
 2023-07-02 10:33:55,936 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,936 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.49669222638878036}
 2023-07-02 10:33:55,936 [prior] Evaluating prior at array([0.31178702, 0.49669223])
 2023-07-02 10:33:55,936 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,936 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49669222638878036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,936 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,936 [classy] Re-using computed results
 2023-07-02 10:33:55,936 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
 2023-07-02 10:33:55,936 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:55,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49669222638878036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,936 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:55,956 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62086
 2023-07-02 10:33:55,956 [model] Computed derived parameters: {}
 2023-07-02 10:33:55,956 [mcmc] New sample, #323:
   Omega_m:0.311787, b1:0.4810307
 2023-07-02 10:33:55,956 [model] Posterior to be computed for parameters {'Omega_m': 0.2993613265823718, 'b1': 0.51426340318561}
 2023-07-02 10:33:55,956 [prior] Evaluating prior at array([0.29936133, 0.5142634 ])
 2023-07-02 10:33:55,956 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:55,956 [model] Got input parameters: {'Omega_m': 0.2993613265823718, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.51426340318561, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:55,956 [classy] Got parameters {'Omega_m': 0.2993613265823718, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:55,956 [classy] Computing new state
 2023-07-02 10:33:55,956 [classy] Setting parameters: {'Omega_m': 0.2993613265823718, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.86920239485838}
 2023-07-02 10:33:56,001 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111168
 2023-07-02 10:33:56,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.51426340318561, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,003 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,024 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.872277
 2023-07-02 10:33:56,024 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,024 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.47886160727360505}
 2023-07-02 10:33:56,024 [prior] Evaluating prior at array([0.31178702, 0.47886161])
 2023-07-02 10:33:56,025 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,025 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47886160727360505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,025 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,025 [classy] Re-using computed results
 2023-07-02 10:33:56,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
 2023-07-02 10:33:56,025 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47886160727360505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,025 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,045 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.908878
 2023-07-02 10:33:56,045 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,045 [model] Posterior to be computed for parameters {'Omega_m': 0.319497004670791, 'b1': 0.48578954208882735}
 2023-07-02 10:33:56,045 [prior] Evaluating prior at array([0.319497  , 0.48578954])
 2023-07-02 10:33:56,046 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,046 [model] Got input parameters: {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48578954208882735, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,046 [classy] Got parameters {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,046 [classy] Computing new state
 2023-07-02 10:33:56,046 [classy] Setting parameters: {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,092 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.42459552908923}
 2023-07-02 10:33:56,092 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,094 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00316618
 2023-07-02 10:33:56,094 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48578954208882735, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,094 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,113 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71434
 2023-07-02 10:33:56,113 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,113 [mcmc] New sample, #324:
   Omega_m:0.311787, b1:0.4966922
 2023-07-02 10:33:56,113 [model] Posterior to be computed for parameters {'Omega_m': 0.319497004670791, 'b1': 0.492789554306529}
 2023-07-02 10:33:56,113 [prior] Evaluating prior at array([0.319497  , 0.49278955])
 2023-07-02 10:33:56,114 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,114 [model] Got input parameters: {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.492789554306529, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,114 [classy] Got parameters {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,114 [classy] Re-using computed results
 2023-07-02 10:33:56,114 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.42459552908923}
 2023-07-02 10:33:56,114 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,114 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.492789554306529, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,114 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,136 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82341
 2023-07-02 10:33:56,136 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,137 [mcmc] New sample, #325:
   Omega_m:0.319497, b1:0.4857895
 2023-07-02 10:33:56,137 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.4797572152794664}
 2023-07-02 10:33:56,137 [prior] Evaluating prior at array([0.328713  , 0.47975722])
 2023-07-02 10:33:56,137 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,137 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4797572152794664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,137 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,137 [classy] Computing new state
 2023-07-02 10:33:56,137 [classy] Setting parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
 2023-07-02 10:33:56,181 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,183 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0157236
 2023-07-02 10:33:56,183 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4797572152794664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,183 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,202 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9058
 2023-07-02 10:33:56,202 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,202 [mcmc] New sample, #326:
   Omega_m:0.319497, b1:0.4927896
 2023-07-02 10:33:56,202 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.5012586211377089}
 2023-07-02 10:33:56,202 [prior] Evaluating prior at array([0.328713  , 0.50125862])
 2023-07-02 10:33:56,203 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,203 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5012586211377089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,203 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,203 [classy] Re-using computed results
 2023-07-02 10:33:56,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
 2023-07-02 10:33:56,203 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5012586211377089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,203 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,222 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.094407
 2023-07-02 10:33:56,222 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,222 [mcmc] New sample, #327:
   Omega_m:0.328713, b1:0.4797572
 2023-07-02 10:33:56,222 [model] Posterior to be computed for parameters {'Omega_m': 0.3543550335157322, 'b1': 0.4649982238049591}
 2023-07-02 10:33:56,222 [prior] Evaluating prior at array([0.35435503, 0.46499822])
 2023-07-02 10:33:56,222 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,222 [model] Got input parameters: {'Omega_m': 0.3543550335157322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4649982238049591, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,222 [classy] Got parameters {'Omega_m': 0.3543550335157322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,222 [classy] Computing new state
 2023-07-02 10:33:56,222 [classy] Setting parameters: {'Omega_m': 0.3543550335157322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.5018683268413}
 2023-07-02 10:33:56,266 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0974575
 2023-07-02 10:33:56,268 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4649982238049591, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,268 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,288 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.05577
 2023-07-02 10:33:56,288 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,288 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.5488506990338249}
 2023-07-02 10:33:56,288 [prior] Evaluating prior at array([0.328713 , 0.5488507])
 2023-07-02 10:33:56,288 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,288 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5488506990338249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,288 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,288 [classy] Re-using computed results
 2023-07-02 10:33:56,288 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
 2023-07-02 10:33:56,288 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,288 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5488506990338249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,289 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,308 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.8567
 2023-07-02 10:33:56,308 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,308 [model] Posterior to be computed for parameters {'Omega_m': 0.3356905369090545, 'b1': 0.4913916872625205}
 2023-07-02 10:33:56,308 [prior] Evaluating prior at array([0.33569054, 0.49139169])
 2023-07-02 10:33:56,308 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,308 [model] Got input parameters: {'Omega_m': 0.3356905369090545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4913916872625205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,308 [classy] Got parameters {'Omega_m': 0.3356905369090545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,308 [classy] Computing new state
 2023-07-02 10:33:56,308 [classy] Setting parameters: {'Omega_m': 0.3356905369090545, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5563543638445}
 2023-07-02 10:33:56,352 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,354 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0314115
 2023-07-02 10:33:56,354 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4913916872625205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,354 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,373 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.53935
 2023-07-02 10:33:56,374 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,374 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.505162320511507}
 2023-07-02 10:33:56,374 [prior] Evaluating prior at array([0.328713  , 0.50516232])
 2023-07-02 10:33:56,374 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,374 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.505162320511507, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,374 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,374 [classy] Re-using computed results
 2023-07-02 10:33:56,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
 2023-07-02 10:33:56,374 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.505162320511507, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,374 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,394 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.521766
 2023-07-02 10:33:56,394 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,394 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5208527644901814}
 2023-07-02 10:33:56,394 [prior] Evaluating prior at array([0.31485674, 0.52085276])
 2023-07-02 10:33:56,394 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,394 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5208527644901814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,395 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,395 [classy] Computing new state
 2023-07-02 10:33:56,395 [classy] Setting parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,438 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
 2023-07-02 10:33:56,438 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,440 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000545684
 2023-07-02 10:33:56,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5208527644901814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,440 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,459 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7987
 2023-07-02 10:33:56,459 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,459 [mcmc] New sample, #328:
   Omega_m:0.328713, b1:0.5012586
 2023-07-02 10:33:56,459 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5260896995663333}
 2023-07-02 10:33:56,460 [prior] Evaluating prior at array([0.31485674, 0.5260897 ])
 2023-07-02 10:33:56,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,460 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5260896995663333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,460 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,460 [classy] Re-using computed results
 2023-07-02 10:33:56,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
 2023-07-02 10:33:56,460 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5260896995663333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,480 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.13063
 2023-07-02 10:33:56,480 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,480 [mcmc] New sample, #329:
   Omega_m:0.3148567, b1:0.5208528
 2023-07-02 10:33:56,480 [model] Posterior to be computed for parameters {'Omega_m': 0.2948052999495469, 'b1': 0.5544444333077412}
 2023-07-02 10:33:56,480 [prior] Evaluating prior at array([0.2948053 , 0.55444443])
 2023-07-02 10:33:56,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,480 [model] Got input parameters: {'Omega_m': 0.2948052999495469, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5544444333077412, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,480 [classy] Got parameters {'Omega_m': 0.2948052999495469, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,480 [classy] Computing new state
 2023-07-02 10:33:56,480 [classy] Setting parameters: {'Omega_m': 0.2948052999495469, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4423876450121}
 2023-07-02 10:33:56,524 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,526 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0202447
 2023-07-02 10:33:56,526 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5544444333077412, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,526 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,546 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.43539
 2023-07-02 10:33:56,546 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,546 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5484704507863232}
 2023-07-02 10:33:56,546 [prior] Evaluating prior at array([0.31485674, 0.54847045])
 2023-07-02 10:33:56,546 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,546 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5484704507863232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,546 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,546 [classy] Re-using computed results
 2023-07-02 10:33:56,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
 2023-07-02 10:33:56,547 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5484704507863232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,547 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.55068
 2023-07-02 10:33:56,566 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,566 [model] Posterior to be computed for parameters {'Omega_m': 0.35670040994647145, 'b1': 0.4669185622204331}
 2023-07-02 10:33:56,566 [prior] Evaluating prior at array([0.35670041, 0.46691856])
 2023-07-02 10:33:56,566 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,566 [model] Got input parameters: {'Omega_m': 0.35670040994647145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4669185622204331, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,566 [classy] Got parameters {'Omega_m': 0.35670040994647145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,566 [classy] Computing new state
 2023-07-02 10:33:56,566 [classy] Setting parameters: {'Omega_m': 0.35670040994647145, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.25075137877093}
 2023-07-02 10:33:56,610 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.108076
 2023-07-02 10:33:56,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4669185622204331, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,612 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,631 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2832
 2023-07-02 10:33:56,632 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,632 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5057755739912578}
 2023-07-02 10:33:56,632 [prior] Evaluating prior at array([0.31485674, 0.50577557])
 2023-07-02 10:33:56,632 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,632 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5057755739912578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,632 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,632 [classy] Re-using computed results
 2023-07-02 10:33:56,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
 2023-07-02 10:33:56,632 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,632 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5057755739912578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,632 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,652 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85375
 2023-07-02 10:33:56,652 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,652 [mcmc] New sample, #330:
   Omega_m:0.3148567, b1:0.5260897
 2023-07-02 10:33:56,652 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.5374477849642203}
 2023-07-02 10:33:56,652 [prior] Evaluating prior at array([0.2924593 , 0.53744778])
 2023-07-02 10:33:56,652 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,652 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5374477849642203, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,652 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,652 [classy] Computing new state
 2023-07-02 10:33:56,652 [classy] Setting parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,696 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
 2023-07-02 10:33:56,696 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,698 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0260732
 2023-07-02 10:33:56,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5374477849642203, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,698 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,717 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.307959
 2023-07-02 10:33:56,718 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,718 [mcmc] New sample, #331:
   Omega_m:0.3148567, b1:0.5057756
 2023-07-02 10:33:56,718 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.5168254349462263}
 2023-07-02 10:33:56,718 [prior] Evaluating prior at array([0.2924593 , 0.51682543])
 2023-07-02 10:33:56,718 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,718 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5168254349462263, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,718 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,718 [classy] Re-using computed results
 2023-07-02 10:33:56,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
 2023-07-02 10:33:56,718 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,718 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5168254349462263, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,718 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,738 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.80425
 2023-07-02 10:33:56,738 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,738 [mcmc] New sample, #332:
   Omega_m:0.2924593, b1:0.5374478
 2023-07-02 10:33:56,739 [model] Posterior to be computed for parameters {'Omega_m': 0.2783700799838957, 'b1': 0.5367490012167613}
 2023-07-02 10:33:56,739 [prior] Evaluating prior at array([0.27837008, 0.536749  ])
 2023-07-02 10:33:56,739 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,739 [model] Got input parameters: {'Omega_m': 0.2783700799838957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5367490012167613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,739 [classy] Got parameters {'Omega_m': 0.2783700799838957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,739 [classy] Computing new state
 2023-07-02 10:33:56,739 [classy] Setting parameters: {'Omega_m': 0.2783700799838957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,783 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.5759755620221}
 2023-07-02 10:33:56,783 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0781141
 2023-07-02 10:33:56,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5367490012167613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,784 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,804 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.22381
 2023-07-02 10:33:56,804 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,804 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.6169558330306847}
 2023-07-02 10:33:56,804 [prior] Evaluating prior at array([0.2924593 , 0.61695583])
 2023-07-02 10:33:56,805 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,805 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6169558330306847, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,805 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,805 [classy] Re-using computed results
 2023-07-02 10:33:56,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
 2023-07-02 10:33:56,805 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,805 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6169558330306847, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,805 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,824 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.5143
 2023-07-02 10:33:56,824 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,824 [model] Posterior to be computed for parameters {'Omega_m': 0.2718894070263659, 'b1': 0.5459133204314447}
 2023-07-02 10:33:56,824 [prior] Evaluating prior at array([0.27188941, 0.54591332])
 2023-07-02 10:33:56,824 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,824 [model] Got input parameters: {'Omega_m': 0.2718894070263659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5459133204314447, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,824 [classy] Got parameters {'Omega_m': 0.2718894070263659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,824 [classy] Computing new state
 2023-07-02 10:33:56,824 [classy] Setting parameters: {'Omega_m': 0.2718894070263659, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,869 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.4470986127955}
 2023-07-02 10:33:56,869 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,871 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.11246
 2023-07-02 10:33:56,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5459133204314447, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,871 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,890 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.3249
 2023-07-02 10:33:56,891 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,891 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.5069827720525667}
 2023-07-02 10:33:56,891 [prior] Evaluating prior at array([0.2924593 , 0.50698277])
 2023-07-02 10:33:56,891 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,891 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5069827720525667, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,891 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,891 [classy] Re-using computed results
 2023-07-02 10:33:56,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
 2023-07-02 10:33:56,891 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,891 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5069827720525667, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,891 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,911 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.25973
 2023-07-02 10:33:56,911 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,911 [mcmc] New sample, #333:
   Omega_m:0.2924593, b1:0.5168254
 2023-07-02 10:33:56,911 [model] Posterior to be computed for parameters {'Omega_m': 0.3093521914785011, 'b1': 0.4830945364404621}
 2023-07-02 10:33:56,911 [prior] Evaluating prior at array([0.30935219, 0.48309454])
 2023-07-02 10:33:56,911 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,911 [model] Got input parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4830945364404621, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,911 [classy] Got parameters {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,911 [classy] Computing new state
 2023-07-02 10:33:56,911 [classy] Setting parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:56,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63865989616025}
 2023-07-02 10:33:56,955 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:56,957 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000808593
 2023-07-02 10:33:56,957 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4830945364404621, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,957 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,977 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.756472
 2023-07-02 10:33:56,977 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,977 [mcmc] New sample, #334:
   Omega_m:0.2924593, b1:0.5069828
 2023-07-02 10:33:56,977 [model] Posterior to be computed for parameters {'Omega_m': 0.3093521914785011, 'b1': 0.46985935379866645}
 2023-07-02 10:33:56,977 [prior] Evaluating prior at array([0.30935219, 0.46985935])
 2023-07-02 10:33:56,977 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,977 [model] Got input parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46985935379866645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,977 [classy] Got parameters {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,977 [classy] Re-using computed results
 2023-07-02 10:33:56,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63865989616025}
 2023-07-02 10:33:56,977 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:56,977 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46985935379866645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,977 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:56,997 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.54205
 2023-07-02 10:33:56,997 [model] Computed derived parameters: {}
 2023-07-02 10:33:56,997 [model] Posterior to be computed for parameters {'Omega_m': 0.29434259735560503, 'b1': 0.5043196025295068}
 2023-07-02 10:33:56,997 [prior] Evaluating prior at array([0.2943426, 0.5043196])
 2023-07-02 10:33:56,998 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:56,998 [model] Got input parameters: {'Omega_m': 0.29434259735560503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5043196025295068, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:56,998 [classy] Got parameters {'Omega_m': 0.29434259735560503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:56,998 [classy] Computing new state
 2023-07-02 10:33:56,998 [classy] Setting parameters: {'Omega_m': 0.29434259735560503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.5010298673712}
 2023-07-02 10:33:57,043 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,045 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0213328
 2023-07-02 10:33:57,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5043196025295068, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,045 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,064 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60974
 2023-07-02 10:33:57,064 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,064 [model] Posterior to be computed for parameters {'Omega_m': 0.3093521914785011, 'b1': 0.4694589962158406}
 2023-07-02 10:33:57,064 [prior] Evaluating prior at array([0.30935219, 0.469459  ])
 2023-07-02 10:33:57,065 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,065 [model] Got input parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4694589962158406, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,065 [classy] Got parameters {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,065 [classy] Re-using computed results
 2023-07-02 10:33:57,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63865989616025}
 2023-07-02 10:33:57,065 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,065 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4694589962158406, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,065 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,084 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.62466
 2023-07-02 10:33:57,084 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,084 [model] Posterior to be computed for parameters {'Omega_m': 0.30475123840662965, 'b1': 0.48960074388507907}
 2023-07-02 10:33:57,085 [prior] Evaluating prior at array([0.30475124, 0.48960074])
 2023-07-02 10:33:57,085 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,085 [model] Got input parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48960074388507907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,085 [classy] Got parameters {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,085 [classy] Computing new state
 2023-07-02 10:33:57,085 [classy] Setting parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,129 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2009367594883}
 2023-07-02 10:33:57,129 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,131 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00394095
 2023-07-02 10:33:57,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48960074388507907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,131 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,152 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0527742
 2023-07-02 10:33:57,152 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,152 [mcmc] New sample, #335:
   Omega_m:0.3093522, b1:0.4830945
 2023-07-02 10:33:57,152 [model] Posterior to be computed for parameters {'Omega_m': 0.30475123840662965, 'b1': 0.4666158906380616}
 2023-07-02 10:33:57,152 [prior] Evaluating prior at array([0.30475124, 0.46661589])
 2023-07-02 10:33:57,152 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,152 [model] Got input parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4666158906380616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,152 [classy] Got parameters {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,152 [classy] Re-using computed results
 2023-07-02 10:33:57,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2009367594883}
 2023-07-02 10:33:57,152 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4666158906380616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,152 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,172 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.65046
 2023-07-02 10:33:57,172 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,172 [model] Posterior to be computed for parameters {'Omega_m': 0.29851669274326603, 'b1': 0.4984170145088265}
 2023-07-02 10:33:57,172 [prior] Evaluating prior at array([0.29851669, 0.49841701])
 2023-07-02 10:33:57,172 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,172 [model] Got input parameters: {'Omega_m': 0.29851669274326603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4984170145088265, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,172 [classy] Got parameters {'Omega_m': 0.29851669274326603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,172 [classy] Computing new state
 2023-07-02 10:33:57,172 [classy] Setting parameters: {'Omega_m': 0.29851669274326603, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.97488737327072}
 2023-07-02 10:33:57,216 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,218 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0125939
 2023-07-02 10:33:57,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4984170145088265, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,218 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,237 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.35682
 2023-07-02 10:33:57,238 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,238 [model] Posterior to be computed for parameters {'Omega_m': 0.30475123840662965, 'b1': 0.5187947111097473}
 2023-07-02 10:33:57,238 [prior] Evaluating prior at array([0.30475124, 0.51879471])
 2023-07-02 10:33:57,238 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,238 [model] Got input parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187947111097473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,238 [classy] Got parameters {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,238 [classy] Re-using computed results
 2023-07-02 10:33:57,238 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2009367594883}
 2023-07-02 10:33:57,238 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187947111097473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,238 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,258 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28626
 2023-07-02 10:33:57,258 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,258 [mcmc] New sample, #336:
   Omega_m:0.3047512, b1:0.4896007
 2023-07-02 10:33:57,258 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5202858942841632}
 2023-07-02 10:33:57,258 [prior] Evaluating prior at array([0.30369673, 0.52028589])
 2023-07-02 10:33:57,258 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,258 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5202858942841632, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,258 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,258 [classy] Computing new state
 2023-07-02 10:33:57,258 [classy] Setting parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,302 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
 2023-07-02 10:33:57,302 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,304 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00504291
 2023-07-02 10:33:57,304 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5202858942841632, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,304 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,323 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14607
 2023-07-02 10:33:57,323 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,323 [mcmc] New sample, #337:
   Omega_m:0.3047512, b1:0.5187947
 2023-07-02 10:33:57,323 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.508255803699687}
 2023-07-02 10:33:57,323 [prior] Evaluating prior at array([0.30369673, 0.5082558 ])
 2023-07-02 10:33:57,323 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,323 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.508255803699687, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,323 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,324 [classy] Re-using computed results
 2023-07-02 10:33:57,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
 2023-07-02 10:33:57,324 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.508255803699687, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,324 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,343 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72783
 2023-07-02 10:33:57,343 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,343 [mcmc] New sample, #338:
   Omega_m:0.3036967, b1:0.5202859
 2023-07-02 10:33:57,343 [model] Posterior to be computed for parameters {'Omega_m': 0.27840067413578484, 'b1': 0.5440269517750643}
 2023-07-02 10:33:57,343 [prior] Evaluating prior at array([0.27840067, 0.54402695])
 2023-07-02 10:33:57,343 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,343 [model] Got input parameters: {'Omega_m': 0.27840067413578484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5440269517750643, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,343 [classy] Got parameters {'Omega_m': 0.27840067413578484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,343 [classy] Computing new state
 2023-07-02 10:33:57,343 [classy] Setting parameters: {'Omega_m': 0.27840067413578484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,387 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.57190649804704}
 2023-07-02 10:33:57,387 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,389 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0779682
 2023-07-02 10:33:57,389 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5440269517750643, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,389 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,408 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.24831
 2023-07-02 10:33:57,408 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,409 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5004668867843597}
 2023-07-02 10:33:57,409 [prior] Evaluating prior at array([0.30369673, 0.50046689])
 2023-07-02 10:33:57,409 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,409 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5004668867843597, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,409 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,409 [classy] Re-using computed results
 2023-07-02 10:33:57,409 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
 2023-07-02 10:33:57,409 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,409 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5004668867843597, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,409 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,428 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05921
 2023-07-02 10:33:57,428 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,428 [model] Posterior to be computed for parameters {'Omega_m': 0.2977286925026266, 'b1': 0.5166952022388994}
 2023-07-02 10:33:57,428 [prior] Evaluating prior at array([0.29772869, 0.5166952 ])
 2023-07-02 10:33:57,428 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,428 [model] Got input parameters: {'Omega_m': 0.2977286925026266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166952022388994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,429 [classy] Got parameters {'Omega_m': 0.2977286925026266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,429 [classy] Computing new state
 2023-07-02 10:33:57,429 [classy] Setting parameters: {'Omega_m': 0.2977286925026266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.07372260836118}
 2023-07-02 10:33:57,473 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,474 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0140596
 2023-07-02 10:33:57,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166952022388994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,474 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,493 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.493463
 2023-07-02 10:33:57,494 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,494 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5249174652095655}
 2023-07-02 10:33:57,494 [prior] Evaluating prior at array([0.30369673, 0.52491747])
 2023-07-02 10:33:57,494 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,494 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5249174652095655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,494 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,494 [classy] Re-using computed results
 2023-07-02 10:33:57,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
 2023-07-02 10:33:57,494 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,494 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5249174652095655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,494 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,514 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.10325
 2023-07-02 10:33:57,514 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,514 [mcmc] New sample, #339:
   Omega_m:0.3036967, b1:0.5082558
 2023-07-02 10:33:57,514 [model] Posterior to be computed for parameters {'Omega_m': 0.27941781513620356, 'b1': 0.5592502742613158}
 2023-07-02 10:33:57,514 [prior] Evaluating prior at array([0.27941782, 0.55925027])
 2023-07-02 10:33:57,514 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,514 [model] Got input parameters: {'Omega_m': 0.27941781513620356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5592502742613158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,514 [classy] Got parameters {'Omega_m': 0.27941781513620356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,514 [classy] Computing new state
 2023-07-02 10:33:57,514 [classy] Setting parameters: {'Omega_m': 0.27941781513620356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,558 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.43676876012066}
 2023-07-02 10:33:57,558 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,560 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0731982
 2023-07-02 10:33:57,560 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5592502742613158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,560 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,579 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.51244
 2023-07-02 10:33:57,579 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,579 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5323495960847019}
 2023-07-02 10:33:57,579 [prior] Evaluating prior at array([0.30369673, 0.5323496 ])
 2023-07-02 10:33:57,580 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,580 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5323495960847019, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,580 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,580 [classy] Re-using computed results
 2023-07-02 10:33:57,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
 2023-07-02 10:33:57,580 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,580 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5323495960847019, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,580 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,599 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79196
 2023-07-02 10:33:57,599 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,599 [model] Posterior to be computed for parameters {'Omega_m': 0.3164564435048646, 'b1': 0.506873952254501}
 2023-07-02 10:33:57,599 [prior] Evaluating prior at array([0.31645644, 0.50687395])
 2023-07-02 10:33:57,600 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,600 [model] Got input parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.506873952254501, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,600 [classy] Got parameters {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,600 [classy] Computing new state
 2023-07-02 10:33:57,600 [classy] Setting parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.78481102943462}
 2023-07-02 10:33:57,643 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00116058
 2023-07-02 10:33:57,645 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.506873952254501, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,645 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,665 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68868
 2023-07-02 10:33:57,665 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,665 [mcmc] New sample, #340:
   Omega_m:0.3036967, b1:0.5249175
 2023-07-02 10:33:57,665 [model] Posterior to be computed for parameters {'Omega_m': 0.3164564435048646, 'b1': 0.5181945269301252}
 2023-07-02 10:33:57,665 [prior] Evaluating prior at array([0.31645644, 0.51819453])
 2023-07-02 10:33:57,665 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,665 [model] Got input parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5181945269301252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,666 [classy] Got parameters {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,666 [classy] Re-using computed results
 2023-07-02 10:33:57,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.78481102943462}
 2023-07-02 10:33:57,666 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,666 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5181945269301252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,666 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,685 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76077
 2023-07-02 10:33:57,686 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,686 [model] Posterior to be computed for parameters {'Omega_m': 0.33353294197643324, 'b1': 0.4827260768582154}
 2023-07-02 10:33:57,686 [prior] Evaluating prior at array([0.33353294, 0.48272608])
 2023-07-02 10:33:57,686 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,686 [model] Got input parameters: {'Omega_m': 0.33353294197643324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4827260768582154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,686 [classy] Got parameters {'Omega_m': 0.33353294197643324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,686 [classy] Computing new state
 2023-07-02 10:33:57,686 [classy] Setting parameters: {'Omega_m': 0.33353294197643324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,730 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.80051424165774}
 2023-07-02 10:33:57,730 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,732 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0260108
 2023-07-02 10:33:57,732 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4827260768582154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,732 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,751 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.466693
 2023-07-02 10:33:57,751 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,751 [model] Posterior to be computed for parameters {'Omega_m': 0.3164564435048646, 'b1': 0.5562248129981515}
 2023-07-02 10:33:57,751 [prior] Evaluating prior at array([0.31645644, 0.55622481])
 2023-07-02 10:33:57,752 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,752 [model] Got input parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5562248129981515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,752 [classy] Got parameters {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,752 [classy] Re-using computed results
 2023-07-02 10:33:57,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.78481102943462}
 2023-07-02 10:33:57,752 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,752 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5562248129981515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,752 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,771 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.88263
 2023-07-02 10:33:57,771 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,772 [model] Posterior to be computed for parameters {'Omega_m': 0.31640918084833974, 'b1': 0.5069407863740696}
 2023-07-02 10:33:57,772 [prior] Evaluating prior at array([0.31640918, 0.50694079])
 2023-07-02 10:33:57,772 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,772 [model] Got input parameters: {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5069407863740696, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,772 [classy] Got parameters {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,772 [classy] Computing new state
 2023-07-02 10:33:57,772 [classy] Setting parameters: {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,816 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7904324880373}
 2023-07-02 10:33:57,816 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,818 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00113805
 2023-07-02 10:33:57,818 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5069407863740696, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,818 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,837 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69029
 2023-07-02 10:33:57,837 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,837 [mcmc] New sample, #341:
   Omega_m:0.3164564, b1:0.506874
 2023-07-02 10:33:57,837 [model] Posterior to be computed for parameters {'Omega_m': 0.31640918084833974, 'b1': 0.5073199169572127}
 2023-07-02 10:33:57,837 [prior] Evaluating prior at array([0.31640918, 0.50731992])
 2023-07-02 10:33:57,838 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,838 [model] Got input parameters: {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5073199169572127, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,838 [classy] Got parameters {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,838 [classy] Re-using computed results
 2023-07-02 10:33:57,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7904324880373}
 2023-07-02 10:33:57,838 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,838 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5073199169572127, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,838 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,858 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6709
 2023-07-02 10:33:57,858 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,858 [mcmc] New sample, #342:
   Omega_m:0.3164092, b1:0.5069408
 2023-07-02 10:33:57,858 [model] Posterior to be computed for parameters {'Omega_m': 0.32195202798203837, 'b1': 0.49948177718001757}
 2023-07-02 10:33:57,858 [prior] Evaluating prior at array([0.32195203, 0.49948178])
 2023-07-02 10:33:57,858 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,858 [model] Got input parameters: {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49948177718001757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,859 [classy] Got parameters {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,859 [classy] Computing new state
 2023-07-02 10:33:57,859 [classy] Setting parameters: {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,902 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13596828734586}
 2023-07-02 10:33:57,902 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,905 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00557209
 2023-07-02 10:33:57,905 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49948177718001757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,905 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,924 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29797
 2023-07-02 10:33:57,924 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,925 [mcmc] New sample, #343:
   Omega_m:0.3164092, b1:0.5073199
 2023-07-02 10:33:57,925 [model] Posterior to be computed for parameters {'Omega_m': 0.32195202798203837, 'b1': 0.5393403046853895}
 2023-07-02 10:33:57,925 [prior] Evaluating prior at array([0.32195203, 0.5393403 ])
 2023-07-02 10:33:57,925 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,925 [model] Got input parameters: {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5393403046853895, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,925 [classy] Got parameters {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,925 [classy] Re-using computed results
 2023-07-02 10:33:57,925 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13596828734586}
 2023-07-02 10:33:57,925 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:57,925 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5393403046853895, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,925 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:57,944 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.93258
 2023-07-02 10:33:57,944 [model] Computed derived parameters: {}
 2023-07-02 10:33:57,944 [model] Posterior to be computed for parameters {'Omega_m': 0.3271694096315802, 'b1': 0.49210387812314904}
 2023-07-02 10:33:57,945 [prior] Evaluating prior at array([0.32716941, 0.49210388])
 2023-07-02 10:33:57,945 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:57,945 [model] Got input parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49210387812314904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,945 [classy] Got parameters {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:57,945 [classy] Computing new state
 2023-07-02 10:33:57,945 [classy] Setting parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:57,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5290514821312}
 2023-07-02 10:33:57,989 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:57,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129586
 2023-07-02 10:33:57,991 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49210387812314904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:57,991 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,011 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.63138
 2023-07-02 10:33:58,011 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,011 [mcmc] New sample, #344:
   Omega_m:0.321952, b1:0.4994818
 2023-07-02 10:33:58,011 [model] Posterior to be computed for parameters {'Omega_m': 0.3271694096315802, 'b1': 0.512544607465576}
 2023-07-02 10:33:58,011 [prior] Evaluating prior at array([0.32716941, 0.51254461])
 2023-07-02 10:33:58,011 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,011 [model] Got input parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.512544607465576, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,011 [classy] Got parameters {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,011 [classy] Re-using computed results
 2023-07-02 10:33:58,012 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5290514821312}
 2023-07-02 10:33:58,012 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,012 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.512544607465576, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,012 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.15347
 2023-07-02 10:33:58,031 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,031 [model] Posterior to be computed for parameters {'Omega_m': 0.34450779123450037, 'b1': 0.4675856738075715}
 2023-07-02 10:33:58,031 [prior] Evaluating prior at array([0.34450779, 0.46758567])
 2023-07-02 10:33:58,031 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,031 [model] Got input parameters: {'Omega_m': 0.34450779123450037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4675856738075715, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,031 [classy] Got parameters {'Omega_m': 0.34450779123450037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,031 [classy] Computing new state
 2023-07-02 10:33:58,032 [classy] Setting parameters: {'Omega_m': 0.34450779123450037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.57309944634636}
 2023-07-02 10:33:58,076 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0584099
 2023-07-02 10:33:58,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4675856738075715, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,078 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,097 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.54067
 2023-07-02 10:33:58,097 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,097 [model] Posterior to be computed for parameters {'Omega_m': 0.3271694096315802, 'b1': 0.4353646958261076}
 2023-07-02 10:33:58,097 [prior] Evaluating prior at array([0.32716941, 0.4353647 ])
 2023-07-02 10:33:58,098 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,098 [model] Got input parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4353646958261076, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,098 [classy] Got parameters {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,098 [classy] Re-using computed results
 2023-07-02 10:33:58,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5290514821312}
 2023-07-02 10:33:58,098 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4353646958261076, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,098 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,118 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.64533
 2023-07-02 10:33:58,118 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,118 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.4667088370770122}
 2023-07-02 10:33:58,118 [prior] Evaluating prior at array([0.34512786, 0.46670884])
 2023-07-02 10:33:58,119 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,119 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4667088370770122, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,119 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,119 [classy] Computing new state
 2023-07-02 10:33:58,119 [classy] Setting parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
 2023-07-02 10:33:58,164 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0605977
 2023-07-02 10:33:58,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4667088370770122, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,166 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,185 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.74016
 2023-07-02 10:33:58,185 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,185 [mcmc] New sample, #345:
   Omega_m:0.3271694, b1:0.4921039
 2023-07-02 10:33:58,185 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.4622165594146393}
 2023-07-02 10:33:58,185 [prior] Evaluating prior at array([0.34512786, 0.46221656])
 2023-07-02 10:33:58,185 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,185 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4622165594146393, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,185 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,186 [classy] Re-using computed results
 2023-07-02 10:33:58,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
 2023-07-02 10:33:58,186 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4622165594146393, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.26434
 2023-07-02 10:33:58,205 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,205 [mcmc] New sample, #346:
   Omega_m:0.3451279, b1:0.4667088
 2023-07-02 10:33:58,205 [model] Posterior to be computed for parameters {'Omega_m': 0.3561250594681581, 'b1': 0.44666541787912345}
 2023-07-02 10:33:58,205 [prior] Evaluating prior at array([0.35612506, 0.44666542])
 2023-07-02 10:33:58,205 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,205 [model] Got input parameters: {'Omega_m': 0.3561250594681581, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44666541787912345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,205 [classy] Got parameters {'Omega_m': 0.3561250594681581, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,205 [classy] Computing new state
 2023-07-02 10:33:58,205 [classy] Setting parameters: {'Omega_m': 0.3561250594681581, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.31221153355764}
 2023-07-02 10:33:58,249 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105425
 2023-07-02 10:33:58,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44666541787912345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,251 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,271 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.19044
 2023-07-02 10:33:58,271 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,271 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.4969898077929139}
 2023-07-02 10:33:58,271 [prior] Evaluating prior at array([0.34512786, 0.49698981])
 2023-07-02 10:33:58,271 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,271 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4969898077929139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,271 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,271 [classy] Re-using computed results
 2023-07-02 10:33:58,272 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
 2023-07-02 10:33:58,272 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,272 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4969898077929139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,272 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,291 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.12811
 2023-07-02 10:33:58,291 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,291 [model] Posterior to be computed for parameters {'Omega_m': 0.3490782393808513, 'b1': 0.4566303257138088}
 2023-07-02 10:33:58,291 [prior] Evaluating prior at array([0.34907824, 0.45663033])
 2023-07-02 10:33:58,292 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,292 [model] Got input parameters: {'Omega_m': 0.3490782393808513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4566303257138088, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,292 [classy] Got parameters {'Omega_m': 0.3490782393808513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,292 [classy] Computing new state
 2023-07-02 10:33:58,292 [classy] Setting parameters: {'Omega_m': 0.3490782393808513, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0724723665007}
 2023-07-02 10:33:58,335 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,337 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0754014
 2023-07-02 10:33:58,337 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4566303257138088, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,337 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.56747
 2023-07-02 10:33:58,357 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,357 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.44654270464853485}
 2023-07-02 10:33:58,357 [prior] Evaluating prior at array([0.34512786, 0.4465427 ])
 2023-07-02 10:33:58,357 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,357 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44654270464853485, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,357 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,357 [classy] Re-using computed results
 2023-07-02 10:33:58,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
 2023-07-02 10:33:58,357 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,357 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44654270464853485, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,357 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,377 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.51246
 2023-07-02 10:33:58,377 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,377 [mcmc] New sample, #347:
   Omega_m:0.3451279, b1:0.4622166
 2023-07-02 10:33:58,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3238976969857947, 'b1': 0.4765642743377901}
 2023-07-02 10:33:58,377 [prior] Evaluating prior at array([0.3238977 , 0.47656427])
 2023-07-02 10:33:58,378 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,378 [model] Got input parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4765642743377901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,378 [classy] Got parameters {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,378 [classy] Computing new state
 2023-07-02 10:33:58,378 [classy] Setting parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90861184879094}
 2023-07-02 10:33:58,422 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,423 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00796908
 2023-07-02 10:33:58,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4765642743377901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,424 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,443 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35853
 2023-07-02 10:33:58,443 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,443 [mcmc] New sample, #348:
   Omega_m:0.3451279, b1:0.4465427
 2023-07-02 10:33:58,443 [model] Posterior to be computed for parameters {'Omega_m': 0.3238976969857947, 'b1': 0.4871919984567674}
 2023-07-02 10:33:58,443 [prior] Evaluating prior at array([0.3238977, 0.487192 ])
 2023-07-02 10:33:58,443 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,443 [model] Got input parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4871919984567674, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,443 [classy] Got parameters {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,443 [classy] Re-using computed results
 2023-07-02 10:33:58,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90861184879094}
 2023-07-02 10:33:58,443 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4871919984567674, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,444 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,463 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49165
 2023-07-02 10:33:58,463 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,463 [mcmc] New sample, #349:
   Omega_m:0.3238977, b1:0.4765643
 2023-07-02 10:33:58,463 [model] Posterior to be computed for parameters {'Omega_m': 0.3536620607430115, 'b1': 0.44510221357167157}
 2023-07-02 10:33:58,463 [prior] Evaluating prior at array([0.35366206, 0.44510221])
 2023-07-02 10:33:58,463 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,463 [model] Got input parameters: {'Omega_m': 0.3536620607430115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44510221357167157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,463 [classy] Got parameters {'Omega_m': 0.3536620607430115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,464 [classy] Computing new state
 2023-07-02 10:33:58,464 [classy] Setting parameters: {'Omega_m': 0.3536620607430115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57635805199703}
 2023-07-02 10:33:58,507 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.094415
 2023-07-02 10:33:58,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44510221357167157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,529 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.73921
 2023-07-02 10:33:58,529 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,529 [model] Posterior to be computed for parameters {'Omega_m': 0.3238976969857947, 'b1': 0.5181795097611104}
 2023-07-02 10:33:58,529 [prior] Evaluating prior at array([0.3238977 , 0.51817951])
 2023-07-02 10:33:58,529 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,529 [model] Got input parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5181795097611104, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,529 [classy] Got parameters {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,529 [classy] Re-using computed results
 2023-07-02 10:33:58,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90861184879094}
 2023-07-02 10:33:58,529 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,529 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5181795097611104, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,529 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,548 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.730424
 2023-07-02 10:33:58,548 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,548 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4832373095330477}
 2023-07-02 10:33:58,548 [prior] Evaluating prior at array([0.32669431, 0.48323731])
 2023-07-02 10:33:58,549 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,549 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4832373095330477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,549 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,549 [classy] Computing new state
 2023-07-02 10:33:58,549 [classy] Setting parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,593 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
 2023-07-02 10:33:58,593 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,594 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0121603
 2023-07-02 10:33:58,595 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4832373095330477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,595 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,614 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17213
 2023-07-02 10:33:58,614 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,614 [mcmc] New sample, #350:
   Omega_m:0.3238977, b1:0.487192
 2023-07-02 10:33:58,615 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.5035907335598834}
 2023-07-02 10:33:58,615 [prior] Evaluating prior at array([0.32669431, 0.50359073])
 2023-07-02 10:33:58,615 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,615 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5035907335598834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,615 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,615 [classy] Re-using computed results
 2023-07-02 10:33:58,615 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
 2023-07-02 10:33:58,615 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,615 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5035907335598834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,615 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,634 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.548058
 2023-07-02 10:33:58,634 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,634 [model] Posterior to be computed for parameters {'Omega_m': 0.3557945584978752, 'b1': 0.4420866486329316}
 2023-07-02 10:33:58,634 [prior] Evaluating prior at array([0.35579456, 0.44208665])
 2023-07-02 10:33:58,635 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,635 [model] Got input parameters: {'Omega_m': 0.3557945584978752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4420866486329316, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,635 [classy] Got parameters {'Omega_m': 0.3557945584978752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,635 [classy] Computing new state
 2023-07-02 10:33:58,635 [classy] Setting parameters: {'Omega_m': 0.3557945584978752, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.3475597847608}
 2023-07-02 10:33:58,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103916
 2023-07-02 10:33:58,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4420866486329316, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,681 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.54204
 2023-07-02 10:33:58,700 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,700 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.538146183363322}
 2023-07-02 10:33:58,700 [prior] Evaluating prior at array([0.32669431, 0.53814618])
 2023-07-02 10:33:58,700 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,701 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.538146183363322, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,701 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,701 [classy] Re-using computed results
 2023-07-02 10:33:58,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
 2023-07-02 10:33:58,701 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.538146183363322, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,720 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.84763
 2023-07-02 10:33:58,720 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,720 [model] Posterior to be computed for parameters {'Omega_m': 0.2904527361570845, 'b1': 0.5344865154252195}
 2023-07-02 10:33:58,720 [prior] Evaluating prior at array([0.29045274, 0.53448652])
 2023-07-02 10:33:58,721 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,721 [model] Got input parameters: {'Omega_m': 0.2904527361570845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5344865154252195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,721 [classy] Got parameters {'Omega_m': 0.2904527361570845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,721 [classy] Computing new state
 2023-07-02 10:33:58,721 [classy] Setting parameters: {'Omega_m': 0.2904527361570845, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.99720687881018}
 2023-07-02 10:33:58,765 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0316807
 2023-07-02 10:33:58,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5344865154252195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.17263
 2023-07-02 10:33:58,786 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,786 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4735103346262174}
 2023-07-02 10:33:58,786 [prior] Evaluating prior at array([0.32669431, 0.47351033])
 2023-07-02 10:33:58,786 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,786 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4735103346262174, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,786 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,786 [classy] Re-using computed results
 2023-07-02 10:33:58,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
 2023-07-02 10:33:58,786 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4735103346262174, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,787 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,806 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13238
 2023-07-02 10:33:58,806 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,806 [mcmc] New sample, #351:
   Omega_m:0.3266943, b1:0.4832373
 2023-07-02 10:33:58,806 [model] Posterior to be computed for parameters {'Omega_m': 0.3628205529809486, 'b1': 0.4224242153770302}
 2023-07-02 10:33:58,806 [prior] Evaluating prior at array([0.36282055, 0.42242422])
 2023-07-02 10:33:58,806 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,806 [model] Got input parameters: {'Omega_m': 0.3628205529809486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4224242153770302, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,806 [classy] Got parameters {'Omega_m': 0.3628205529809486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,806 [classy] Computing new state
 2023-07-02 10:33:58,806 [classy] Setting parameters: {'Omega_m': 0.3628205529809486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,850 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.60260062588577}
 2023-07-02 10:33:58,850 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,852 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138067
 2023-07-02 10:33:58,852 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4224242153770302, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,852 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,871 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.6798
 2023-07-02 10:33:58,872 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,872 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4772316055619289}
 2023-07-02 10:33:58,872 [prior] Evaluating prior at array([0.32669431, 0.47723161])
 2023-07-02 10:33:58,872 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,872 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4772316055619289, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,872 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,872 [classy] Re-using computed results
 2023-07-02 10:33:58,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
 2023-07-02 10:33:58,872 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,872 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4772316055619289, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,872 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,892 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20827
 2023-07-02 10:33:58,892 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,892 [mcmc] New sample, #352:
   Omega_m:0.3266943, b1:0.4735103
 2023-07-02 10:33:58,892 [model] Posterior to be computed for parameters {'Omega_m': 0.35193552570279996, 'b1': 0.44153800269047183}
 2023-07-02 10:33:58,892 [prior] Evaluating prior at array([0.35193553, 0.441538  ])
 2023-07-02 10:33:58,892 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,892 [model] Got input parameters: {'Omega_m': 0.35193552570279996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44153800269047183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,892 [classy] Got parameters {'Omega_m': 0.35193552570279996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,892 [classy] Computing new state
 2023-07-02 10:33:58,892 [classy] Setting parameters: {'Omega_m': 0.35193552570279996, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:58,937 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.76252773701663}
 2023-07-02 10:33:58,937 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:58,939 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0870256
 2023-07-02 10:33:58,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44153800269047183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,939 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.74285
 2023-07-02 10:33:58,958 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,958 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4479765827375237}
 2023-07-02 10:33:58,958 [prior] Evaluating prior at array([0.32669431, 0.44797658])
 2023-07-02 10:33:58,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,958 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4479765827375237, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,958 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,958 [classy] Re-using computed results
 2023-07-02 10:33:58,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
 2023-07-02 10:33:58,959 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:58,959 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4479765827375237, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,959 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:58,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.345188
 2023-07-02 10:33:58,978 [model] Computed derived parameters: {}
 2023-07-02 10:33:58,978 [model] Posterior to be computed for parameters {'Omega_m': 0.3370104943604416, 'b1': 0.4626434885569676}
 2023-07-02 10:33:58,979 [prior] Evaluating prior at array([0.33701049, 0.46264349])
 2023-07-02 10:33:58,979 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:58,979 [model] Got input parameters: {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4626434885569676, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:58,979 [classy] Got parameters {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:58,979 [classy] Computing new state
 2023-07-02 10:33:58,979 [classy] Setting parameters: {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.40768086881573}
 2023-07-02 10:33:59,023 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0349534
 2023-07-02 10:33:59,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4626434885569676, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,025 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,044 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.473463
 2023-07-02 10:33:59,044 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,044 [mcmc] New sample, #353:
   Omega_m:0.3266943, b1:0.4772316
 2023-07-02 10:33:59,044 [model] Posterior to be computed for parameters {'Omega_m': 0.3370104943604416, 'b1': 0.42668022661685284}
 2023-07-02 10:33:59,044 [prior] Evaluating prior at array([0.33701049, 0.42668023])
 2023-07-02 10:33:59,044 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,044 [model] Got input parameters: {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42668022661685284, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,044 [classy] Got parameters {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,044 [classy] Re-using computed results
 2023-07-02 10:33:59,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.40768086881573}
 2023-07-02 10:33:59,044 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42668022661685284, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,044 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,063 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.54675
 2023-07-02 10:33:59,064 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,064 [model] Posterior to be computed for parameters {'Omega_m': 0.30641205370319907, 'b1': 0.5059127415330351}
 2023-07-02 10:33:59,064 [prior] Evaluating prior at array([0.30641205, 0.50591274])
 2023-07-02 10:33:59,064 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,064 [model] Got input parameters: {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5059127415330351, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,064 [classy] Got parameters {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,064 [classy] Computing new state
 2023-07-02 10:33:59,064 [classy] Setting parameters: {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,108 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.9971166485374}
 2023-07-02 10:33:59,108 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,110 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00249794
 2023-07-02 10:33:59,110 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5059127415330351, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,110 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,132 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21072
 2023-07-02 10:33:59,132 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,132 [mcmc] New sample, #354:
   Omega_m:0.3370105, b1:0.4626435
 2023-07-02 10:33:59,132 [model] Posterior to be computed for parameters {'Omega_m': 0.30641205370319907, 'b1': 0.5162927549867663}
 2023-07-02 10:33:59,132 [prior] Evaluating prior at array([0.30641205, 0.51629275])
 2023-07-02 10:33:59,133 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,133 [model] Got input parameters: {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5162927549867663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,133 [classy] Got parameters {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,133 [classy] Re-using computed results
 2023-07-02 10:33:59,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.9971166485374}
 2023-07-02 10:33:59,133 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5162927549867663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,133 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,153 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4767
 2023-07-02 10:33:59,153 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,153 [mcmc] New sample, #355:
   Omega_m:0.3064121, b1:0.5059127
 2023-07-02 10:33:59,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3029997865972861, 'b1': 0.5211180416829599}
 2023-07-02 10:33:59,153 [prior] Evaluating prior at array([0.30299979, 0.52111804])
 2023-07-02 10:33:59,153 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,153 [model] Got input parameters: {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5211180416829599, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,153 [classy] Got parameters {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,153 [classy] Computing new state
 2023-07-02 10:33:59,153 [classy] Setting parameters: {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.41693983705898}
 2023-07-02 10:33:59,197 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,199 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00585108
 2023-07-02 10:33:59,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5211180416829599, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,199 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,219 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.04422
 2023-07-02 10:33:59,219 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,219 [mcmc] New sample, #356:
   Omega_m:0.3064121, b1:0.5162928
 2023-07-02 10:33:59,219 [model] Posterior to be computed for parameters {'Omega_m': 0.3029997865972861, 'b1': 0.6092070961755289}
 2023-07-02 10:33:59,219 [prior] Evaluating prior at array([0.30299979, 0.6092071 ])
 2023-07-02 10:33:59,219 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,219 [model] Got input parameters: {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6092070961755289, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,219 [classy] Got parameters {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,219 [classy] Re-using computed results
 2023-07-02 10:33:59,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.41693983705898}
 2023-07-02 10:33:59,220 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,220 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6092070961755289, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,220 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,239 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.95
 2023-07-02 10:33:59,239 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,239 [model] Posterior to be computed for parameters {'Omega_m': 0.3013225429407779, 'b1': 0.5234898318303373}
 2023-07-02 10:33:59,239 [prior] Evaluating prior at array([0.30132254, 0.52348983])
 2023-07-02 10:33:59,240 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,240 [model] Got input parameters: {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5234898318303373, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,240 [classy] Got parameters {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,240 [classy] Computing new state
 2023-07-02 10:33:59,240 [classy] Setting parameters: {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62481840707625}
 2023-07-02 10:33:59,284 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,286 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00805874
 2023-07-02 10:33:59,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5234898318303373, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,286 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,305 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.77263
 2023-07-02 10:33:59,305 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,305 [mcmc] New sample, #357:
   Omega_m:0.3029998, b1:0.521118
 2023-07-02 10:33:59,305 [model] Posterior to be computed for parameters {'Omega_m': 0.3013225429407779, 'b1': 0.5483551461464687}
 2023-07-02 10:33:59,305 [prior] Evaluating prior at array([0.30132254, 0.54835515])
 2023-07-02 10:33:59,306 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,306 [model] Got input parameters: {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483551461464687, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,306 [classy] Got parameters {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,306 [classy] Re-using computed results
 2023-07-02 10:33:59,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62481840707625}
 2023-07-02 10:33:59,306 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483551461464687, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,306 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,326 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.319601
 2023-07-02 10:33:59,326 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,326 [model] Posterior to be computed for parameters {'Omega_m': 0.3007412339943405, 'b1': 0.5243118607743089}
 2023-07-02 10:33:59,326 [prior] Evaluating prior at array([0.30074123, 0.52431186])
 2023-07-02 10:33:59,326 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,326 [model] Got input parameters: {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5243118607743089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,326 [classy] Got parameters {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,326 [classy] Computing new state
 2023-07-02 10:33:59,326 [classy] Setting parameters: {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,370 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.69710255486774}
 2023-07-02 10:33:59,370 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,372 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00891116
 2023-07-02 10:33:59,372 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5243118607743089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,372 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,392 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66924
 2023-07-02 10:33:59,392 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,392 [mcmc] New sample, #358:
   Omega_m:0.3013225, b1:0.5234898
 2023-07-02 10:33:59,392 [model] Posterior to be computed for parameters {'Omega_m': 0.3007412339943405, 'b1': 0.5193881621776889}
 2023-07-02 10:33:59,392 [prior] Evaluating prior at array([0.30074123, 0.51938816])
 2023-07-02 10:33:59,393 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,393 [model] Got input parameters: {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5193881621776889, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,393 [classy] Got parameters {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,393 [classy] Re-using computed results
 2023-07-02 10:33:59,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.69710255486774}
 2023-07-02 10:33:59,393 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5193881621776889, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,393 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,412 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.55518
 2023-07-02 10:33:59,412 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,412 [mcmc] New sample, #359:
   Omega_m:0.3007412, b1:0.5243119
 2023-07-02 10:33:59,412 [model] Posterior to be computed for parameters {'Omega_m': 0.2999288016564884, 'b1': 0.5205370226946755}
 2023-07-02 10:33:59,412 [prior] Evaluating prior at array([0.2999288 , 0.52053702])
 2023-07-02 10:33:59,412 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,413 [model] Got input parameters: {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205370226946755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,413 [classy] Got parameters {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,413 [classy] Computing new state
 2023-07-02 10:33:59,413 [classy] Setting parameters: {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,457 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.79834225312166}
 2023-07-02 10:33:59,457 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,458 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0101786
 2023-07-02 10:33:59,459 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205370226946755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,459 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3943
 2023-07-02 10:33:59,479 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,479 [mcmc] New sample, #360:
   Omega_m:0.3007412, b1:0.5193882
 2023-07-02 10:33:59,479 [model] Posterior to be computed for parameters {'Omega_m': 0.2999288016564884, 'b1': 0.47472049413044237}
 2023-07-02 10:33:59,479 [prior] Evaluating prior at array([0.2999288 , 0.47472049])
 2023-07-02 10:33:59,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,480 [model] Got input parameters: {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47472049413044237, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,480 [classy] Got parameters {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,480 [classy] Re-using computed results
 2023-07-02 10:33:59,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.79834225312166}
 2023-07-02 10:33:59,480 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47472049413044237, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,499 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.5402
 2023-07-02 10:33:59,499 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,500 [model] Posterior to be computed for parameters {'Omega_m': 0.3047433114156396, 'b1': 0.5137288247522372}
 2023-07-02 10:33:59,500 [prior] Evaluating prior at array([0.30474331, 0.51372882])
 2023-07-02 10:33:59,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,500 [model] Got input parameters: {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5137288247522372, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,500 [classy] Got parameters {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,500 [classy] Computing new state
 2023-07-02 10:33:59,500 [classy] Setting parameters: {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2019121948667}
 2023-07-02 10:33:59,544 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0039487
 2023-07-02 10:33:59,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5137288247522372, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,546 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,566 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2123
 2023-07-02 10:33:59,566 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,566 [mcmc] New sample, #361:
   Omega_m:0.2999288, b1:0.520537
 2023-07-02 10:33:59,566 [model] Posterior to be computed for parameters {'Omega_m': 0.3047433114156396, 'b1': 0.5309169448072816}
 2023-07-02 10:33:59,566 [prior] Evaluating prior at array([0.30474331, 0.53091694])
 2023-07-02 10:33:59,566 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,566 [model] Got input parameters: {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5309169448072816, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,566 [classy] Got parameters {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,566 [classy] Re-using computed results
 2023-07-02 10:33:59,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2019121948667}
 2023-07-02 10:33:59,566 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5309169448072816, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,566 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90017
 2023-07-02 10:33:59,587 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,587 [mcmc] New sample, #362:
   Omega_m:0.3047433, b1:0.5137288
 2023-07-02 10:33:59,587 [model] Posterior to be computed for parameters {'Omega_m': 0.306334387878479, 'b1': 0.5286670036829594}
 2023-07-02 10:33:59,587 [prior] Evaluating prior at array([0.30633439, 0.528667  ])
 2023-07-02 10:33:59,587 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,587 [model] Got input parameters: {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5286670036829594, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,587 [classy] Got parameters {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,587 [classy] Computing new state
 2023-07-02 10:33:59,587 [classy] Setting parameters: {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00662391847243}
 2023-07-02 10:33:59,632 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,633 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00255747
 2023-07-02 10:33:59,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5286670036829594, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,634 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,653 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.04037
 2023-07-02 10:33:59,653 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,653 [mcmc] New sample, #363:
   Omega_m:0.3047433, b1:0.5309169
 2023-07-02 10:33:59,653 [model] Posterior to be computed for parameters {'Omega_m': 0.306334387878479, 'b1': 0.5380079157217817}
 2023-07-02 10:33:59,653 [prior] Evaluating prior at array([0.30633439, 0.53800792])
 2023-07-02 10:33:59,653 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,653 [model] Got input parameters: {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5380079157217817, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,653 [classy] Got parameters {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,653 [classy] Re-using computed results
 2023-07-02 10:33:59,653 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00662391847243}
 2023-07-02 10:33:59,653 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5380079157217817, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,653 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,672 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15584
 2023-07-02 10:33:59,673 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,673 [mcmc] New sample, #364:
   Omega_m:0.3063344, b1:0.528667
 2023-07-02 10:33:59,673 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5327083020356528}
 2023-07-02 10:33:59,673 [prior] Evaluating prior at array([0.31008208, 0.5327083 ])
 2023-07-02 10:33:59,673 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,673 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5327083020356528, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,673 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,673 [classy] Computing new state
 2023-07-02 10:33:59,673 [classy] Setting parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,717 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
 2023-07-02 10:33:59,718 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,719 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000558299
 2023-07-02 10:33:59,719 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5327083020356528, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,719 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,740 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.269
 2023-07-02 10:33:59,740 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,740 [mcmc] New sample, #365:
   Omega_m:0.3063344, b1:0.5380079
 2023-07-02 10:33:59,740 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5610362963643449}
 2023-07-02 10:33:59,740 [prior] Evaluating prior at array([0.31008208, 0.5610363 ])
 2023-07-02 10:33:59,740 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,740 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5610362963643449, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,740 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,740 [classy] Re-using computed results
 2023-07-02 10:33:59,740 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
 2023-07-02 10:33:59,740 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5610362963643449, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,740 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,759 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.79005
 2023-07-02 10:33:59,760 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,760 [model] Posterior to be computed for parameters {'Omega_m': 0.297930075429868, 'b1': 0.5498924534177505}
 2023-07-02 10:33:59,760 [prior] Evaluating prior at array([0.29793008, 0.54989245])
 2023-07-02 10:33:59,760 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,760 [model] Got input parameters: {'Omega_m': 0.297930075429868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5498924534177505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,760 [classy] Got parameters {'Omega_m': 0.297930075429868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,760 [classy] Computing new state
 2023-07-02 10:33:59,760 [classy] Setting parameters: {'Omega_m': 0.297930075429868, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.04844272578305}
 2023-07-02 10:33:59,805 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0136769
 2023-07-02 10:33:59,806 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5498924534177505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,806 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,826 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.196817
 2023-07-02 10:33:59,826 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,826 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5184212274663356}
 2023-07-02 10:33:59,826 [prior] Evaluating prior at array([0.31008208, 0.51842123])
 2023-07-02 10:33:59,826 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,826 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5184212274663356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,826 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,827 [classy] Re-using computed results
 2023-07-02 10:33:59,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
 2023-07-02 10:33:59,827 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5184212274663356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,827 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,847 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55041
 2023-07-02 10:33:59,847 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,847 [mcmc] New sample, #366:
   Omega_m:0.3100821, b1:0.5327083
 2023-07-02 10:33:59,847 [model] Posterior to be computed for parameters {'Omega_m': 0.304065971352212, 'b1': 0.5269286088171513}
 2023-07-02 10:33:59,847 [prior] Evaluating prior at array([0.30406597, 0.52692861])
 2023-07-02 10:33:59,847 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,847 [model] Got input parameters: {'Omega_m': 0.304065971352212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5269286088171513, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,847 [classy] Got parameters {'Omega_m': 0.304065971352212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,847 [classy] Computing new state
 2023-07-02 10:33:59,847 [classy] Setting parameters: {'Omega_m': 0.304065971352212, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,892 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28531780081414}
 2023-07-02 10:33:59,892 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,894 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00464052
 2023-07-02 10:33:59,894 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5269286088171513, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,894 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,913 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07602
 2023-07-02 10:33:59,913 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,914 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5312831796253852}
 2023-07-02 10:33:59,914 [prior] Evaluating prior at array([0.31008208, 0.53128318])
 2023-07-02 10:33:59,914 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,914 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5312831796253852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,914 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,914 [classy] Re-using computed results
 2023-07-02 10:33:59,914 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
 2023-07-02 10:33:59,914 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:33:59,914 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5312831796253852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,914 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:33:59,934 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44872
 2023-07-02 10:33:59,934 [model] Computed derived parameters: {}
 2023-07-02 10:33:59,934 [model] Posterior to be computed for parameters {'Omega_m': 0.28140960850445523, 'b1': 0.5589669700708685}
 2023-07-02 10:33:59,934 [prior] Evaluating prior at array([0.28140961, 0.55896697])
 2023-07-02 10:33:59,935 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:33:59,935 [model] Got input parameters: {'Omega_m': 0.28140960850445523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5589669700708685, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,935 [classy] Got parameters {'Omega_m': 0.28140960850445523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:33:59,935 [classy] Computing new state
 2023-07-02 10:33:59,935 [classy] Setting parameters: {'Omega_m': 0.28140960850445523, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:33:59,979 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.17334913713125}
 2023-07-02 10:33:59,979 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:33:59,981 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0643291
 2023-07-02 10:33:59,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5589669700708685, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:33:59,981 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,000 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.47915
 2023-07-02 10:34:00,000 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,000 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5015174155101206}
 2023-07-02 10:34:00,000 [prior] Evaluating prior at array([0.31008208, 0.50151742])
 2023-07-02 10:34:00,001 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,001 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015174155101206, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,001 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,001 [classy] Re-using computed results
 2023-07-02 10:34:00,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
 2023-07-02 10:34:00,001 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,001 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015174155101206, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,001 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,020 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61638
 2023-07-02 10:34:00,020 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,020 [mcmc] New sample, #367:
   Omega_m:0.3100821, b1:0.5184212
 2023-07-02 10:34:00,020 [model] Posterior to be computed for parameters {'Omega_m': 0.30546450836965516, 'b1': 0.5080471257540324}
 2023-07-02 10:34:00,020 [prior] Evaluating prior at array([0.30546451, 0.50804713])
 2023-07-02 10:34:00,021 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,021 [model] Got input parameters: {'Omega_m': 0.30546450836965516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080471257540324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,021 [classy] Got parameters {'Omega_m': 0.30546450836965516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,021 [classy] Computing new state
 2023-07-02 10:34:00,021 [classy] Setting parameters: {'Omega_m': 0.30546450836965516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11328191181138}
 2023-07-02 10:34:00,065 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,067 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00327756
 2023-07-02 10:34:00,067 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080471257540324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,067 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,088 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12786
 2023-07-02 10:34:00,088 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,088 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.449894631677556}
 2023-07-02 10:34:00,088 [prior] Evaluating prior at array([0.31008208, 0.44989463])
 2023-07-02 10:34:00,088 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,088 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.449894631677556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,089 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,089 [classy] Re-using computed results
 2023-07-02 10:34:00,089 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
 2023-07-02 10:34:00,089 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.449894631677556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,089 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,109 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.13449
 2023-07-02 10:34:00,109 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,109 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.46518990205618194}
 2023-07-02 10:34:00,109 [prior] Evaluating prior at array([0.33577158, 0.4651899 ])
 2023-07-02 10:34:00,109 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,109 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46518990205618194, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,109 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,109 [classy] Computing new state
 2023-07-02 10:34:00,109 [classy] Setting parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
 2023-07-02 10:34:00,158 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0316237
 2023-07-02 10:34:00,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46518990205618194, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,160 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,179 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.727329
 2023-07-02 10:34:00,179 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,179 [mcmc] New sample, #368:
   Omega_m:0.3100821, b1:0.5015174
 2023-07-02 10:34:00,179 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.46374019534941474}
 2023-07-02 10:34:00,179 [prior] Evaluating prior at array([0.33577158, 0.4637402 ])
 2023-07-02 10:34:00,180 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,180 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46374019534941474, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,180 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,180 [classy] Re-using computed results
 2023-07-02 10:34:00,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
 2023-07-02 10:34:00,180 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46374019534941474, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,180 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,200 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.741294
 2023-07-02 10:34:00,200 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,200 [mcmc] New sample, #369:
   Omega_m:0.3357716, b1:0.4651899
 2023-07-02 10:34:00,200 [model] Posterior to be computed for parameters {'Omega_m': 0.3484646051337628, 'b1': 0.4457909849637962}
 2023-07-02 10:34:00,201 [prior] Evaluating prior at array([0.34846461, 0.44579098])
 2023-07-02 10:34:00,201 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,201 [model] Got input parameters: {'Omega_m': 0.3484646051337628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4457909849637962, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,201 [classy] Got parameters {'Omega_m': 0.3484646051337628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,201 [classy] Computing new state
 2023-07-02 10:34:00,201 [classy] Setting parameters: {'Omega_m': 0.3484646051337628, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,247 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.13933695823752}
 2023-07-02 10:34:00,247 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0730047
 2023-07-02 10:34:00,249 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4457909849637962, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,249 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.5764
 2023-07-02 10:34:00,270 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,270 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.4552282237432503}
 2023-07-02 10:34:00,270 [prior] Evaluating prior at array([0.33577158, 0.45522822])
 2023-07-02 10:34:00,270 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,270 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4552282237432503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,270 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,270 [classy] Re-using computed results
 2023-07-02 10:34:00,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
 2023-07-02 10:34:00,270 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,270 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4552282237432503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,270 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,291 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.591418
 2023-07-02 10:34:00,291 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,291 [mcmc] New sample, #370:
   Omega_m:0.3357716, b1:0.4637402
 2023-07-02 10:34:00,291 [model] Posterior to be computed for parameters {'Omega_m': 0.34097483181638716, 'b1': 0.4478703013266224}
 2023-07-02 10:34:00,291 [prior] Evaluating prior at array([0.34097483, 0.4478703 ])
 2023-07-02 10:34:00,292 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,292 [model] Got input parameters: {'Omega_m': 0.34097483181638716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4478703013266224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,292 [classy] Got parameters {'Omega_m': 0.34097483181638716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,292 [classy] Computing new state
 2023-07-02 10:34:00,292 [classy] Setting parameters: {'Omega_m': 0.34097483181638716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9643061477438}
 2023-07-02 10:34:00,336 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.046658
 2023-07-02 10:34:00,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4478703013266224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,338 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.505656
 2023-07-02 10:34:00,357 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,357 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.4686038888114684}
 2023-07-02 10:34:00,357 [prior] Evaluating prior at array([0.33577158, 0.46860389])
 2023-07-02 10:34:00,358 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,358 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4686038888114684, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,358 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,358 [classy] Re-using computed results
 2023-07-02 10:34:00,358 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
 2023-07-02 10:34:00,358 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,358 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4686038888114684, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,358 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,377 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.648418
 2023-07-02 10:34:00,377 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,377 [mcmc] New sample, #371:
   Omega_m:0.3357716, b1:0.4552282
 2023-07-02 10:34:00,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3392266129036548, 'b1': 0.46371812264750434}
 2023-07-02 10:34:00,377 [prior] Evaluating prior at array([0.33922661, 0.46371812])
 2023-07-02 10:34:00,377 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,377 [model] Got input parameters: {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46371812264750434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,377 [classy] Got parameters {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,378 [classy] Computing new state
 2023-07-02 10:34:00,378 [classy] Setting parameters: {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15924799238002}
 2023-07-02 10:34:00,422 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,424 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0413009
 2023-07-02 10:34:00,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46371812264750434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,424 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,444 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.152064
 2023-07-02 10:34:00,444 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,444 [mcmc] New sample, #372:
   Omega_m:0.3357716, b1:0.4686039
 2023-07-02 10:34:00,444 [model] Posterior to be computed for parameters {'Omega_m': 0.3392266129036548, 'b1': 0.46399124076873466}
 2023-07-02 10:34:00,444 [prior] Evaluating prior at array([0.33922661, 0.46399124])
 2023-07-02 10:34:00,445 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,445 [model] Got input parameters: {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46399124076873466, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,445 [classy] Got parameters {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,445 [classy] Re-using computed results
 2023-07-02 10:34:00,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15924799238002}
 2023-07-02 10:34:00,445 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46399124076873466, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,445 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,464 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.16328
 2023-07-02 10:34:00,464 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,464 [mcmc] New sample, #373:
   Omega_m:0.3392266, b1:0.4637181
 2023-07-02 10:34:00,464 [model] Posterior to be computed for parameters {'Omega_m': 0.3392414315069503, 'b1': 0.46397028578276245}
 2023-07-02 10:34:00,464 [prior] Evaluating prior at array([0.33924143, 0.46397029])
 2023-07-02 10:34:00,464 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,464 [model] Got input parameters: {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46397028578276245, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,464 [classy] Got parameters {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,464 [classy] Computing new state
 2023-07-02 10:34:00,464 [classy] Setting parameters: {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15759263528454}
 2023-07-02 10:34:00,509 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.041345
 2023-07-02 10:34:00,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46397028578276245, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,511 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,530 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.166957
 2023-07-02 10:34:00,530 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,530 [mcmc] New sample, #374:
   Omega_m:0.3392266, b1:0.4639912
 2023-07-02 10:34:00,530 [model] Posterior to be computed for parameters {'Omega_m': 0.3392414315069503, 'b1': 0.37307515200024777}
 2023-07-02 10:34:00,531 [prior] Evaluating prior at array([0.33924143, 0.37307515])
 2023-07-02 10:34:00,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,531 [model] Got input parameters: {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37307515200024777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,531 [classy] Got parameters {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,531 [classy] Re-using computed results
 2023-07-02 10:34:00,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15759263528454}
 2023-07-02 10:34:00,531 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,531 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37307515200024777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,531 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.5786
 2023-07-02 10:34:00,551 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,551 [model] Posterior to be computed for parameters {'Omega_m': 0.3319842465738009, 'b1': 0.4742326705324972}
 2023-07-02 10:34:00,551 [prior] Evaluating prior at array([0.33198425, 0.47423267])
 2023-07-02 10:34:00,552 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,552 [model] Got input parameters: {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4742326705324972, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,552 [classy] Got parameters {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,552 [classy] Computing new state
 2023-07-02 10:34:00,552 [classy] Setting parameters: {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.97664988466943}
 2023-07-02 10:34:00,596 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0224353
 2023-07-02 10:34:00,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4742326705324972, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,598 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,617 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39
 2023-07-02 10:34:00,617 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,617 [mcmc] New sample, #375:
   Omega_m:0.3392414, b1:0.4639703
 2023-07-02 10:34:00,617 [model] Posterior to be computed for parameters {'Omega_m': 0.3319842465738009, 'b1': 0.47016964205098094}
 2023-07-02 10:34:00,617 [prior] Evaluating prior at array([0.33198425, 0.47016964])
 2023-07-02 10:34:00,617 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,617 [model] Got input parameters: {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47016964205098094, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,617 [classy] Got parameters {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,618 [classy] Re-using computed results
 2023-07-02 10:34:00,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.97664988466943}
 2023-07-02 10:34:00,618 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,618 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47016964205098094, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,618 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,637 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.449
 2023-07-02 10:34:00,637 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,637 [mcmc] New sample, #376:
   Omega_m:0.3319842, b1:0.4742327
 2023-07-02 10:34:00,637 [model] Posterior to be computed for parameters {'Omega_m': 0.33016587977308526, 'b1': 0.4727409944275546}
 2023-07-02 10:34:00,637 [prior] Evaluating prior at array([0.33016588, 0.47274099])
 2023-07-02 10:34:00,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,638 [model] Got input parameters: {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4727409944275546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,638 [classy] Got parameters {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,638 [classy] Computing new state
 2023-07-02 10:34:00,638 [classy] Setting parameters: {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,682 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.18440148741675}
 2023-07-02 10:34:00,682 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185628
 2023-07-02 10:34:00,684 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4727409944275546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,684 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,704 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.74339
 2023-07-02 10:34:00,704 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,704 [mcmc] New sample, #377:
   Omega_m:0.3319842, b1:0.4701696
 2023-07-02 10:34:00,704 [model] Posterior to be computed for parameters {'Omega_m': 0.33016587977308526, 'b1': 0.4861989109628942}
 2023-07-02 10:34:00,704 [prior] Evaluating prior at array([0.33016588, 0.48619891])
 2023-07-02 10:34:00,704 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,704 [model] Got input parameters: {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4861989109628942, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,704 [classy] Got parameters {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,704 [classy] Re-using computed results
 2023-07-02 10:34:00,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.18440148741675}
 2023-07-02 10:34:00,704 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,704 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4861989109628942, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,704 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,723 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24987
 2023-07-02 10:34:00,723 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,724 [mcmc] New sample, #378:
   Omega_m:0.3301659, b1:0.472741
 2023-07-02 10:34:00,724 [model] Posterior to be computed for parameters {'Omega_m': 0.31822809996285656, 'b1': 0.5030801246288957}
 2023-07-02 10:34:00,724 [prior] Evaluating prior at array([0.3182281 , 0.50308012])
 2023-07-02 10:34:00,724 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,724 [model] Got input parameters: {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5030801246288957, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,724 [classy] Got parameters {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,724 [classy] Computing new state
 2023-07-02 10:34:00,724 [classy] Setting parameters: {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,768 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.57454846355145}
 2023-07-02 10:34:00,768 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,770 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00219698
 2023-07-02 10:34:00,770 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5030801246288957, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,770 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,790 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67421
 2023-07-02 10:34:00,790 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,790 [mcmc] New sample, #379:
   Omega_m:0.3301659, b1:0.4861989
 2023-07-02 10:34:00,791 [model] Posterior to be computed for parameters {'Omega_m': 0.31822809996285656, 'b1': 0.47963362413864974}
 2023-07-02 10:34:00,791 [prior] Evaluating prior at array([0.3182281 , 0.47963362])
 2023-07-02 10:34:00,791 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,791 [model] Got input parameters: {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47963362413864974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,791 [classy] Got parameters {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,791 [classy] Re-using computed results
 2023-07-02 10:34:00,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.57454846355145}
 2023-07-02 10:34:00,791 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,791 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47963362413864974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,791 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,811 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28769
 2023-07-02 10:34:00,811 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,811 [mcmc] New sample, #380:
   Omega_m:0.3182281, b1:0.5030801
 2023-07-02 10:34:00,811 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.491139626742398}
 2023-07-02 10:34:00,811 [prior] Evaluating prior at array([0.31009147, 0.49113963])
 2023-07-02 10:34:00,811 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,811 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.491139626742398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,811 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,811 [classy] Computing new state
 2023-07-02 10:34:00,811 [classy] Setting parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
 2023-07-02 10:34:00,856 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000555511
 2023-07-02 10:34:00,857 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.491139626742398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,858 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,877 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91203
 2023-07-02 10:34:00,877 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,877 [mcmc] New sample, #381:
   Omega_m:0.3182281, b1:0.4796336
 2023-07-02 10:34:00,877 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.44323128292284303}
 2023-07-02 10:34:00,877 [prior] Evaluating prior at array([0.31009147, 0.44323128])
 2023-07-02 10:34:00,877 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,877 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44323128292284303, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,877 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,877 [classy] Re-using computed results
 2023-07-02 10:34:00,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
 2023-07-02 10:34:00,877 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,877 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44323128292284303, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,877 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,898 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.16592
 2023-07-02 10:34:00,898 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,898 [model] Posterior to be computed for parameters {'Omega_m': 0.29298879356262336, 'b1': 0.5153245257046967}
 2023-07-02 10:34:00,898 [prior] Evaluating prior at array([0.29298879, 0.51532453])
 2023-07-02 10:34:00,898 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,898 [model] Got input parameters: {'Omega_m': 0.29298879356262336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5153245257046967, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,898 [classy] Got parameters {'Omega_m': 0.29298879356262336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,898 [classy] Computing new state
 2023-07-02 10:34:00,898 [classy] Setting parameters: {'Omega_m': 0.29298879356262336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:00,943 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.67306915815044}
 2023-07-02 10:34:00,943 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:00,945 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0246896
 2023-07-02 10:34:00,945 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5153245257046967, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,945 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,964 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.71918
 2023-07-02 10:34:00,964 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,964 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.5208796410411071}
 2023-07-02 10:34:00,964 [prior] Evaluating prior at array([0.31009147, 0.52087964])
 2023-07-02 10:34:00,964 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,964 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5208796410411071, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,964 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,964 [classy] Re-using computed results
 2023-07-02 10:34:00,964 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
 2023-07-02 10:34:00,965 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:00,965 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5208796410411071, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,965 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:00,983 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41089
 2023-07-02 10:34:00,984 [model] Computed derived parameters: {}
 2023-07-02 10:34:00,984 [mcmc] New sample, #382:
   Omega_m:0.3100915, b1:0.4911396
 2023-07-02 10:34:00,984 [model] Posterior to be computed for parameters {'Omega_m': 0.3256378573794381, 'b1': 0.49889550094856255}
 2023-07-02 10:34:00,984 [prior] Evaluating prior at array([0.32563786, 0.4988955 ])
 2023-07-02 10:34:00,984 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:00,984 [model] Got input parameters: {'Omega_m': 0.3256378573794381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49889550094856255, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:00,984 [classy] Got parameters {'Omega_m': 0.3256378573794381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:00,984 [classy] Computing new state
 2023-07-02 10:34:00,984 [classy] Setting parameters: {'Omega_m': 0.3256378573794381, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,028 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7063046580616}
 2023-07-02 10:34:01,028 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,029 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0104746
 2023-07-02 10:34:01,030 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49889550094856255, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,030 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,050 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45708
 2023-07-02 10:34:01,050 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,050 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.5859242913094588}
 2023-07-02 10:34:01,050 [prior] Evaluating prior at array([0.31009147, 0.58592429])
 2023-07-02 10:34:01,050 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,050 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5859242913094588, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,050 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,050 [classy] Re-using computed results
 2023-07-02 10:34:01,050 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
 2023-07-02 10:34:01,050 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,050 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5859242913094588, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,050 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,069 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.2342
 2023-07-02 10:34:01,069 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,070 [model] Posterior to be computed for parameters {'Omega_m': 0.3062966987295614, 'b1': 0.5262458321581266}
 2023-07-02 10:34:01,070 [prior] Evaluating prior at array([0.3062967 , 0.52624583])
 2023-07-02 10:34:01,070 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,070 [model] Got input parameters: {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5262458321581266, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,070 [classy] Got parameters {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,070 [classy] Computing new state
 2023-07-02 10:34:01,070 [classy] Setting parameters: {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01124039635167}
 2023-07-02 10:34:01,115 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,116 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00258666
 2023-07-02 10:34:01,116 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5262458321581266, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,117 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,138 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18989
 2023-07-02 10:34:01,138 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,139 [mcmc] New sample, #383:
   Omega_m:0.3100915, b1:0.5208796
 2023-07-02 10:34:01,139 [model] Posterior to be computed for parameters {'Omega_m': 0.3062966987295614, 'b1': 0.5681512142353196}
 2023-07-02 10:34:01,139 [prior] Evaluating prior at array([0.3062967 , 0.56815121])
 2023-07-02 10:34:01,139 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,139 [model] Got input parameters: {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5681512142353196, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,139 [classy] Got parameters {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,139 [classy] Re-using computed results
 2023-07-02 10:34:01,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01124039635167}
 2023-07-02 10:34:01,139 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5681512142353196, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,139 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,159 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.14401
 2023-07-02 10:34:01,160 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,160 [model] Posterior to be computed for parameters {'Omega_m': 0.32180664021827077, 'b1': 0.5043132248910918}
 2023-07-02 10:34:01,160 [prior] Evaluating prior at array([0.32180664, 0.50431322])
 2023-07-02 10:34:01,160 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,160 [model] Got input parameters: {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5043132248910918, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,160 [classy] Got parameters {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,160 [classy] Computing new state
 2023-07-02 10:34:01,160 [classy] Setting parameters: {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,204 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.15300475096248}
 2023-07-02 10:34:01,204 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,206 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00541032
 2023-07-02 10:34:01,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5043132248910918, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,226 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.95319
 2023-07-02 10:34:01,226 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,226 [mcmc] New sample, #384:
   Omega_m:0.3062967, b1:0.5262458
 2023-07-02 10:34:01,226 [model] Posterior to be computed for parameters {'Omega_m': 0.32180664021827077, 'b1': 0.5228490216839586}
 2023-07-02 10:34:01,226 [prior] Evaluating prior at array([0.32180664, 0.52284902])
 2023-07-02 10:34:01,226 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,226 [model] Got input parameters: {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5228490216839586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,226 [classy] Got parameters {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,226 [classy] Re-using computed results
 2023-07-02 10:34:01,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.15300475096248}
 2023-07-02 10:34:01,226 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5228490216839586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,226 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,246 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.72533
 2023-07-02 10:34:01,247 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,247 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.4979011946070625}
 2023-07-02 10:34:01,247 [prior] Evaluating prior at array([0.32634099, 0.49790119])
 2023-07-02 10:34:01,247 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,247 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4979011946070625, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,247 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,247 [classy] Computing new state
 2023-07-02 10:34:01,247 [classy] Setting parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,291 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,292 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0115828
 2023-07-02 10:34:01,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4979011946070625, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,292 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,312 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34868
 2023-07-02 10:34:01,313 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,313 [mcmc] New sample, #385:
   Omega_m:0.3218066, b1:0.5043132
 2023-07-02 10:34:01,313 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.5640244243980341}
 2023-07-02 10:34:01,313 [prior] Evaluating prior at array([0.32634099, 0.56402442])
 2023-07-02 10:34:01,313 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,313 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5640244243980341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,313 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,313 [classy] Re-using computed results
 2023-07-02 10:34:01,313 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,313 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,313 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5640244243980341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,313 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.7688
 2023-07-02 10:34:01,332 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,332 [model] Posterior to be computed for parameters {'Omega_m': 0.3624106644658897, 'b1': 0.446895076799916}
 2023-07-02 10:34:01,333 [prior] Evaluating prior at array([0.36241066, 0.44689508])
 2023-07-02 10:34:01,333 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,333 [model] Got input parameters: {'Omega_m': 0.3624106644658897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.446895076799916, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,333 [classy] Got parameters {'Omega_m': 0.3624106644658897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,333 [classy] Computing new state
 2023-07-02 10:34:01,333 [classy] Setting parameters: {'Omega_m': 0.3624106644658897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,377 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.64568997189525}
 2023-07-02 10:34:01,377 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,379 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.135957
 2023-07-02 10:34:01,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.446895076799916, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,379 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,399 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2864
 2023-07-02 10:34:01,399 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,399 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.47295512434369624}
 2023-07-02 10:34:01,399 [prior] Evaluating prior at array([0.32634099, 0.47295512])
 2023-07-02 10:34:01,400 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,400 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47295512434369624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,400 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,400 [classy] Re-using computed results
 2023-07-02 10:34:01,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,400 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,400 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47295512434369624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,400 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,419 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13413
 2023-07-02 10:34:01,419 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,420 [mcmc] New sample, #386:
   Omega_m:0.326341, b1:0.4979012
 2023-07-02 10:34:01,420 [model] Posterior to be computed for parameters {'Omega_m': 0.35378144629416375, 'b1': 0.43415158340118853}
 2023-07-02 10:34:01,420 [prior] Evaluating prior at array([0.35378145, 0.43415158])
 2023-07-02 10:34:01,420 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,420 [model] Got input parameters: {'Omega_m': 0.35378144629416375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43415158340118853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,420 [classy] Got parameters {'Omega_m': 0.35378144629416375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,420 [classy] Computing new state
 2023-07-02 10:34:01,420 [classy] Setting parameters: {'Omega_m': 0.35378144629416375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.5635174786093}
 2023-07-02 10:34:01,464 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,466 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0949359
 2023-07-02 10:34:01,466 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43415158340118853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,466 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,486 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.22108
 2023-07-02 10:34:01,486 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,486 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.4740608036104873}
 2023-07-02 10:34:01,486 [prior] Evaluating prior at array([0.32634099, 0.4740608 ])
 2023-07-02 10:34:01,486 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,486 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4740608036104873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,486 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,486 [classy] Re-using computed results
 2023-07-02 10:34:01,486 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,487 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,487 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4740608036104873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,487 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,507 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17153
 2023-07-02 10:34:01,507 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,507 [mcmc] New sample, #387:
   Omega_m:0.326341, b1:0.4729551
 2023-07-02 10:34:01,507 [model] Posterior to be computed for parameters {'Omega_m': 0.3375857085063246, 'b1': 0.4581596544377444}
 2023-07-02 10:34:01,507 [prior] Evaluating prior at array([0.33758571, 0.45815965])
 2023-07-02 10:34:01,508 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,508 [model] Got input parameters: {'Omega_m': 0.3375857085063246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4581596544377444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,508 [classy] Got parameters {'Omega_m': 0.3375857085063246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,508 [classy] Computing new state
 2023-07-02 10:34:01,508 [classy] Setting parameters: {'Omega_m': 0.3375857085063246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,551 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.34305836986834}
 2023-07-02 10:34:01,552 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,553 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0365528
 2023-07-02 10:34:01,554 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4581596544377444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,554 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,573 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.357779
 2023-07-02 10:34:01,573 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,573 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.49489267969220424}
 2023-07-02 10:34:01,573 [prior] Evaluating prior at array([0.32634099, 0.49489268])
 2023-07-02 10:34:01,573 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,573 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49489267969220424, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,573 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,573 [classy] Re-using computed results
 2023-07-02 10:34:01,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,573 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,573 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49489267969220424, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,573 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,592 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62803
 2023-07-02 10:34:01,593 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,593 [mcmc] New sample, #388:
   Omega_m:0.326341, b1:0.4740608
 2023-07-02 10:34:01,593 [model] Posterior to be computed for parameters {'Omega_m': 0.34314133607444913, 'b1': 0.4711353179307621}
 2023-07-02 10:34:01,593 [prior] Evaluating prior at array([0.34314134, 0.47113532])
 2023-07-02 10:34:01,593 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,593 [model] Got input parameters: {'Omega_m': 0.34314133607444913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4711353179307621, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,593 [classy] Got parameters {'Omega_m': 0.34314133607444913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,593 [classy] Computing new state
 2023-07-02 10:34:01,593 [classy] Setting parameters: {'Omega_m': 0.34314133607444913, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,637 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.72397389692074}
 2023-07-02 10:34:01,638 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,639 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.053719
 2023-07-02 10:34:01,639 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4711353179307621, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,639 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,660 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.30515
 2023-07-02 10:34:01,660 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,660 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.49251742952574756}
 2023-07-02 10:34:01,660 [prior] Evaluating prior at array([0.32634099, 0.49251743])
 2023-07-02 10:34:01,660 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,660 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49251742952574756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,660 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,660 [classy] Re-using computed results
 2023-07-02 10:34:01,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,660 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49251742952574756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,661 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,679 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8121
 2023-07-02 10:34:01,680 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,680 [mcmc] New sample, #389:
   Omega_m:0.326341, b1:0.4948927
 2023-07-02 10:34:01,680 [model] Posterior to be computed for parameters {'Omega_m': 0.3298326384116941, 'b1': 0.48757989627786874}
 2023-07-02 10:34:01,680 [prior] Evaluating prior at array([0.32983264, 0.4875799 ])
 2023-07-02 10:34:01,680 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,680 [model] Got input parameters: {'Omega_m': 0.3298326384116941, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48757989627786874, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,680 [classy] Got parameters {'Omega_m': 0.3298326384116941, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,680 [classy] Computing new state
 2023-07-02 10:34:01,680 [classy] Setting parameters: {'Omega_m': 0.3298326384116941, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,725 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2225851889139}
 2023-07-02 10:34:01,725 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,727 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0178916
 2023-07-02 10:34:01,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48757989627786874, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,727 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,746 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24088
 2023-07-02 10:34:01,746 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,746 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.5483764733617812}
 2023-07-02 10:34:01,746 [prior] Evaluating prior at array([0.32634099, 0.54837647])
 2023-07-02 10:34:01,747 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,747 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483764733617812, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,747 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,747 [classy] Re-using computed results
 2023-07-02 10:34:01,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
 2023-07-02 10:34:01,747 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,747 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483764733617812, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,747 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,767 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.4689
 2023-07-02 10:34:01,767 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,767 [model] Posterior to be computed for parameters {'Omega_m': 0.30927079193676327, 'b1': 0.516656402062756}
 2023-07-02 10:34:01,767 [prior] Evaluating prior at array([0.30927079, 0.5166564 ])
 2023-07-02 10:34:01,767 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,767 [model] Got input parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.516656402062756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,767 [classy] Got parameters {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,767 [classy] Computing new state
 2023-07-02 10:34:01,767 [classy] Setting parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,811 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64854361278285}
 2023-07-02 10:34:01,812 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000840646
 2023-07-02 10:34:01,813 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.516656402062756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,813 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,833 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63063
 2023-07-02 10:34:01,833 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,833 [mcmc] New sample, #390:
   Omega_m:0.326341, b1:0.4925174
 2023-07-02 10:34:01,833 [model] Posterior to be computed for parameters {'Omega_m': 0.30927079193676327, 'b1': 0.5340731051513992}
 2023-07-02 10:34:01,833 [prior] Evaluating prior at array([0.30927079, 0.53407311])
 2023-07-02 10:34:01,833 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,833 [model] Got input parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5340731051513992, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,833 [classy] Got parameters {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,833 [classy] Re-using computed results
 2023-07-02 10:34:01,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64854361278285}
 2023-07-02 10:34:01,833 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,833 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5340731051513992, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,833 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,853 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23223
 2023-07-02 10:34:01,853 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,854 [mcmc] New sample, #391:
   Omega_m:0.3092708, b1:0.5166564
 2023-07-02 10:34:01,854 [model] Posterior to be computed for parameters {'Omega_m': 0.33364597473123825, 'b1': 0.4996041607209782}
 2023-07-02 10:34:01,854 [prior] Evaluating prior at array([0.33364597, 0.49960416])
 2023-07-02 10:34:01,854 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,854 [model] Got input parameters: {'Omega_m': 0.33364597473123825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4996041607209782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,854 [classy] Got parameters {'Omega_m': 0.33364597473123825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,854 [classy] Computing new state
 2023-07-02 10:34:01,854 [classy] Setting parameters: {'Omega_m': 0.33364597473123825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.78768795442875}
 2023-07-02 10:34:01,898 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0262816
 2023-07-02 10:34:01,900 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4996041607209782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,900 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,920 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.93907
 2023-07-02 10:34:01,920 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,920 [model] Posterior to be computed for parameters {'Omega_m': 0.30927079193676327, 'b1': 0.5762989093017274}
 2023-07-02 10:34:01,920 [prior] Evaluating prior at array([0.30927079, 0.57629891])
 2023-07-02 10:34:01,920 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,920 [model] Got input parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5762989093017274, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,920 [classy] Got parameters {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,920 [classy] Re-using computed results
 2023-07-02 10:34:01,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64854361278285}
 2023-07-02 10:34:01,920 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:01,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5762989093017274, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,921 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:01,940 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.56627
 2023-07-02 10:34:01,940 [model] Computed derived parameters: {}
 2023-07-02 10:34:01,940 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.5373448518321421}
 2023-07-02 10:34:01,940 [prior] Evaluating prior at array([0.30695713, 0.53734485])
 2023-07-02 10:34:01,940 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:01,940 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5373448518321421, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,941 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:01,941 [classy] Computing new state
 2023-07-02 10:34:01,941 [classy] Setting parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:01,985 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
 2023-07-02 10:34:01,985 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:01,986 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00210168
 2023-07-02 10:34:01,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5373448518321421, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:01,987 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16082
 2023-07-02 10:34:02,007 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,007 [mcmc] New sample, #392:
   Omega_m:0.3092708, b1:0.5340731
 2023-07-02 10:34:02,007 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.5153848024989736}
 2023-07-02 10:34:02,007 [prior] Evaluating prior at array([0.30695713, 0.5153848 ])
 2023-07-02 10:34:02,007 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,007 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5153848024989736, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,007 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,008 [classy] Re-using computed results
 2023-07-02 10:34:02,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
 2023-07-02 10:34:02,008 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5153848024989736, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,008 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,029 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53154
 2023-07-02 10:34:02,029 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,029 [mcmc] New sample, #393:
   Omega_m:0.3069571, b1:0.5373449
 2023-07-02 10:34:02,029 [model] Posterior to be computed for parameters {'Omega_m': 0.3327655738089936, 'b1': 0.47888908627563787}
 2023-07-02 10:34:02,029 [prior] Evaluating prior at array([0.33276557, 0.47888909])
 2023-07-02 10:34:02,029 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,029 [model] Got input parameters: {'Omega_m': 0.3327655738089936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47888908627563787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,029 [classy] Got parameters {'Omega_m': 0.3327655738089936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,029 [classy] Computing new state
 2023-07-02 10:34:02,029 [classy] Setting parameters: {'Omega_m': 0.3327655738089936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.88769621461336}
 2023-07-02 10:34:02,074 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,076 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0242075
 2023-07-02 10:34:02,076 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47888908627563787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,076 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,096 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.995321
 2023-07-02 10:34:02,096 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,096 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.5151205545158337}
 2023-07-02 10:34:02,096 [prior] Evaluating prior at array([0.30695713, 0.51512055])
 2023-07-02 10:34:02,096 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,096 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5151205545158337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,096 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,096 [classy] Re-using computed results
 2023-07-02 10:34:02,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
 2023-07-02 10:34:02,096 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,096 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5151205545158337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,096 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53196
 2023-07-02 10:34:02,117 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,117 [mcmc] New sample, #394:
   Omega_m:0.3069571, b1:0.5153848
 2023-07-02 10:34:02,117 [model] Posterior to be computed for parameters {'Omega_m': 0.29514104408932057, 'b1': 0.5318296833622995}
 2023-07-02 10:34:02,117 [prior] Evaluating prior at array([0.29514104, 0.53182968])
 2023-07-02 10:34:02,117 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,117 [model] Got input parameters: {'Omega_m': 0.29514104408932057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5318296833622995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,117 [classy] Got parameters {'Omega_m': 0.29514104408932057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,117 [classy] Computing new state
 2023-07-02 10:34:02,117 [classy] Setting parameters: {'Omega_m': 0.29514104408932057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3998885998488}
 2023-07-02 10:34:02,163 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0194741
 2023-07-02 10:34:02,165 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5318296833622995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,165 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,184 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.412718
 2023-07-02 10:34:02,184 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,184 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.507175400849865}
 2023-07-02 10:34:02,185 [prior] Evaluating prior at array([0.30695713, 0.5071754 ])
 2023-07-02 10:34:02,185 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,185 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.507175400849865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,185 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,185 [classy] Re-using computed results
 2023-07-02 10:34:02,185 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
 2023-07-02 10:34:02,185 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,185 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.507175400849865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,185 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,204 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37146
 2023-07-02 10:34:02,204 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,204 [mcmc] New sample, #395:
   Omega_m:0.3069571, b1:0.5151206
 2023-07-02 10:34:02,204 [model] Posterior to be computed for parameters {'Omega_m': 0.29850861524975986, 'b1': 0.5191224475337723}
 2023-07-02 10:34:02,204 [prior] Evaluating prior at array([0.29850862, 0.51912245])
 2023-07-02 10:34:02,204 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,204 [model] Got input parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191224475337723, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,204 [classy] Got parameters {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,204 [classy] Computing new state
 2023-07-02 10:34:02,205 [classy] Setting parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9758988057451}
 2023-07-02 10:34:02,249 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0126084
 2023-07-02 10:34:02,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191224475337723, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,251 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,271 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.921069
 2023-07-02 10:34:02,271 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,271 [mcmc] New sample, #396:
   Omega_m:0.3069571, b1:0.5071754
 2023-07-02 10:34:02,271 [model] Posterior to be computed for parameters {'Omega_m': 0.29850861524975986, 'b1': 0.5194416788091566}
 2023-07-02 10:34:02,271 [prior] Evaluating prior at array([0.29850862, 0.51944168])
 2023-07-02 10:34:02,272 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,272 [model] Got input parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5194416788091566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,272 [classy] Got parameters {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,272 [classy] Re-using computed results
 2023-07-02 10:34:02,272 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9758988057451}
 2023-07-02 10:34:02,272 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,272 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5194416788091566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,272 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,291 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.9394
 2023-07-02 10:34:02,291 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,291 [mcmc] New sample, #397:
   Omega_m:0.2985086, b1:0.5191224
 2023-07-02 10:34:02,292 [model] Posterior to be computed for parameters {'Omega_m': 0.2776255104055501, 'b1': 0.5489724760334908}
 2023-07-02 10:34:02,292 [prior] Evaluating prior at array([0.27762551, 0.54897248])
 2023-07-02 10:34:02,292 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,292 [model] Got input parameters: {'Omega_m': 0.2776255104055501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5489724760334908, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,292 [classy] Got parameters {'Omega_m': 0.2776255104055501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,292 [classy] Computing new state
 2023-07-02 10:34:02,292 [classy] Setting parameters: {'Omega_m': 0.2776255104055501, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.6751775939724}
 2023-07-02 10:34:02,336 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0817138
 2023-07-02 10:34:02,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5489724760334908, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,338 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,358 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.28374
 2023-07-02 10:34:02,358 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,358 [model] Posterior to be computed for parameters {'Omega_m': 0.29850861524975986, 'b1': 0.5828570092383326}
 2023-07-02 10:34:02,358 [prior] Evaluating prior at array([0.29850862, 0.58285701])
 2023-07-02 10:34:02,358 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,359 [model] Got input parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5828570092383326, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,359 [classy] Got parameters {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,359 [classy] Re-using computed results
 2023-07-02 10:34:02,359 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9758988057451}
 2023-07-02 10:34:02,359 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5828570092383326, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,359 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,378 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46582
 2023-07-02 10:34:02,378 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,379 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.49415132853053656}
 2023-07-02 10:34:02,379 [prior] Evaluating prior at array([0.31639303, 0.49415133])
 2023-07-02 10:34:02,379 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,379 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49415132853053656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,379 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,379 [classy] Computing new state
 2023-07-02 10:34:02,379 [classy] Setting parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
 2023-07-02 10:34:02,423 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,425 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00113043
 2023-07-02 10:34:02,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49415132853053656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,425 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88248
 2023-07-02 10:34:02,444 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,445 [mcmc] New sample, #398:
   Omega_m:0.2985086, b1:0.5194417
 2023-07-02 10:34:02,445 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.45995741762883807}
 2023-07-02 10:34:02,445 [prior] Evaluating prior at array([0.31639303, 0.45995742])
 2023-07-02 10:34:02,445 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,445 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45995741762883807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,445 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,445 [classy] Re-using computed results
 2023-07-02 10:34:02,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
 2023-07-02 10:34:02,445 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45995741762883807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,445 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,465 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.806045
 2023-07-02 10:34:02,465 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,465 [model] Posterior to be computed for parameters {'Omega_m': 0.29572736309142833, 'b1': 0.5233746473083404}
 2023-07-02 10:34:02,465 [prior] Evaluating prior at array([0.29572736, 0.52337465])
 2023-07-02 10:34:02,465 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,465 [model] Got input parameters: {'Omega_m': 0.29572736309142833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5233746473083404, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,465 [classy] Got parameters {'Omega_m': 0.29572736309142833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,465 [classy] Computing new state
 2023-07-02 10:34:02,465 [classy] Setting parameters: {'Omega_m': 0.29572736309142833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.32576712333324}
 2023-07-02 10:34:02,509 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0181659
 2023-07-02 10:34:02,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5233746473083404, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,512 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,531 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.24131
 2023-07-02 10:34:02,531 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.4652973365539925}
 2023-07-02 10:34:02,531 [prior] Evaluating prior at array([0.31639303, 0.46529734])
 2023-07-02 10:34:02,532 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,532 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4652973365539925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,532 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,532 [classy] Re-using computed results
 2023-07-02 10:34:02,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
 2023-07-02 10:34:02,532 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4652973365539925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,532 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,551 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.155575
 2023-07-02 10:34:02,551 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,551 [model] Posterior to be computed for parameters {'Omega_m': 0.32621898852460657, 'b1': 0.4802564417337894}
 2023-07-02 10:34:02,551 [prior] Evaluating prior at array([0.32621899, 0.48025644])
 2023-07-02 10:34:02,551 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,551 [model] Got input parameters: {'Omega_m': 0.32621898852460657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4802564417337894, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,551 [classy] Got parameters {'Omega_m': 0.32621898852460657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,551 [classy] Computing new state
 2023-07-02 10:34:02,551 [classy] Setting parameters: {'Omega_m': 0.32621898852460657, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.63896155274264}
 2023-07-02 10:34:02,596 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0113865
 2023-07-02 10:34:02,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4802564417337894, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,597 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,618 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.274
 2023-07-02 10:34:02,618 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,618 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.47251288564438876}
 2023-07-02 10:34:02,618 [prior] Evaluating prior at array([0.31639303, 0.47251289])
 2023-07-02 10:34:02,618 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,618 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47251288564438876, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,619 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,619 [classy] Re-using computed results
 2023-07-02 10:34:02,619 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
 2023-07-02 10:34:02,619 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,619 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47251288564438876, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,619 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,638 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23337
 2023-07-02 10:34:02,638 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,638 [model] Posterior to be computed for parameters {'Omega_m': 0.30163674124987483, 'b1': 0.5150181960324958}
 2023-07-02 10:34:02,638 [prior] Evaluating prior at array([0.30163674, 0.5150182 ])
 2023-07-02 10:34:02,638 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,638 [model] Got input parameters: {'Omega_m': 0.30163674124987483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150181960324958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,638 [classy] Got parameters {'Omega_m': 0.30163674124987483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,638 [classy] Computing new state
 2023-07-02 10:34:02,638 [classy] Setting parameters: {'Omega_m': 0.30163674124987483, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.58580014591882}
 2023-07-02 10:34:02,683 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,685 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00761678
 2023-07-02 10:34:02,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150181960324958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,685 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,705 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59043
 2023-07-02 10:34:02,705 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.526007633647398}
 2023-07-02 10:34:02,705 [prior] Evaluating prior at array([0.31639303, 0.52600763])
 2023-07-02 10:34:02,705 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,705 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.526007633647398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,705 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,705 [classy] Re-using computed results
 2023-07-02 10:34:02,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
 2023-07-02 10:34:02,705 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.526007633647398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,705 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,726 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.712257
 2023-07-02 10:34:02,726 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,726 [model] Posterior to be computed for parameters {'Omega_m': 0.30629227855963836, 'b1': 0.5084348010205674}
 2023-07-02 10:34:02,726 [prior] Evaluating prior at array([0.30629228, 0.5084348 ])
 2023-07-02 10:34:02,726 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,726 [model] Got input parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5084348010205674, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,726 [classy] Got parameters {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,726 [classy] Computing new state
 2023-07-02 10:34:02,726 [classy] Setting parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,770 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01178131470812}
 2023-07-02 10:34:02,770 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,772 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00259009
 2023-07-02 10:34:02,772 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5084348010205674, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,772 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,791 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.3061
 2023-07-02 10:34:02,791 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,791 [mcmc] New sample, #399:
   Omega_m:0.316393, b1:0.4941513
 2023-07-02 10:34:02,792 [model] Posterior to be computed for parameters {'Omega_m': 0.30629227855963836, 'b1': 0.47395597949394064}
 2023-07-02 10:34:02,792 [prior] Evaluating prior at array([0.30629228, 0.47395598])
 2023-07-02 10:34:02,792 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,792 [model] Got input parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47395597949394064, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,792 [classy] Got parameters {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,792 [classy] Re-using computed results
 2023-07-02 10:34:02,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01178131470812}
 2023-07-02 10:34:02,792 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47395597949394064, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,792 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,811 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.09902
 2023-07-02 10:34:02,811 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,811 [model] Posterior to be computed for parameters {'Omega_m': 0.3028074554373338, 'b1': 0.513362689174899}
 2023-07-02 10:34:02,811 [prior] Evaluating prior at array([0.30280746, 0.51336269])
 2023-07-02 10:34:02,812 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,812 [model] Got input parameters: {'Omega_m': 0.3028074554373338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.513362689174899, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,812 [classy] Got parameters {'Omega_m': 0.3028074554373338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,812 [classy] Computing new state
 2023-07-02 10:34:02,812 [classy] Setting parameters: {'Omega_m': 0.3028074554373338, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4407275791473}
 2023-07-02 10:34:02,856 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,858 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00608537
 2023-07-02 10:34:02,858 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.513362689174899, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,858 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,878 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79847
 2023-07-02 10:34:02,878 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,878 [model] Posterior to be computed for parameters {'Omega_m': 0.30629227855963836, 'b1': 0.5189580995967357}
 2023-07-02 10:34:02,878 [prior] Evaluating prior at array([0.30629228, 0.5189581 ])
 2023-07-02 10:34:02,878 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,879 [model] Got input parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5189580995967357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,879 [classy] Got parameters {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,879 [classy] Re-using computed results
 2023-07-02 10:34:02,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01178131470812}
 2023-07-02 10:34:02,879 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,879 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5189580995967357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,879 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,898 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.44347
 2023-07-02 10:34:02,899 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,899 [mcmc] New sample, #400:
   Omega_m:0.3062923, b1:0.5084348
 2023-07-02 10:34:02,899 [mcmc] Learn + convergence test @ 400 samples accepted.
 2023-07-02 10:34:02,899 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:02,904 [mcmc]  - Acceptance rate: 0.397
 2023-07-02 10:34:02,904 [mcmc]  - Condition number = 8.94406
 2023-07-02 10:34:02,904 [mcmc]  - Eigenvalues = array([0.00573545, 0.05129817])
 2023-07-02 10:34:02,904 [mcmc]  - Convergence of means: R-1 = 0.051298 after 320 accepted steps
 2023-07-02 10:34:02,904 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:02,904 [mcmc] array([[ 9.22576354e-05, -1.28600163e-04],
       [-1.28600163e-04,  3.31754404e-04]])
 2023-07-02 10:34:02,915 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:02,915 [model] Posterior to be computed for parameters {'Omega_m': 0.31017443128197053, 'b1': 0.5135466724413341}
 2023-07-02 10:34:02,915 [prior] Evaluating prior at array([0.31017443, 0.51354667])
 2023-07-02 10:34:02,915 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,915 [model] Got input parameters: {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135466724413341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,915 [classy] Got parameters {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,915 [classy] Computing new state
 2023-07-02 10:34:02,915 [classy] Setting parameters: {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:02,960 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53895190519492}
 2023-07-02 10:34:02,960 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:02,962 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000531381
 2023-07-02 10:34:02,962 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135466724413341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,962 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:02,983 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72914
 2023-07-02 10:34:02,983 [model] Computed derived parameters: {}
 2023-07-02 10:34:02,983 [mcmc] New sample, #401:
   Omega_m:0.3062923, b1:0.5189581
 2023-07-02 10:34:02,983 [model] Posterior to be computed for parameters {'Omega_m': 0.31017443128197053, 'b1': 0.5575680079258327}
 2023-07-02 10:34:02,983 [prior] Evaluating prior at array([0.31017443, 0.55756801])
 2023-07-02 10:34:02,983 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:02,983 [model] Got input parameters: {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5575680079258327, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,984 [classy] Got parameters {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:02,984 [classy] Re-using computed results
 2023-07-02 10:34:02,984 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53895190519492}
 2023-07-02 10:34:02,984 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:02,984 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5575680079258327, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:02,984 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,003 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.82942
 2023-07-02 10:34:03,003 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,004 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.4972640121345697}
 2023-07-02 10:34:03,004 [prior] Evaluating prior at array([0.3218556 , 0.49726401])
 2023-07-02 10:34:03,004 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,004 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4972640121345697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,004 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,004 [classy] Computing new state
 2023-07-02 10:34:03,004 [classy] Setting parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,049 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
 2023-07-02 10:34:03,049 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00546453
 2023-07-02 10:34:03,051 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4972640121345697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,051 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,071 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4442
 2023-07-02 10:34:03,071 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,071 [mcmc] New sample, #402:
   Omega_m:0.3101744, b1:0.5135467
 2023-07-02 10:34:03,071 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.6015576710679337}
 2023-07-02 10:34:03,071 [prior] Evaluating prior at array([0.3218556 , 0.60155767])
 2023-07-02 10:34:03,071 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,071 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6015576710679337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,071 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,072 [classy] Re-using computed results
 2023-07-02 10:34:03,072 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
 2023-07-02 10:34:03,072 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,072 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6015576710679337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,072 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,091 [fs_likelihood.fslikelihood] Computed log-likelihood = -36.5354
 2023-07-02 10:34:03,091 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,091 [model] Posterior to be computed for parameters {'Omega_m': 0.3304105002249723, 'b1': 0.4853391234784089}
 2023-07-02 10:34:03,091 [prior] Evaluating prior at array([0.3304105 , 0.48533912])
 2023-07-02 10:34:03,091 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,091 [model] Got input parameters: {'Omega_m': 0.3304105002249723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853391234784089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,091 [classy] Got parameters {'Omega_m': 0.3304105002249723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,091 [classy] Computing new state
 2023-07-02 10:34:03,091 [classy] Setting parameters: {'Omega_m': 0.3304105002249723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15639222109297}
 2023-07-02 10:34:03,139 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,140 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0190632
 2023-07-02 10:34:03,141 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853391234784089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,141 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,160 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24262
 2023-07-02 10:34:03,160 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,161 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.5380688891278057}
 2023-07-02 10:34:03,161 [prior] Evaluating prior at array([0.3218556 , 0.53806889])
 2023-07-02 10:34:03,161 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,161 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5380688891278057, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,161 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,161 [classy] Re-using computed results
 2023-07-02 10:34:03,161 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
 2023-07-02 10:34:03,161 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,161 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5380688891278057, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,161 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,182 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.49411
 2023-07-02 10:34:03,182 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,182 [model] Posterior to be computed for parameters {'Omega_m': 0.2157161208066216, 'b1': 0.6452144101424373}
 2023-07-02 10:34:03,182 [prior] Evaluating prior at array([0.21571612, 0.64521441])
 2023-07-02 10:34:03,182 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,182 [model] Got input parameters: {'Omega_m': 0.2157161208066216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6452144101424373, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,182 [classy] Got parameters {'Omega_m': 0.2157161208066216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,182 [classy] Computing new state
 2023-07-02 10:34:03,182 [classy] Setting parameters: {'Omega_m': 0.2157161208066216, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.82231608225342}
 2023-07-02 10:34:03,226 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,228 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.749984
 2023-07-02 10:34:03,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6452144101424373, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,228 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,247 [fs_likelihood.fslikelihood] Computed log-likelihood = -82.9647
 2023-07-02 10:34:03,247 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.5331885403459865}
 2023-07-02 10:34:03,248 [prior] Evaluating prior at array([0.3218556 , 0.53318854])
 2023-07-02 10:34:03,248 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,248 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5331885403459865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,248 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,248 [classy] Re-using computed results
 2023-07-02 10:34:03,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
 2023-07-02 10:34:03,248 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,248 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5331885403459865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,248 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,267 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.13703
 2023-07-02 10:34:03,267 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,267 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5330825944382281}
 2023-07-02 10:34:03,267 [prior] Evaluating prior at array([0.29615938, 0.53308259])
 2023-07-02 10:34:03,268 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,268 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330825944382281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,268 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,268 [classy] Computing new state
 2023-07-02 10:34:03,268 [classy] Setting parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
 2023-07-02 10:34:03,312 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0172325
 2023-07-02 10:34:03,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330825944382281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,314 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,335 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.714806
 2023-07-02 10:34:03,335 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,335 [mcmc] New sample, #403:
   Omega_m:0.3218556, b1:0.497264
 2023-07-02 10:34:03,335 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5346933179969885}
 2023-07-02 10:34:03,335 [prior] Evaluating prior at array([0.29615938, 0.53469332])
 2023-07-02 10:34:03,335 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,335 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5346933179969885, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,335 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,335 [classy] Re-using computed results
 2023-07-02 10:34:03,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
 2023-07-02 10:34:03,335 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5346933179969885, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,335 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,355 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.720472
 2023-07-02 10:34:03,355 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,355 [mcmc] New sample, #404:
   Omega_m:0.2961594, b1:0.5330826
 2023-07-02 10:34:03,355 [model] Posterior to be computed for parameters {'Omega_m': 0.3471174283873723, 'b1': 0.46366165329319864}
 2023-07-02 10:34:03,355 [prior] Evaluating prior at array([0.34711743, 0.46366165])
 2023-07-02 10:34:03,355 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,355 [model] Got input parameters: {'Omega_m': 0.3471174283873723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46366165329319864, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,355 [classy] Got parameters {'Omega_m': 0.3471174283873723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,355 [classy] Computing new state
 2023-07-02 10:34:03,355 [classy] Setting parameters: {'Omega_m': 0.3471174283873723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2865128906438}
 2023-07-02 10:34:03,400 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0678676
 2023-07-02 10:34:03,401 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46366165329319864, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,401 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,421 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.37284
 2023-07-02 10:34:03,421 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,421 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5273613487766589}
 2023-07-02 10:34:03,421 [prior] Evaluating prior at array([0.29615938, 0.52736135])
 2023-07-02 10:34:03,422 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,422 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5273613487766589, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,422 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,422 [classy] Re-using computed results
 2023-07-02 10:34:03,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
 2023-07-02 10:34:03,422 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,422 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5273613487766589, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,422 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,441 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.584704
 2023-07-02 10:34:03,441 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,442 [mcmc] New sample, #405:
   Omega_m:0.2961594, b1:0.5346933
 2023-07-02 10:34:03,442 [model] Posterior to be computed for parameters {'Omega_m': 0.25207010974626076, 'b1': 0.5888184545902818}
 2023-07-02 10:34:03,442 [prior] Evaluating prior at array([0.25207011, 0.58881845])
 2023-07-02 10:34:03,442 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,442 [model] Got input parameters: {'Omega_m': 0.25207010974626076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5888184545902818, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,442 [classy] Got parameters {'Omega_m': 0.25207010974626076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,442 [classy] Computing new state
 2023-07-02 10:34:03,442 [classy] Setting parameters: {'Omega_m': 0.25207010974626076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,486 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.22467187139597}
 2023-07-02 10:34:03,486 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,488 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.262812
 2023-07-02 10:34:03,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5888184545902818, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,488 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,508 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.6965
 2023-07-02 10:34:03,508 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,508 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5098061155898931}
 2023-07-02 10:34:03,508 [prior] Evaluating prior at array([0.29615938, 0.50980612])
 2023-07-02 10:34:03,508 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,508 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5098061155898931, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,509 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,509 [classy] Re-using computed results
 2023-07-02 10:34:03,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
 2023-07-02 10:34:03,509 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5098061155898931, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,529 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.85939
 2023-07-02 10:34:03,529 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,529 [mcmc] New sample, #406:
   Omega_m:0.2961594, b1:0.5273613
 2023-07-02 10:34:03,529 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.4853632083758137}
 2023-07-02 10:34:03,529 [prior] Evaluating prior at array([0.3136947 , 0.48536321])
 2023-07-02 10:34:03,529 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,529 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853632083758137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,529 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,529 [classy] Computing new state
 2023-07-02 10:34:03,530 [classy] Setting parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
 2023-07-02 10:34:03,573 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000292036
 2023-07-02 10:34:03,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853632083758137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,576 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,595 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11708
 2023-07-02 10:34:03,595 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,595 [mcmc] New sample, #407:
   Omega_m:0.2961594, b1:0.5098061
 2023-07-02 10:34:03,595 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.48668802781481163}
 2023-07-02 10:34:03,596 [prior] Evaluating prior at array([0.3136947 , 0.48668803])
 2023-07-02 10:34:03,596 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,596 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48668802781481163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,596 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,596 [classy] Re-using computed results
 2023-07-02 10:34:03,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
 2023-07-02 10:34:03,596 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48668802781481163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,596 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2332
 2023-07-02 10:34:03,616 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,616 [mcmc] New sample, #408:
   Omega_m:0.3136947, b1:0.4853632
 2023-07-02 10:34:03,616 [model] Posterior to be computed for parameters {'Omega_m': 0.2942025589156645, 'b1': 0.5138585946135361}
 2023-07-02 10:34:03,616 [prior] Evaluating prior at array([0.29420256, 0.51385859])
 2023-07-02 10:34:03,616 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,616 [model] Got input parameters: {'Omega_m': 0.2942025589156645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5138585946135361, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,616 [classy] Got parameters {'Omega_m': 0.2942025589156645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,616 [classy] Computing new state
 2023-07-02 10:34:03,616 [classy] Setting parameters: {'Omega_m': 0.2942025589156645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.5187925439928}
 2023-07-02 10:34:03,660 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.021668
 2023-07-02 10:34:03,662 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5138585946135361, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,662 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,682 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.29218
 2023-07-02 10:34:03,682 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,682 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.4709718881406779}
 2023-07-02 10:34:03,682 [prior] Evaluating prior at array([0.3136947 , 0.47097189])
 2023-07-02 10:34:03,683 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,683 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4709718881406779, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,683 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,683 [classy] Re-using computed results
 2023-07-02 10:34:03,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
 2023-07-02 10:34:03,683 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4709718881406779, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,683 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,702 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.285769
 2023-07-02 10:34:03,703 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,703 [mcmc] New sample, #409:
   Omega_m:0.3136947, b1:0.486688
 2023-07-02 10:34:03,703 [model] Posterior to be computed for parameters {'Omega_m': 0.33479531142120156, 'b1': 0.44155922936011693}
 2023-07-02 10:34:03,703 [prior] Evaluating prior at array([0.33479531, 0.44155923])
 2023-07-02 10:34:03,703 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,703 [model] Got input parameters: {'Omega_m': 0.33479531142120156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44155922936011693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,703 [classy] Got parameters {'Omega_m': 0.33479531142120156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,703 [classy] Computing new state
 2023-07-02 10:34:03,703 [classy] Setting parameters: {'Omega_m': 0.33479531142120156, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.65748851699811}
 2023-07-02 10:34:03,747 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,749 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0291117
 2023-07-02 10:34:03,749 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44155922936011693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,749 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,769 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.469883
 2023-07-02 10:34:03,769 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,769 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.47282664608364716}
 2023-07-02 10:34:03,769 [prior] Evaluating prior at array([0.3136947 , 0.47282665])
 2023-07-02 10:34:03,769 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,769 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47282664608364716, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,769 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,769 [classy] Re-using computed results
 2023-07-02 10:34:03,769 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
 2023-07-02 10:34:03,769 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,769 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47282664608364716, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,769 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,789 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.579532
 2023-07-02 10:34:03,789 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,789 [mcmc] New sample, #410:
   Omega_m:0.3136947, b1:0.4709719
 2023-07-02 10:34:03,789 [model] Posterior to be computed for parameters {'Omega_m': 0.33172923829776163, 'b1': 0.44768786124554727}
 2023-07-02 10:34:03,790 [prior] Evaluating prior at array([0.33172924, 0.44768786])
 2023-07-02 10:34:03,790 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,790 [model] Got input parameters: {'Omega_m': 0.33172923829776163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44768786124554727, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,790 [classy] Got parameters {'Omega_m': 0.33172923829776163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,790 [classy] Computing new state
 2023-07-02 10:34:03,790 [classy] Setting parameters: {'Omega_m': 0.33172923829776163, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.00572306219476}
 2023-07-02 10:34:03,834 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,835 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.021871
 2023-07-02 10:34:03,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44768786124554727, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,836 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,855 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.158559
 2023-07-02 10:34:03,855 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,855 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.4850288391223774}
 2023-07-02 10:34:03,855 [prior] Evaluating prior at array([0.3136947 , 0.48502884])
 2023-07-02 10:34:03,855 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,855 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4850288391223774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,855 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,855 [classy] Re-using computed results
 2023-07-02 10:34:03,855 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
 2023-07-02 10:34:03,855 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,856 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4850288391223774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,856 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,875 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08635
 2023-07-02 10:34:03,875 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,875 [mcmc] New sample, #411:
   Omega_m:0.3136947, b1:0.4728266
 2023-07-02 10:34:03,875 [model] Posterior to be computed for parameters {'Omega_m': 0.28708113506643673, 'b1': 0.5221261319309135}
 2023-07-02 10:34:03,875 [prior] Evaluating prior at array([0.28708114, 0.52212613])
 2023-07-02 10:34:03,875 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,875 [model] Got input parameters: {'Omega_m': 0.28708113506643673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5221261319309135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,875 [classy] Got parameters {'Omega_m': 0.28708113506643673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,875 [classy] Computing new state
 2023-07-02 10:34:03,875 [classy] Setting parameters: {'Omega_m': 0.28708113506643673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:03,919 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.43194687538517}
 2023-07-02 10:34:03,920 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:03,921 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0424211
 2023-07-02 10:34:03,922 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5221261319309135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,922 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,942 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.19147
 2023-07-02 10:34:03,942 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,942 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.47018105076464906}
 2023-07-02 10:34:03,942 [prior] Evaluating prior at array([0.3136947 , 0.47018105])
 2023-07-02 10:34:03,943 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,943 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47018105076464906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,943 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,943 [classy] Re-using computed results
 2023-07-02 10:34:03,943 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
 2023-07-02 10:34:03,943 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:03,943 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47018105076464906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,943 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:03,962 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.1554
 2023-07-02 10:34:03,962 [model] Computed derived parameters: {}
 2023-07-02 10:34:03,962 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.4588131294607831}
 2023-07-02 10:34:03,962 [prior] Evaluating prior at array([0.33250182, 0.45881313])
 2023-07-02 10:34:03,962 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:03,963 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4588131294607831, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:03,963 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:03,963 [classy] Computing new state
 2023-07-02 10:34:03,963 [classy] Setting parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,007 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
 2023-07-02 10:34:04,007 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,009 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0236021
 2023-07-02 10:34:04,009 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4588131294607831, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,009 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,028 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10002
 2023-07-02 10:34:04,028 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,028 [mcmc] New sample, #412:
   Omega_m:0.3136947, b1:0.4850288
 2023-07-02 10:34:04,028 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.49525029698126866}
 2023-07-02 10:34:04,028 [prior] Evaluating prior at array([0.33250182, 0.4952503 ])
 2023-07-02 10:34:04,029 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,029 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49525029698126866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,029 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,029 [classy] Re-using computed results
 2023-07-02 10:34:04,029 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
 2023-07-02 10:34:04,029 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,029 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49525029698126866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,029 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,049 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.633015
 2023-07-02 10:34:04,049 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,049 [model] Posterior to be computed for parameters {'Omega_m': 0.3336984615857981, 'b1': 0.45714510602023084}
 2023-07-02 10:34:04,049 [prior] Evaluating prior at array([0.33369846, 0.45714511])
 2023-07-02 10:34:04,050 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,050 [model] Got input parameters: {'Omega_m': 0.3336984615857981, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45714510602023084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,050 [classy] Got parameters {'Omega_m': 0.3336984615857981, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,050 [classy] Computing new state
 2023-07-02 10:34:04,050 [classy] Setting parameters: {'Omega_m': 0.3336984615857981, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,094 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.781732909058}
 2023-07-02 10:34:04,094 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,096 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0264079
 2023-07-02 10:34:04,096 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45714510602023084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,096 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,116 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.910473
 2023-07-02 10:34:04,116 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,116 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.4499738188870939}
 2023-07-02 10:34:04,116 [prior] Evaluating prior at array([0.33250182, 0.44997382])
 2023-07-02 10:34:04,116 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,116 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4499738188870939, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,116 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,116 [classy] Re-using computed results
 2023-07-02 10:34:04,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
 2023-07-02 10:34:04,116 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,116 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4499738188870939, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,116 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,139 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.426352
 2023-07-02 10:34:04,139 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,139 [model] Posterior to be computed for parameters {'Omega_m': 0.2894712871703308, 'b1': 0.5187944407467544}
 2023-07-02 10:34:04,139 [prior] Evaluating prior at array([0.28947129, 0.51879444])
 2023-07-02 10:34:04,139 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,139 [model] Got input parameters: {'Omega_m': 0.2894712871703308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187944407467544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,139 [classy] Got parameters {'Omega_m': 0.2894712871703308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,139 [classy] Computing new state
 2023-07-02 10:34:04,140 [classy] Setting parameters: {'Omega_m': 0.2894712871703308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12330670930834}
 2023-07-02 10:34:04,184 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,185 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0346354
 2023-07-02 10:34:04,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187944407467544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.20028
 2023-07-02 10:34:04,205 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,205 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.46032603935392774}
 2023-07-02 10:34:04,205 [prior] Evaluating prior at array([0.33250182, 0.46032604])
 2023-07-02 10:34:04,205 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,205 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46032603935392774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,205 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,205 [classy] Re-using computed results
 2023-07-02 10:34:04,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
 2023-07-02 10:34:04,206 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46032603935392774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,225 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.17402
 2023-07-02 10:34:04,225 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,225 [mcmc] New sample, #413:
   Omega_m:0.3325018, b1:0.4588131
 2023-07-02 10:34:04,225 [model] Posterior to be computed for parameters {'Omega_m': 0.33611141766540426, 'b1': 0.4552945377125158}
 2023-07-02 10:34:04,225 [prior] Evaluating prior at array([0.33611142, 0.45529454])
 2023-07-02 10:34:04,225 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,225 [model] Got input parameters: {'Omega_m': 0.33611141766540426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4552945377125158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,225 [classy] Got parameters {'Omega_m': 0.33611141766540426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,225 [classy] Computing new state
 2023-07-02 10:34:04,225 [classy] Setting parameters: {'Omega_m': 0.33611141766540426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,269 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.50889172454458}
 2023-07-02 10:34:04,269 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,271 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0325213
 2023-07-02 10:34:04,271 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4552945377125158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,271 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,291 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.548363
 2023-07-02 10:34:04,292 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,292 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.47424111391339085}
 2023-07-02 10:34:04,292 [prior] Evaluating prior at array([0.33250182, 0.47424111])
 2023-07-02 10:34:04,292 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,292 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47424111391339085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,292 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,292 [classy] Re-using computed results
 2023-07-02 10:34:04,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
 2023-07-02 10:34:04,292 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47424111391339085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,292 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,312 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.27417
 2023-07-02 10:34:04,312 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,312 [mcmc] New sample, #414:
   Omega_m:0.3325018, b1:0.460326
 2023-07-02 10:34:04,312 [model] Posterior to be computed for parameters {'Omega_m': 0.3276120072437892, 'b1': 0.4810571472996067}
 2023-07-02 10:34:04,312 [prior] Evaluating prior at array([0.32761201, 0.48105715])
 2023-07-02 10:34:04,312 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,312 [model] Got input parameters: {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4810571472996067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,312 [classy] Got parameters {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,313 [classy] Computing new state
 2023-07-02 10:34:04,313 [classy] Setting parameters: {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.47796346563553}
 2023-07-02 10:34:04,357 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137248
 2023-07-02 10:34:04,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4810571472996067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,359 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,379 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06864
 2023-07-02 10:34:04,379 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,379 [mcmc] New sample, #415:
   Omega_m:0.3325018, b1:0.4742411
 2023-07-02 10:34:04,379 [model] Posterior to be computed for parameters {'Omega_m': 0.3276120072437892, 'b1': 0.4690397551553866}
 2023-07-02 10:34:04,379 [prior] Evaluating prior at array([0.32761201, 0.46903976])
 2023-07-02 10:34:04,379 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,379 [model] Got input parameters: {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4690397551553866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,379 [classy] Got parameters {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,379 [classy] Re-using computed results
 2023-07-02 10:34:04,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.47796346563553}
 2023-07-02 10:34:04,380 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,380 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4690397551553866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,380 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,400 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91142
 2023-07-02 10:34:04,400 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,400 [mcmc] New sample, #416:
   Omega_m:0.327612, b1:0.4810571
 2023-07-02 10:34:04,401 [model] Posterior to be computed for parameters {'Omega_m': 0.328201062498136, 'b1': 0.4682186567011533}
 2023-07-02 10:34:04,401 [prior] Evaluating prior at array([0.32820106, 0.46821866])
 2023-07-02 10:34:04,401 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,401 [model] Got input parameters: {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4682186567011533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,401 [classy] Got parameters {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,401 [classy] Computing new state
 2023-07-02 10:34:04,401 [classy] Setting parameters: {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,446 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41006973419633}
 2023-07-02 10:34:04,446 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,448 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0147777
 2023-07-02 10:34:04,448 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4682186567011533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,448 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,468 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84466
 2023-07-02 10:34:04,468 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,468 [mcmc] New sample, #417:
   Omega_m:0.327612, b1:0.4690398
 2023-07-02 10:34:04,468 [model] Posterior to be computed for parameters {'Omega_m': 0.328201062498136, 'b1': 0.5211384272590601}
 2023-07-02 10:34:04,468 [prior] Evaluating prior at array([0.32820106, 0.52113843])
 2023-07-02 10:34:04,468 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,468 [model] Got input parameters: {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5211384272590601, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,468 [classy] Got parameters {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,468 [classy] Re-using computed results
 2023-07-02 10:34:04,468 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41006973419633}
 2023-07-02 10:34:04,468 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,468 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5211384272590601, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,468 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.68378
 2023-07-02 10:34:04,490 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,490 [model] Posterior to be computed for parameters {'Omega_m': 0.3169489977851921, 'b1': 0.4839031835338281}
 2023-07-02 10:34:04,490 [prior] Evaluating prior at array([0.316949  , 0.48390318])
 2023-07-02 10:34:04,491 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,491 [model] Got input parameters: {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4839031835338281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,491 [classy] Got parameters {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,491 [classy] Computing new state
 2023-07-02 10:34:04,491 [classy] Setting parameters: {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,536 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72624883210472}
 2023-07-02 10:34:04,536 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,539 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00141142
 2023-07-02 10:34:04,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4839031835338281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,539 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,560 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46536
 2023-07-02 10:34:04,560 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,560 [mcmc] New sample, #418:
   Omega_m:0.3282011, b1:0.4682187
 2023-07-02 10:34:04,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3169489977851921, 'b1': 0.450033837881795}
 2023-07-02 10:34:04,560 [prior] Evaluating prior at array([0.316949  , 0.45003384])
 2023-07-02 10:34:04,561 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,561 [model] Got input parameters: {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.450033837881795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,561 [classy] Got parameters {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,561 [classy] Re-using computed results
 2023-07-02 10:34:04,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72624883210472}
 2023-07-02 10:34:04,561 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.450033837881795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,561 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,581 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.72717
 2023-07-02 10:34:04,581 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,581 [model] Posterior to be computed for parameters {'Omega_m': 0.32589804097134906, 'b1': 0.47142889445348024}
 2023-07-02 10:34:04,581 [prior] Evaluating prior at array([0.32589804, 0.47142889])
 2023-07-02 10:34:04,581 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,581 [model] Got input parameters: {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47142889445348024, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,581 [classy] Got parameters {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,581 [classy] Computing new state
 2023-07-02 10:34:04,581 [classy] Setting parameters: {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,626 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.67614014801873}
 2023-07-02 10:34:04,626 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,628 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108782
 2023-07-02 10:34:04,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47142889445348024, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,628 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,648 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08489
 2023-07-02 10:34:04,648 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,648 [mcmc] New sample, #419:
   Omega_m:0.316949, b1:0.4839032
 2023-07-02 10:34:04,648 [model] Posterior to be computed for parameters {'Omega_m': 0.32589804097134906, 'b1': 0.5137782996889283}
 2023-07-02 10:34:04,648 [prior] Evaluating prior at array([0.32589804, 0.5137783 ])
 2023-07-02 10:34:04,649 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,649 [model] Got input parameters: {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5137782996889283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,649 [classy] Got parameters {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,649 [classy] Re-using computed results
 2023-07-02 10:34:04,649 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.67614014801873}
 2023-07-02 10:34:04,649 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,649 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5137782996889283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,649 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,668 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.792217
 2023-07-02 10:34:04,668 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,668 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.48470905973104295}
 2023-07-02 10:34:04,668 [prior] Evaluating prior at array([0.31637086, 0.48470906])
 2023-07-02 10:34:04,669 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,669 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48470905973104295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,669 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,669 [classy] Computing new state
 2023-07-02 10:34:04,669 [classy] Setting parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
 2023-07-02 10:34:04,714 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00111996
 2023-07-02 10:34:04,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48470905973104295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,716 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,735 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45826
 2023-07-02 10:34:04,736 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,736 [mcmc] New sample, #420:
   Omega_m:0.325898, b1:0.4714289
 2023-07-02 10:34:04,736 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.48312182821580857}
 2023-07-02 10:34:04,736 [prior] Evaluating prior at array([0.31637086, 0.48312183])
 2023-07-02 10:34:04,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,736 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48312182821580857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,736 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,736 [classy] Re-using computed results
 2023-07-02 10:34:04,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
 2023-07-02 10:34:04,736 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48312182821580857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,736 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34126
 2023-07-02 10:34:04,756 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,756 [mcmc] New sample, #421:
   Omega_m:0.3163709, b1:0.4847091
 2023-07-02 10:34:04,756 [model] Posterior to be computed for parameters {'Omega_m': 0.3083662635758382, 'b1': 0.4942796341017114}
 2023-07-02 10:34:04,756 [prior] Evaluating prior at array([0.30836626, 0.49427963])
 2023-07-02 10:34:04,757 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,757 [model] Got input parameters: {'Omega_m': 0.3083662635758382, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4942796341017114, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,757 [classy] Got parameters {'Omega_m': 0.3083662635758382, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,757 [classy] Computing new state
 2023-07-02 10:34:04,757 [classy] Setting parameters: {'Omega_m': 0.3083662635758382, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7585251002326}
 2023-07-02 10:34:04,801 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,803 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00125294
 2023-07-02 10:34:04,803 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4942796341017114, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,803 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.794
 2023-07-02 10:34:04,822 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,822 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.4737469066584642}
 2023-07-02 10:34:04,822 [prior] Evaluating prior at array([0.31637086, 0.47374691])
 2023-07-02 10:34:04,823 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,823 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4737469066584642, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,823 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,823 [classy] Re-using computed results
 2023-07-02 10:34:04,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
 2023-07-02 10:34:04,823 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,823 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4737469066584642, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,823 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3871
 2023-07-02 10:34:04,843 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,843 [model] Posterior to be computed for parameters {'Omega_m': 0.2934834937149975, 'b1': 0.5150250891965752}
 2023-07-02 10:34:04,843 [prior] Evaluating prior at array([0.29348349, 0.51502509])
 2023-07-02 10:34:04,843 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,843 [model] Got input parameters: {'Omega_m': 0.2934834937149975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150250891965752, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,843 [classy] Got parameters {'Omega_m': 0.2934834937149975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,843 [classy] Computing new state
 2023-07-02 10:34:04,843 [classy] Setting parameters: {'Omega_m': 0.2934834937149975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,887 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.61012445332122}
 2023-07-02 10:34:04,887 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,889 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0234329
 2023-07-02 10:34:04,889 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150250891965752, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,889 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,909 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.50512
 2023-07-02 10:34:04,909 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,909 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.5371521561629854}
 2023-07-02 10:34:04,909 [prior] Evaluating prior at array([0.31637086, 0.53715216])
 2023-07-02 10:34:04,910 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,910 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5371521561629854, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,910 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,910 [classy] Re-using computed results
 2023-07-02 10:34:04,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
 2023-07-02 10:34:04,910 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5371521561629854, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,910 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,929 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.41567
 2023-07-02 10:34:04,929 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,929 [model] Posterior to be computed for parameters {'Omega_m': 0.33604736747089414, 'b1': 0.4556942697373722}
 2023-07-02 10:34:04,929 [prior] Evaluating prior at array([0.33604737, 0.45569427])
 2023-07-02 10:34:04,929 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,929 [model] Got input parameters: {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4556942697373722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,930 [classy] Got parameters {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,930 [classy] Computing new state
 2023-07-02 10:34:04,930 [classy] Setting parameters: {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:04,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.51610835098884}
 2023-07-02 10:34:04,974 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:04,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0323514
 2023-07-02 10:34:04,976 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4556942697373722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,976 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:04,996 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.571823
 2023-07-02 10:34:04,996 [model] Computed derived parameters: {}
 2023-07-02 10:34:04,997 [mcmc] New sample, #422:
   Omega_m:0.3163709, b1:0.4831218
 2023-07-02 10:34:04,997 [model] Posterior to be computed for parameters {'Omega_m': 0.33604736747089414, 'b1': 0.4223908499530782}
 2023-07-02 10:34:04,997 [prior] Evaluating prior at array([0.33604737, 0.42239085])
 2023-07-02 10:34:04,997 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:04,997 [model] Got input parameters: {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4223908499530782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,997 [classy] Got parameters {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:04,997 [classy] Re-using computed results
 2023-07-02 10:34:04,997 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.51610835098884}
 2023-07-02 10:34:04,997 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:04,997 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4223908499530782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:04,997 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,016 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.49459
 2023-07-02 10:34:05,017 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,017 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.46722520891072716}
 2023-07-02 10:34:05,017 [prior] Evaluating prior at array([0.32777508, 0.46722521])
 2023-07-02 10:34:05,017 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,017 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46722520891072716, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,017 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,017 [classy] Computing new state
 2023-07-02 10:34:05,017 [classy] Setting parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
 2023-07-02 10:34:05,061 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,063 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0140125
 2023-07-02 10:34:05,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46722520891072716, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,063 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,082 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81509
 2023-07-02 10:34:05,083 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,083 [mcmc] New sample, #423:
   Omega_m:0.3360474, b1:0.4556943
 2023-07-02 10:34:05,083 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.5099399218688974}
 2023-07-02 10:34:05,083 [prior] Evaluating prior at array([0.32777508, 0.50993992])
 2023-07-02 10:34:05,083 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,083 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5099399218688974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,083 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,083 [classy] Re-using computed results
 2023-07-02 10:34:05,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
 2023-07-02 10:34:05,083 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5099399218688974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,083 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,103 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.942709
 2023-07-02 10:34:05,103 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,104 [model] Posterior to be computed for parameters {'Omega_m': 0.35809088608210493, 'b1': 0.424967272695987}
 2023-07-02 10:34:05,104 [prior] Evaluating prior at array([0.35809089, 0.42496727])
 2023-07-02 10:34:05,104 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,104 [model] Got input parameters: {'Omega_m': 0.35809088608210493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.424967272695987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,104 [classy] Got parameters {'Omega_m': 0.35809088608210493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,104 [classy] Computing new state
 2023-07-02 10:34:05,104 [classy] Setting parameters: {'Omega_m': 0.35809088608210493, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.10258903764918}
 2023-07-02 10:34:05,151 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.114603
 2023-07-02 10:34:05,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.424967272695987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,153 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,172 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.7109
 2023-07-02 10:34:05,172 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,172 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.48630417432039663}
 2023-07-02 10:34:05,172 [prior] Evaluating prior at array([0.32777508, 0.48630417])
 2023-07-02 10:34:05,172 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,172 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48630417432039663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,172 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,172 [classy] Re-using computed results
 2023-07-02 10:34:05,172 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
 2023-07-02 10:34:05,172 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,172 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48630417432039663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,172 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,191 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.85339
 2023-07-02 10:34:05,191 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,191 [mcmc] New sample, #424:
   Omega_m:0.3277751, b1:0.4672252
 2023-07-02 10:34:05,191 [model] Posterior to be computed for parameters {'Omega_m': 0.3425830189674795, 'b1': 0.46566303147488514}
 2023-07-02 10:34:05,191 [prior] Evaluating prior at array([0.34258302, 0.46566303])
 2023-07-02 10:34:05,192 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,192 [model] Got input parameters: {'Omega_m': 0.3425830189674795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46566303147488514, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,192 [classy] Got parameters {'Omega_m': 0.3425830189674795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,192 [classy] Computing new state
 2023-07-02 10:34:05,192 [classy] Setting parameters: {'Omega_m': 0.3425830189674795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.78577393074937}
 2023-07-02 10:34:05,236 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0518552
 2023-07-02 10:34:05,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46566303147488514, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,238 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,258 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.47966
 2023-07-02 10:34:05,258 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,258 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.5763700021532966}
 2023-07-02 10:34:05,258 [prior] Evaluating prior at array([0.32777508, 0.57637   ])
 2023-07-02 10:34:05,258 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,259 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5763700021532966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,259 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,259 [classy] Re-using computed results
 2023-07-02 10:34:05,259 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
 2023-07-02 10:34:05,259 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,259 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5763700021532966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,259 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,278 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.5378
 2023-07-02 10:34:05,278 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,278 [model] Posterior to be computed for parameters {'Omega_m': 0.31312902878619187, 'b1': 0.5067196651784145}
 2023-07-02 10:34:05,278 [prior] Evaluating prior at array([0.31312903, 0.50671967])
 2023-07-02 10:34:05,279 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,279 [model] Got input parameters: {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5067196651784145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,279 [classy] Got parameters {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,279 [classy] Computing new state
 2023-07-02 10:34:05,279 [classy] Setting parameters: {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1825790993551}
 2023-07-02 10:34:05,324 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,325 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000227853
 2023-07-02 10:34:05,325 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5067196651784145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,325 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,345 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87872
 2023-07-02 10:34:05,345 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,345 [mcmc] New sample, #425:
   Omega_m:0.3277751, b1:0.4863042
 2023-07-02 10:34:05,345 [model] Posterior to be computed for parameters {'Omega_m': 0.31312902878619187, 'b1': 0.5295502551689203}
 2023-07-02 10:34:05,345 [prior] Evaluating prior at array([0.31312903, 0.52955026])
 2023-07-02 10:34:05,345 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,345 [model] Got input parameters: {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5295502551689203, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,345 [classy] Got parameters {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,346 [classy] Re-using computed results
 2023-07-02 10:34:05,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1825790993551}
 2023-07-02 10:34:05,346 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,346 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5295502551689203, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,346 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.06376
 2023-07-02 10:34:05,366 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,366 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.49115048447936255}
 2023-07-02 10:34:05,366 [prior] Evaluating prior at array([0.32429834, 0.49115048])
 2023-07-02 10:34:05,366 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,366 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49115048447936255, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,366 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,366 [classy] Computing new state
 2023-07-02 10:34:05,366 [classy] Setting parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
 2023-07-02 10:34:05,411 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00851573
 2023-07-02 10:34:05,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49115048447936255, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,413 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.31677
 2023-07-02 10:34:05,432 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,433 [mcmc] New sample, #426:
   Omega_m:0.313129, b1:0.5067197
 2023-07-02 10:34:05,433 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.48479078979105206}
 2023-07-02 10:34:05,433 [prior] Evaluating prior at array([0.32429834, 0.48479079])
 2023-07-02 10:34:05,433 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,433 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48479078979105206, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,433 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,433 [classy] Re-using computed results
 2023-07-02 10:34:05,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
 2023-07-02 10:34:05,433 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,433 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48479078979105206, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,433 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,453 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47338
 2023-07-02 10:34:05,453 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,453 [mcmc] New sample, #427:
   Omega_m:0.3242983, b1:0.4911505
 2023-07-02 10:34:05,453 [model] Posterior to be computed for parameters {'Omega_m': 0.3014323398031338, 'b1': 0.5166642699132299}
 2023-07-02 10:34:05,453 [prior] Evaluating prior at array([0.30143234, 0.51666427])
 2023-07-02 10:34:05,453 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,453 [model] Got input parameters: {'Omega_m': 0.3014323398031338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166642699132299, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,453 [classy] Got parameters {'Omega_m': 0.3014323398031338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,453 [classy] Computing new state
 2023-07-02 10:34:05,454 [classy] Setting parameters: {'Omega_m': 0.3014323398031338, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,497 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6111806003106}
 2023-07-02 10:34:05,497 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,499 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00790283
 2023-07-02 10:34:05,499 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166642699132299, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,499 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,519 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61623
 2023-07-02 10:34:05,520 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,520 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.47656639997746075}
 2023-07-02 10:34:05,520 [prior] Evaluating prior at array([0.32429834, 0.4765664 ])
 2023-07-02 10:34:05,520 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,520 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47656639997746075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,520 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,520 [classy] Re-using computed results
 2023-07-02 10:34:05,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
 2023-07-02 10:34:05,520 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,520 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47656639997746075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,520 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,539 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34907
 2023-07-02 10:34:05,539 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,539 [mcmc] New sample, #428:
   Omega_m:0.3242983, b1:0.4847908
 2023-07-02 10:34:05,539 [model] Posterior to be computed for parameters {'Omega_m': 0.3360538096699194, 'b1': 0.46018017070714184}
 2023-07-02 10:34:05,539 [prior] Evaluating prior at array([0.33605381, 0.46018017])
 2023-07-02 10:34:05,539 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,539 [model] Got input parameters: {'Omega_m': 0.3360538096699194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46018017070714184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,539 [classy] Got parameters {'Omega_m': 0.3360538096699194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,539 [classy] Computing new state
 2023-07-02 10:34:05,539 [classy] Setting parameters: {'Omega_m': 0.3360538096699194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,583 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5153848597415}
 2023-07-02 10:34:05,584 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,585 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0323683
 2023-07-02 10:34:05,585 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46018017070714184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,585 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,605 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.675345
 2023-07-02 10:34:05,606 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,606 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.44185797451107567}
 2023-07-02 10:34:05,606 [prior] Evaluating prior at array([0.32429834, 0.44185797])
 2023-07-02 10:34:05,606 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,606 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44185797451107567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,606 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,606 [classy] Re-using computed results
 2023-07-02 10:34:05,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
 2023-07-02 10:34:05,606 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,606 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44185797451107567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,606 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,626 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.03735
 2023-07-02 10:34:05,626 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,626 [model] Posterior to be computed for parameters {'Omega_m': 0.3220460171658156, 'b1': 0.4797059735710746}
 2023-07-02 10:34:05,626 [prior] Evaluating prior at array([0.32204602, 0.47970597])
 2023-07-02 10:34:05,626 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,626 [model] Got input parameters: {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4797059735710746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,626 [classy] Got parameters {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,626 [classy] Computing new state
 2023-07-02 10:34:05,626 [classy] Setting parameters: {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,671 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12495502141198}
 2023-07-02 10:34:05,671 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,672 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00567803
 2023-07-02 10:34:05,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4797059735710746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,673 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50397
 2023-07-02 10:34:05,692 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,692 [mcmc] New sample, #429:
   Omega_m:0.3242983, b1:0.4765664
 2023-07-02 10:34:05,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3220460171658156, 'b1': 0.4908066089867971}
 2023-07-02 10:34:05,692 [prior] Evaluating prior at array([0.32204602, 0.49080661])
 2023-07-02 10:34:05,692 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,692 [model] Got input parameters: {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4908066089867971, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,692 [classy] Got parameters {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,692 [classy] Re-using computed results
 2023-07-02 10:34:05,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12495502141198}
 2023-07-02 10:34:05,692 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,692 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4908066089867971, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,692 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,713 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64146
 2023-07-02 10:34:05,713 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,713 [mcmc] New sample, #430:
   Omega_m:0.322046, b1:0.479706
 2023-07-02 10:34:05,713 [model] Posterior to be computed for parameters {'Omega_m': 0.32222984978187114, 'b1': 0.4905503602295422}
 2023-07-02 10:34:05,713 [prior] Evaluating prior at array([0.32222985, 0.49055036])
 2023-07-02 10:34:05,714 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,714 [model] Got input parameters: {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4905503602295422, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,714 [classy] Got parameters {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,714 [classy] Computing new state
 2023-07-02 10:34:05,714 [classy] Setting parameters: {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10342687864693}
 2023-07-02 10:34:05,758 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00588806
 2023-07-02 10:34:05,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4905503602295422, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,760 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,779 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62634
 2023-07-02 10:34:05,779 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,779 [mcmc] New sample, #431:
   Omega_m:0.322046, b1:0.4908066
 2023-07-02 10:34:05,779 [model] Posterior to be computed for parameters {'Omega_m': 0.32222984978187114, 'b1': 0.4386008599452459}
 2023-07-02 10:34:05,779 [prior] Evaluating prior at array([0.32222985, 0.43860086])
 2023-07-02 10:34:05,780 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,780 [model] Got input parameters: {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4386008599452459, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,780 [classy] Got parameters {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,780 [classy] Re-using computed results
 2023-07-02 10:34:05,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10342687864693}
 2023-07-02 10:34:05,780 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4386008599452459, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,780 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.4526
 2023-07-02 10:34:05,799 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,799 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.5075745323606417}
 2023-07-02 10:34:05,799 [prior] Evaluating prior at array([0.31001672, 0.50757453])
 2023-07-02 10:34:05,799 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,799 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5075745323606417, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,799 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,799 [classy] Computing new state
 2023-07-02 10:34:05,799 [classy] Setting parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
 2023-07-02 10:34:05,844 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000577993
 2023-07-02 10:34:05,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5075745323606417, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,846 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,866 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76395
 2023-07-02 10:34:05,866 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,866 [mcmc] New sample, #432:
   Omega_m:0.3222298, b1:0.4905504
 2023-07-02 10:34:05,866 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.5143342659358193}
 2023-07-02 10:34:05,866 [prior] Evaluating prior at array([0.31001672, 0.51433427])
 2023-07-02 10:34:05,866 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,866 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5143342659358193, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,866 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,866 [classy] Re-using computed results
 2023-07-02 10:34:05,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
 2023-07-02 10:34:05,866 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5143342659358193, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,866 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70712
 2023-07-02 10:34:05,886 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,886 [mcmc] New sample, #433:
   Omega_m:0.3100167, b1:0.5075745
 2023-07-02 10:34:05,886 [model] Posterior to be computed for parameters {'Omega_m': 0.30989425902720447, 'b1': 0.5145049739555508}
 2023-07-02 10:34:05,886 [prior] Evaluating prior at array([0.30989426, 0.51450497])
 2023-07-02 10:34:05,886 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,886 [model] Got input parameters: {'Omega_m': 0.30989425902720447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5145049739555508, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,886 [classy] Got parameters {'Omega_m': 0.30989425902720447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,886 [classy] Computing new state
 2023-07-02 10:34:05,886 [classy] Setting parameters: {'Omega_m': 0.30989425902720447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:05,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57289880602522}
 2023-07-02 10:34:05,931 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:05,933 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000616333
 2023-07-02 10:34:05,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5145049739555508, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,933 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,952 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70105
 2023-07-02 10:34:05,952 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,952 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.538817009340583}
 2023-07-02 10:34:05,952 [prior] Evaluating prior at array([0.31001672, 0.53881701])
 2023-07-02 10:34:05,952 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,952 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.538817009340583, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,953 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,953 [classy] Re-using computed results
 2023-07-02 10:34:05,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
 2023-07-02 10:34:05,953 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:05,953 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.538817009340583, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,953 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:05,973 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.381591
 2023-07-02 10:34:05,973 [model] Computed derived parameters: {}
 2023-07-02 10:34:05,973 [model] Posterior to be computed for parameters {'Omega_m': 0.27608633747569594, 'b1': 0.5616306585529394}
 2023-07-02 10:34:05,973 [prior] Evaluating prior at array([0.27608634, 0.56163066])
 2023-07-02 10:34:05,973 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:05,973 [model] Got input parameters: {'Omega_m': 0.27608633747569594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5616306585529394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:05,973 [classy] Got parameters {'Omega_m': 0.27608633747569594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:05,973 [classy] Computing new state
 2023-07-02 10:34:05,973 [classy] Setting parameters: {'Omega_m': 0.27608633747569594, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,018 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.8809625887398}
 2023-07-02 10:34:06,018 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0894367
 2023-07-02 10:34:06,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5616306585529394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,020 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,039 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.41703
 2023-07-02 10:34:06,039 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,039 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.49940547469073926}
 2023-07-02 10:34:06,040 [prior] Evaluating prior at array([0.31001672, 0.49940547])
 2023-07-02 10:34:06,040 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,040 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49940547469073926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,040 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,040 [classy] Re-using computed results
 2023-07-02 10:34:06,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
 2023-07-02 10:34:06,040 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49940547469073926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,060 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50766
 2023-07-02 10:34:06,060 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,060 [mcmc] New sample, #434:
   Omega_m:0.3100167, b1:0.5143343
 2023-07-02 10:34:06,060 [model] Posterior to be computed for parameters {'Omega_m': 0.3249515500374706, 'b1': 0.47858745833829075}
 2023-07-02 10:34:06,060 [prior] Evaluating prior at array([0.32495155, 0.47858746])
 2023-07-02 10:34:06,060 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,060 [model] Got input parameters: {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47858745833829075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,060 [classy] Got parameters {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,060 [classy] Computing new state
 2023-07-02 10:34:06,061 [classy] Setting parameters: {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.78597883720485}
 2023-07-02 10:34:06,104 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,105 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00944588
 2023-07-02 10:34:06,105 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47858745833829075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,106 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,128 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37557
 2023-07-02 10:34:06,128 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,128 [mcmc] New sample, #435:
   Omega_m:0.3100167, b1:0.4994055
 2023-07-02 10:34:06,128 [model] Posterior to be computed for parameters {'Omega_m': 0.3249515500374706, 'b1': 0.5088432835794311}
 2023-07-02 10:34:06,128 [prior] Evaluating prior at array([0.32495155, 0.50884328])
 2023-07-02 10:34:06,128 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,128 [model] Got input parameters: {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088432835794311, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,128 [classy] Got parameters {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,128 [classy] Re-using computed results
 2023-07-02 10:34:06,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.78597883720485}
 2023-07-02 10:34:06,128 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088432835794311, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,128 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,148 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.443267
 2023-07-02 10:34:06,148 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3118271771316707, 'b1': 0.4968818411253225}
 2023-07-02 10:34:06,149 [prior] Evaluating prior at array([0.31182718, 0.49688184])
 2023-07-02 10:34:06,149 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,149 [model] Got input parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4968818411253225, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,149 [classy] Got parameters {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,149 [classy] Computing new state
 2023-07-02 10:34:06,149 [classy] Setting parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.3392356478298}
 2023-07-02 10:34:06,193 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,194 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000228865
 2023-07-02 10:34:06,195 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4968818411253225, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,195 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,215 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63544
 2023-07-02 10:34:06,215 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,215 [mcmc] New sample, #436:
   Omega_m:0.3249516, b1:0.4785875
 2023-07-02 10:34:06,215 [model] Posterior to be computed for parameters {'Omega_m': 0.3118271771316707, 'b1': 0.4760947075359782}
 2023-07-02 10:34:06,215 [prior] Evaluating prior at array([0.31182718, 0.47609471])
 2023-07-02 10:34:06,215 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,215 [model] Got input parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4760947075359782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,215 [classy] Got parameters {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,215 [classy] Re-using computed results
 2023-07-02 10:34:06,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.3392356478298}
 2023-07-02 10:34:06,215 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,215 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4760947075359782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,215 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,235 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.512868
 2023-07-02 10:34:06,235 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,235 [model] Posterior to be computed for parameters {'Omega_m': 0.3014546849732174, 'b1': 0.5113403103690889}
 2023-07-02 10:34:06,235 [prior] Evaluating prior at array([0.30145468, 0.51134031])
 2023-07-02 10:34:06,235 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,235 [model] Got input parameters: {'Omega_m': 0.3014546849732174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5113403103690889, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,235 [classy] Got parameters {'Omega_m': 0.3014546849732174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,235 [classy] Computing new state
 2023-07-02 10:34:06,235 [classy] Setting parameters: {'Omega_m': 0.3014546849732174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60840226177444}
 2023-07-02 10:34:06,279 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,281 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00787122
 2023-07-02 10:34:06,281 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5113403103690889, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,281 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,300 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.31702
 2023-07-02 10:34:06,301 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,301 [model] Posterior to be computed for parameters {'Omega_m': 0.3118271771316707, 'b1': 0.5152149635920344}
 2023-07-02 10:34:06,301 [prior] Evaluating prior at array([0.31182718, 0.51521496])
 2023-07-02 10:34:06,301 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,301 [model] Got input parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5152149635920344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,301 [classy] Got parameters {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,301 [classy] Re-using computed results
 2023-07-02 10:34:06,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.3392356478298}
 2023-07-02 10:34:06,301 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,301 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5152149635920344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,301 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,321 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63729
 2023-07-02 10:34:06,321 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,322 [mcmc] New sample, #437:
   Omega_m:0.3118272, b1:0.4968818
 2023-07-02 10:34:06,322 [model] Posterior to be computed for parameters {'Omega_m': 0.3082950458812129, 'b1': 0.5201384872996971}
 2023-07-02 10:34:06,322 [prior] Evaluating prior at array([0.30829505, 0.52013849])
 2023-07-02 10:34:06,322 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,322 [model] Got input parameters: {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5201384872996971, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,322 [classy] Got parameters {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,322 [classy] Computing new state
 2023-07-02 10:34:06,322 [classy] Setting parameters: {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.76719924405833}
 2023-07-02 10:34:06,366 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0012898
 2023-07-02 10:34:06,368 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5201384872996971, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,368 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,387 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49495
 2023-07-02 10:34:06,387 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,387 [mcmc] New sample, #438:
   Omega_m:0.3118272, b1:0.515215
 2023-07-02 10:34:06,388 [model] Posterior to be computed for parameters {'Omega_m': 0.3082950458812129, 'b1': 0.5858109236054713}
 2023-07-02 10:34:06,388 [prior] Evaluating prior at array([0.30829505, 0.58581092])
 2023-07-02 10:34:06,388 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,388 [model] Got input parameters: {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5858109236054713, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,388 [classy] Got parameters {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,388 [classy] Re-using computed results
 2023-07-02 10:34:06,388 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.76719924405833}
 2023-07-02 10:34:06,388 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,388 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5858109236054713, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,388 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,407 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.8145
 2023-07-02 10:34:06,407 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.49975045309432065}
 2023-07-02 10:34:06,407 [prior] Evaluating prior at array([0.3229214 , 0.49975045])
 2023-07-02 10:34:06,407 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,407 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49975045309432065, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,407 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,407 [classy] Computing new state
 2023-07-02 10:34:06,407 [classy] Setting parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
 2023-07-02 10:34:06,452 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00671259
 2023-07-02 10:34:06,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49975045309432065, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,454 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,474 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07901
 2023-07-02 10:34:06,474 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,474 [mcmc] New sample, #439:
   Omega_m:0.308295, b1:0.5201385
 2023-07-02 10:34:06,474 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.5044271318857968}
 2023-07-02 10:34:06,474 [prior] Evaluating prior at array([0.3229214 , 0.50442713])
 2023-07-02 10:34:06,474 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,474 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5044271318857968, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,474 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,474 [classy] Re-using computed results
 2023-07-02 10:34:06,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
 2023-07-02 10:34:06,474 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5044271318857968, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,474 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,494 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65956
 2023-07-02 10:34:06,494 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,494 [mcmc] New sample, #440:
   Omega_m:0.3229214, b1:0.4997505
 2023-07-02 10:34:06,494 [model] Posterior to be computed for parameters {'Omega_m': 0.34910255453412325, 'b1': 0.4679325866917767}
 2023-07-02 10:34:06,494 [prior] Evaluating prior at array([0.34910255, 0.46793259])
 2023-07-02 10:34:06,494 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,494 [model] Got input parameters: {'Omega_m': 0.34910255453412325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4679325866917767, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,494 [classy] Got parameters {'Omega_m': 0.34910255453412325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,494 [classy] Computing new state
 2023-07-02 10:34:06,494 [classy] Setting parameters: {'Omega_m': 0.34910255453412325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0698249072638}
 2023-07-02 10:34:06,539 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0754971
 2023-07-02 10:34:06,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4679325866917767, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,541 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,560 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.11247
 2023-07-02 10:34:06,560 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.49478342003794146}
 2023-07-02 10:34:06,560 [prior] Evaluating prior at array([0.3229214 , 0.49478342])
 2023-07-02 10:34:06,561 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,561 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49478342003794146, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,561 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,561 [classy] Re-using computed results
 2023-07-02 10:34:06,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
 2023-07-02 10:34:06,561 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49478342003794146, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,561 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,581 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38898
 2023-07-02 10:34:06,581 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,581 [mcmc] New sample, #441:
   Omega_m:0.3229214, b1:0.5044271
 2023-07-02 10:34:06,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3315148786976918, 'b1': 0.4828047642045259}
 2023-07-02 10:34:06,581 [prior] Evaluating prior at array([0.33151488, 0.48280476])
 2023-07-02 10:34:06,581 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,581 [model] Got input parameters: {'Omega_m': 0.3315148786976918, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4828047642045259, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,581 [classy] Got parameters {'Omega_m': 0.3315148786976918, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,581 [classy] Computing new state
 2023-07-02 10:34:06,581 [classy] Setting parameters: {'Omega_m': 0.3315148786976918, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.03017721815698}
 2023-07-02 10:34:06,631 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,633 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0214019
 2023-07-02 10:34:06,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4828047642045259, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,633 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,653 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10299
 2023-07-02 10:34:06,653 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,653 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.5185863690684723}
 2023-07-02 10:34:06,653 [prior] Evaluating prior at array([0.3229214 , 0.51858637])
 2023-07-02 10:34:06,653 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,653 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5185863690684723, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,653 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,653 [classy] Re-using computed results
 2023-07-02 10:34:06,653 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
 2023-07-02 10:34:06,653 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5185863690684723, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,653 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,673 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.382806
 2023-07-02 10:34:06,673 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,673 [model] Posterior to be computed for parameters {'Omega_m': 0.3497890450650079, 'b1': 0.4573319589865453}
 2023-07-02 10:34:06,673 [prior] Evaluating prior at array([0.34978905, 0.45733196])
 2023-07-02 10:34:06,674 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,674 [model] Got input parameters: {'Omega_m': 0.3497890450650079, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4573319589865453, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,674 [classy] Got parameters {'Omega_m': 0.3497890450650079, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,674 [classy] Computing new state
 2023-07-02 10:34:06,674 [classy] Setting parameters: {'Omega_m': 0.3497890450650079, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.99515005443737}
 2023-07-02 10:34:06,718 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,720 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0782222
 2023-07-02 10:34:06,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4573319589865453, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,720 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,739 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.00041
 2023-07-02 10:34:06,739 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,739 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.49499917217634587}
 2023-07-02 10:34:06,739 [prior] Evaluating prior at array([0.3229214 , 0.49499917])
 2023-07-02 10:34:06,740 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,740 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49499917217634587, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,740 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,740 [classy] Re-using computed results
 2023-07-02 10:34:06,740 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
 2023-07-02 10:34:06,740 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49499917217634587, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,740 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,759 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37839
 2023-07-02 10:34:06,759 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,759 [mcmc] New sample, #442:
   Omega_m:0.3229214, b1:0.4947834
 2023-07-02 10:34:06,759 [model] Posterior to be computed for parameters {'Omega_m': 0.3681696713573728, 'b1': 0.43192650882664385}
 2023-07-02 10:34:06,759 [prior] Evaluating prior at array([0.36816967, 0.43192651])
 2023-07-02 10:34:06,759 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,759 [model] Got input parameters: {'Omega_m': 0.3681696713573728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43192650882664385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,759 [classy] Got parameters {'Omega_m': 0.3681696713573728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,759 [classy] Computing new state
 2023-07-02 10:34:06,759 [classy] Setting parameters: {'Omega_m': 0.3681696713573728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,804 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.04436631648474}
 2023-07-02 10:34:06,804 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.166897
 2023-07-02 10:34:06,806 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43192650882664385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,806 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,826 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.8114
 2023-07-02 10:34:06,826 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,827 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.5261150297188976}
 2023-07-02 10:34:06,827 [prior] Evaluating prior at array([0.3229214 , 0.52611503])
 2023-07-02 10:34:06,827 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,827 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5261150297188976, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,827 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,827 [classy] Re-using computed results
 2023-07-02 10:34:06,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
 2023-07-02 10:34:06,827 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5261150297188976, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,827 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,846 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.95387
 2023-07-02 10:34:06,846 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,847 [model] Posterior to be computed for parameters {'Omega_m': 0.2980687567885744, 'b1': 0.5296418796140641}
 2023-07-02 10:34:06,847 [prior] Evaluating prior at array([0.29806876, 0.52964188])
 2023-07-02 10:34:06,847 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,847 [model] Got input parameters: {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5296418796140641, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,847 [classy] Got parameters {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,847 [classy] Computing new state
 2023-07-02 10:34:06,847 [classy] Setting parameters: {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.031043964446}
 2023-07-02 10:34:06,891 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,893 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0134167
 2023-07-02 10:34:06,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5296418796140641, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,893 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,912 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14966
 2023-07-02 10:34:06,913 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,913 [mcmc] New sample, #443:
   Omega_m:0.3229214, b1:0.4949992
 2023-07-02 10:34:06,913 [model] Posterior to be computed for parameters {'Omega_m': 0.2980687567885744, 'b1': 0.5079828640795473}
 2023-07-02 10:34:06,913 [prior] Evaluating prior at array([0.29806876, 0.50798286])
 2023-07-02 10:34:06,913 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,913 [model] Got input parameters: {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5079828640795473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,913 [classy] Got parameters {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,913 [classy] Re-using computed results
 2023-07-02 10:34:06,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.031043964446}
 2023-07-02 10:34:06,913 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:06,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5079828640795473, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,913 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:06,933 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.227347
 2023-07-02 10:34:06,934 [model] Computed derived parameters: {}
 2023-07-02 10:34:06,934 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.48786213131900236}
 2023-07-02 10:34:06,934 [prior] Evaluating prior at array([0.32804151, 0.48786213])
 2023-07-02 10:34:06,934 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:06,934 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48786213131900236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,934 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:06,934 [classy] Computing new state
 2023-07-02 10:34:06,934 [classy] Setting parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:06,979 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
 2023-07-02 10:34:06,979 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:06,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0144888
 2023-07-02 10:34:06,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48786213131900236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:06,981 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,000 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70351
 2023-07-02 10:34:07,000 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,000 [mcmc] New sample, #444:
   Omega_m:0.2980688, b1:0.5296419
 2023-07-02 10:34:07,000 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.463989468971631}
 2023-07-02 10:34:07,000 [prior] Evaluating prior at array([0.32804151, 0.46398947])
 2023-07-02 10:34:07,000 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,000 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.463989468971631, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,000 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,000 [classy] Re-using computed results
 2023-07-02 10:34:07,000 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
 2023-07-02 10:34:07,000 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,000 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.463989468971631, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,000 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,022 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61262
 2023-07-02 10:34:07,022 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,022 [mcmc] New sample, #445:
   Omega_m:0.3280415, b1:0.4878621
 2023-07-02 10:34:07,022 [model] Posterior to be computed for parameters {'Omega_m': 0.3717712235667876, 'b1': 0.4030335552074969}
 2023-07-02 10:34:07,022 [prior] Evaluating prior at array([0.37177122, 0.40303356])
 2023-07-02 10:34:07,023 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,023 [model] Got input parameters: {'Omega_m': 0.3717712235667876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4030335552074969, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,023 [classy] Got parameters {'Omega_m': 0.3717712235667876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,023 [classy] Computing new state
 2023-07-02 10:34:07,023 [classy] Setting parameters: {'Omega_m': 0.3717712235667876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,067 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.67272794665297}
 2023-07-02 10:34:07,067 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,069 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.187639
 2023-07-02 10:34:07,069 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4030335552074969, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,069 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,089 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2787
 2023-07-02 10:34:07,089 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,089 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.4672750152650727}
 2023-07-02 10:34:07,089 [prior] Evaluating prior at array([0.32804151, 0.46727502])
 2023-07-02 10:34:07,089 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,090 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4672750152650727, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,090 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,090 [classy] Re-using computed results
 2023-07-02 10:34:07,090 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
 2023-07-02 10:34:07,090 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,090 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4672750152650727, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,090 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,109 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.80762
 2023-07-02 10:34:07,109 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,109 [mcmc] New sample, #446:
   Omega_m:0.3280415, b1:0.4639895
 2023-07-02 10:34:07,109 [model] Posterior to be computed for parameters {'Omega_m': 0.36920293127548787, 'b1': 0.40989910662752693}
 2023-07-02 10:34:07,109 [prior] Evaluating prior at array([0.36920293, 0.40989911])
 2023-07-02 10:34:07,109 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,109 [model] Got input parameters: {'Omega_m': 0.36920293127548787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40989910662752693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,109 [classy] Got parameters {'Omega_m': 0.36920293127548787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,109 [classy] Computing new state
 2023-07-02 10:34:07,109 [classy] Setting parameters: {'Omega_m': 0.36920293127548787, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.9374004605944}
 2023-07-02 10:34:07,156 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17274
 2023-07-02 10:34:07,158 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40989910662752693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,158 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,179 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2447
 2023-07-02 10:34:07,179 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,179 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.4434428287146425}
 2023-07-02 10:34:07,179 [prior] Evaluating prior at array([0.32804151, 0.44344283])
 2023-07-02 10:34:07,179 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,179 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4434428287146425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,179 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,179 [classy] Re-using computed results
 2023-07-02 10:34:07,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
 2023-07-02 10:34:07,180 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4434428287146425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,180 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,199 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.868996
 2023-07-02 10:34:07,199 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,200 [model] Posterior to be computed for parameters {'Omega_m': 0.278283244623468, 'b1': 0.5366342704656394}
 2023-07-02 10:34:07,200 [prior] Evaluating prior at array([0.27828324, 0.53663427])
 2023-07-02 10:34:07,200 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,200 [model] Got input parameters: {'Omega_m': 0.278283244623468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366342704656394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,200 [classy] Got parameters {'Omega_m': 0.278283244623468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,200 [classy] Computing new state
 2023-07-02 10:34:07,200 [classy] Setting parameters: {'Omega_m': 0.278283244623468, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,244 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.58753461005762}
 2023-07-02 10:34:07,245 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,246 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0785294
 2023-07-02 10:34:07,246 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366342704656394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,246 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.30916
 2023-07-02 10:34:07,266 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,266 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.5094437424078074}
 2023-07-02 10:34:07,266 [prior] Evaluating prior at array([0.32804151, 0.50944374])
 2023-07-02 10:34:07,266 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,266 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5094437424078074, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,266 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,266 [classy] Re-using computed results
 2023-07-02 10:34:07,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
 2023-07-02 10:34:07,266 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5094437424078074, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,266 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.975973
 2023-07-02 10:34:07,287 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,287 [model] Posterior to be computed for parameters {'Omega_m': 0.30635373500913804, 'b1': 0.4975061307959563}
 2023-07-02 10:34:07,287 [prior] Evaluating prior at array([0.30635374, 0.49750613])
 2023-07-02 10:34:07,287 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,287 [model] Got input parameters: {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4975061307959563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,287 [classy] Got parameters {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,287 [classy] Computing new state
 2023-07-02 10:34:07,287 [classy] Setting parameters: {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00425673038194}
 2023-07-02 10:34:07,332 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,333 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00254259
 2023-07-02 10:34:07,333 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4975061307959563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,334 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,353 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.56866
 2023-07-02 10:34:07,353 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,353 [mcmc] New sample, #447:
   Omega_m:0.3280415, b1:0.467275
 2023-07-02 10:34:07,353 [model] Posterior to be computed for parameters {'Omega_m': 0.30635373500913804, 'b1': 0.5207632374945664}
 2023-07-02 10:34:07,353 [prior] Evaluating prior at array([0.30635374, 0.52076324])
 2023-07-02 10:34:07,353 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,353 [model] Got input parameters: {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5207632374945664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,353 [classy] Got parameters {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,353 [classy] Re-using computed results
 2023-07-02 10:34:07,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00425673038194}
 2023-07-02 10:34:07,353 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5207632374945664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,353 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,373 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41125
 2023-07-02 10:34:07,373 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,373 [mcmc] New sample, #448:
   Omega_m:0.3063537, b1:0.4975061
 2023-07-02 10:34:07,373 [model] Posterior to be computed for parameters {'Omega_m': 0.30239269898826976, 'b1': 0.5262846219994948}
 2023-07-02 10:34:07,373 [prior] Evaluating prior at array([0.3023927 , 0.52628462])
 2023-07-02 10:34:07,373 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,373 [model] Got input parameters: {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5262846219994948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,374 [classy] Got parameters {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,374 [classy] Computing new state
 2023-07-02 10:34:07,374 [classy] Setting parameters: {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.49206689192476}
 2023-07-02 10:34:07,417 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00660716
 2023-07-02 10:34:07,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5262846219994948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,419 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,439 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.93003
 2023-07-02 10:34:07,439 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,440 [mcmc] New sample, #449:
   Omega_m:0.3063537, b1:0.5207632
 2023-07-02 10:34:07,440 [model] Posterior to be computed for parameters {'Omega_m': 0.30239269898826976, 'b1': 0.5255810476511051}
 2023-07-02 10:34:07,440 [prior] Evaluating prior at array([0.3023927 , 0.52558105])
 2023-07-02 10:34:07,440 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,440 [model] Got input parameters: {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5255810476511051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,440 [classy] Got parameters {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,440 [classy] Re-using computed results
 2023-07-02 10:34:07,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.49206689192476}
 2023-07-02 10:34:07,440 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5255810476511051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,440 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,459 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94015
 2023-07-02 10:34:07,459 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,459 [mcmc] New sample, #450:
   Omega_m:0.3023927, b1:0.5262846
 2023-07-02 10:34:07,460 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5135312397928139}
 2023-07-02 10:34:07,460 [prior] Evaluating prior at array([0.31103722, 0.51353124])
 2023-07-02 10:34:07,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,460 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135312397928139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,460 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,460 [classy] Computing new state
 2023-07-02 10:34:07,460 [classy] Setting parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
 2023-07-02 10:34:07,504 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000331196
 2023-07-02 10:34:07,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135312397928139, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,506 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,527 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73112
 2023-07-02 10:34:07,527 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,527 [mcmc] New sample, #451:
   Omega_m:0.3023927, b1:0.525581
 2023-07-02 10:34:07,527 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.4879755084585546}
 2023-07-02 10:34:07,527 [prior] Evaluating prior at array([0.31103722, 0.48797551])
 2023-07-02 10:34:07,527 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,527 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4879755084585546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,527 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,527 [classy] Re-using computed results
 2023-07-02 10:34:07,527 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
 2023-07-02 10:34:07,527 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4879755084585546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,528 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,547 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81958
 2023-07-02 10:34:07,547 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,547 [mcmc] New sample, #452:
   Omega_m:0.3110372, b1:0.5135312
 2023-07-02 10:34:07,547 [model] Posterior to be computed for parameters {'Omega_m': 0.30338869797634427, 'b1': 0.498636969088821}
 2023-07-02 10:34:07,547 [prior] Evaluating prior at array([0.3033887 , 0.49863697])
 2023-07-02 10:34:07,547 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,547 [model] Got input parameters: {'Omega_m': 0.30338869797634427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.498636969088821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,547 [classy] Got parameters {'Omega_m': 0.30338869797634427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,547 [classy] Computing new state
 2023-07-02 10:34:07,547 [classy] Setting parameters: {'Omega_m': 0.30338869797634427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,592 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.368882695798}
 2023-07-02 10:34:07,592 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,594 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00539225
 2023-07-02 10:34:07,594 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.498636969088821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,594 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,613 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.749875
 2023-07-02 10:34:07,613 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,613 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5493828810266157}
 2023-07-02 10:34:07,613 [prior] Evaluating prior at array([0.31103722, 0.54938288])
 2023-07-02 10:34:07,614 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,614 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5493828810266157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,614 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,614 [classy] Re-using computed results
 2023-07-02 10:34:07,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
 2023-07-02 10:34:07,614 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,614 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5493828810266157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,614 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,634 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.07315
 2023-07-02 10:34:07,635 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,635 [model] Posterior to be computed for parameters {'Omega_m': 0.3379322051051616, 'b1': 0.4504859338540728}
 2023-07-02 10:34:07,635 [prior] Evaluating prior at array([0.33793221, 0.45048593])
 2023-07-02 10:34:07,635 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,635 [model] Got input parameters: {'Omega_m': 0.3379322051051616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4504859338540728, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,635 [classy] Got parameters {'Omega_m': 0.3379322051051616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,635 [classy] Computing new state
 2023-07-02 10:34:07,635 [classy] Setting parameters: {'Omega_m': 0.3379322051051616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.30417414125947}
 2023-07-02 10:34:07,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0375328
 2023-07-02 10:34:07,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4504859338540728, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,681 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,700 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0970122
 2023-07-02 10:34:07,700 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,700 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5325258213647103}
 2023-07-02 10:34:07,700 [prior] Evaluating prior at array([0.31103722, 0.53252582])
 2023-07-02 10:34:07,701 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,701 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5325258213647103, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,701 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,701 [classy] Re-using computed results
 2023-07-02 10:34:07,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
 2023-07-02 10:34:07,701 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5325258213647103, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10955
 2023-07-02 10:34:07,720 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,720 [model] Posterior to be computed for parameters {'Omega_m': 0.2871598831280164, 'b1': 0.521258709048981}
 2023-07-02 10:34:07,720 [prior] Evaluating prior at array([0.28715988, 0.52125871])
 2023-07-02 10:34:07,720 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,721 [model] Got input parameters: {'Omega_m': 0.2871598831280164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521258709048981, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,721 [classy] Got parameters {'Omega_m': 0.2871598831280164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,721 [classy] Computing new state
 2023-07-02 10:34:07,721 [classy] Setting parameters: {'Omega_m': 0.2871598831280164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.4217437303083}
 2023-07-02 10:34:07,764 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0421512
 2023-07-02 10:34:07,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521258709048981, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,787 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.26823
 2023-07-02 10:34:07,787 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,787 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5249017809726502}
 2023-07-02 10:34:07,787 [prior] Evaluating prior at array([0.31103722, 0.52490178])
 2023-07-02 10:34:07,787 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,787 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5249017809726502, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,787 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,787 [classy] Re-using computed results
 2023-07-02 10:34:07,787 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
 2023-07-02 10:34:07,787 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,787 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5249017809726502, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,787 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,807 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.00464
 2023-07-02 10:34:07,807 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,807 [mcmc] New sample, #453:
   Omega_m:0.3110372, b1:0.4879755
 2023-07-02 10:34:07,807 [model] Posterior to be computed for parameters {'Omega_m': 0.3266178453905202, 'b1': 0.5031835677197153}
 2023-07-02 10:34:07,807 [prior] Evaluating prior at array([0.32661785, 0.50318357])
 2023-07-02 10:34:07,807 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,807 [model] Got input parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5031835677197153, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,807 [classy] Got parameters {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,807 [classy] Computing new state
 2023-07-02 10:34:07,807 [classy] Setting parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59280016794216}
 2023-07-02 10:34:07,851 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,853 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0120341
 2023-07-02 10:34:07,853 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5031835677197153, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,853 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,872 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.631904
 2023-07-02 10:34:07,872 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,873 [mcmc] New sample, #454:
   Omega_m:0.3110372, b1:0.5249018
 2023-07-02 10:34:07,873 [model] Posterior to be computed for parameters {'Omega_m': 0.3266178453905202, 'b1': 0.47002167763955904}
 2023-07-02 10:34:07,873 [prior] Evaluating prior at array([0.32661785, 0.47002168])
 2023-07-02 10:34:07,873 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,873 [model] Got input parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47002167763955904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,873 [classy] Got parameters {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,873 [classy] Re-using computed results
 2023-07-02 10:34:07,873 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59280016794216}
 2023-07-02 10:34:07,873 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,873 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47002167763955904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,873 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,893 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99618
 2023-07-02 10:34:07,893 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,893 [mcmc] New sample, #455:
   Omega_m:0.3266178, b1:0.5031836
 2023-07-02 10:34:07,893 [model] Posterior to be computed for parameters {'Omega_m': 0.34749887478940467, 'b1': 0.4409151026014754}
 2023-07-02 10:34:07,893 [prior] Evaluating prior at array([0.34749887, 0.4409151 ])
 2023-07-02 10:34:07,893 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,893 [model] Got input parameters: {'Omega_m': 0.34749887478940467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4409151026014754, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,893 [classy] Got parameters {'Omega_m': 0.34749887478940467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,894 [classy] Computing new state
 2023-07-02 10:34:07,894 [classy] Setting parameters: {'Omega_m': 0.34749887478940467, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:07,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.24478953215723}
 2023-07-02 10:34:07,939 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:07,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0693046
 2023-07-02 10:34:07,941 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4409151026014754, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,941 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,960 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.19119
 2023-07-02 10:34:07,960 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,961 [model] Posterior to be computed for parameters {'Omega_m': 0.3266178453905202, 'b1': 0.4556503657235575}
 2023-07-02 10:34:07,961 [prior] Evaluating prior at array([0.32661785, 0.45565037])
 2023-07-02 10:34:07,961 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,961 [model] Got input parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4556503657235575, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,961 [classy] Got parameters {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,961 [classy] Re-using computed results
 2023-07-02 10:34:07,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59280016794216}
 2023-07-02 10:34:07,961 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:07,961 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4556503657235575, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,961 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:07,980 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.742583
 2023-07-02 10:34:07,980 [model] Computed derived parameters: {}
 2023-07-02 10:34:07,980 [model] Posterior to be computed for parameters {'Omega_m': 0.3135297999833939, 'b1': 0.4882654226421267}
 2023-07-02 10:34:07,980 [prior] Evaluating prior at array([0.3135298 , 0.48826542])
 2023-07-02 10:34:07,980 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:07,980 [model] Got input parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4882654226421267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:07,981 [classy] Got parameters {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:07,981 [classy] Computing new state
 2023-07-02 10:34:07,981 [classy] Setting parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.13446721869096}
 2023-07-02 10:34:08,025 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,026 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000269295
 2023-07-02 10:34:08,026 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4882654226421267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,026 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,047 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33383
 2023-07-02 10:34:08,047 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,047 [mcmc] New sample, #456:
   Omega_m:0.3266178, b1:0.4700217
 2023-07-02 10:34:08,047 [model] Posterior to be computed for parameters {'Omega_m': 0.3135297999833939, 'b1': 0.46425771952517236}
 2023-07-02 10:34:08,047 [prior] Evaluating prior at array([0.3135298 , 0.46425772])
 2023-07-02 10:34:08,047 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,047 [model] Got input parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46425771952517236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,047 [classy] Got parameters {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,047 [classy] Re-using computed results
 2023-07-02 10:34:08,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.13446721869096}
 2023-07-02 10:34:08,047 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,047 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46425771952517236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,047 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,067 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.978433
 2023-07-02 10:34:08,067 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,067 [model] Posterior to be computed for parameters {'Omega_m': 0.3508758858819358, 'b1': 0.4362078046569378}
 2023-07-02 10:34:08,067 [prior] Evaluating prior at array([0.35087589, 0.4362078 ])
 2023-07-02 10:34:08,067 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,067 [model] Got input parameters: {'Omega_m': 0.3508758858819358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4362078046569378, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,067 [classy] Got parameters {'Omega_m': 0.3508758858819358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,067 [classy] Computing new state
 2023-07-02 10:34:08,067 [classy] Setting parameters: {'Omega_m': 0.3508758858819358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.8772028708634}
 2023-07-02 10:34:08,112 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,114 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0826262
 2023-07-02 10:34:08,114 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4362078046569378, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,114 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,137 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22742
 2023-07-02 10:34:08,138 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,138 [model] Posterior to be computed for parameters {'Omega_m': 0.3135297999833939, 'b1': 0.521294504371664}
 2023-07-02 10:34:08,138 [prior] Evaluating prior at array([0.3135298, 0.5212945])
 2023-07-02 10:34:08,138 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,138 [model] Got input parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521294504371664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,138 [classy] Got parameters {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,138 [classy] Re-using computed results
 2023-07-02 10:34:08,138 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.13446721869096}
 2023-07-02 10:34:08,138 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,138 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521294504371664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,138 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,158 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99517
 2023-07-02 10:34:08,158 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,158 [mcmc] New sample, #457:
   Omega_m:0.3135298, b1:0.4882654
 2023-07-02 10:34:08,158 [model] Posterior to be computed for parameters {'Omega_m': 0.3101394708996452, 'b1': 0.5260203665882652}
 2023-07-02 10:34:08,158 [prior] Evaluating prior at array([0.31013947, 0.52602037])
 2023-07-02 10:34:08,158 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,159 [model] Got input parameters: {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5260203665882652, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,159 [classy] Got parameters {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,159 [classy] Computing new state
 2023-07-02 10:34:08,159 [classy] Setting parameters: {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54318704291524}
 2023-07-02 10:34:08,202 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,204 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000541448
 2023-07-02 10:34:08,204 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5260203665882652, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,204 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,223 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.00572
 2023-07-02 10:34:08,223 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,223 [mcmc] New sample, #458:
   Omega_m:0.3135298, b1:0.5212945
 2023-07-02 10:34:08,224 [model] Posterior to be computed for parameters {'Omega_m': 0.3101394708996452, 'b1': 0.4906648537369532}
 2023-07-02 10:34:08,224 [prior] Evaluating prior at array([0.31013947, 0.49066485])
 2023-07-02 10:34:08,224 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,224 [model] Got input parameters: {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906648537369532, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,224 [classy] Got parameters {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,224 [classy] Re-using computed results
 2023-07-02 10:34:08,224 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54318704291524}
 2023-07-02 10:34:08,224 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,224 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906648537369532, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,224 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,244 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87776
 2023-07-02 10:34:08,244 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,244 [mcmc] New sample, #459:
   Omega_m:0.3101395, b1:0.5260204
 2023-07-02 10:34:08,244 [model] Posterior to be computed for parameters {'Omega_m': 0.31180231686296445, 'b1': 0.48834697228180274}
 2023-07-02 10:34:08,244 [prior] Evaluating prior at array([0.31180232, 0.48834697])
 2023-07-02 10:34:08,244 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,244 [model] Got input parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48834697228180274, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,244 [classy] Got parameters {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,244 [classy] Computing new state
 2023-07-02 10:34:08,244 [classy] Setting parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,288 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34223258208854}
 2023-07-02 10:34:08,288 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,290 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000230911
 2023-07-02 10:34:08,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48834697228180274, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,290 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,310 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02403
 2023-07-02 10:34:08,310 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,310 [mcmc] New sample, #460:
   Omega_m:0.3101395, b1:0.4906649
 2023-07-02 10:34:08,310 [model] Posterior to be computed for parameters {'Omega_m': 0.31180231686296445, 'b1': 0.5132131556706865}
 2023-07-02 10:34:08,310 [prior] Evaluating prior at array([0.31180232, 0.51321316])
 2023-07-02 10:34:08,310 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,310 [model] Got input parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5132131556706865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,310 [classy] Got parameters {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,310 [classy] Re-using computed results
 2023-07-02 10:34:08,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34223258208854}
 2023-07-02 10:34:08,310 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,310 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5132131556706865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,310 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,330 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72635
 2023-07-02 10:34:08,330 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,330 [mcmc] New sample, #461:
   Omega_m:0.3118023, b1:0.488347
 2023-07-02 10:34:08,330 [model] Posterior to be computed for parameters {'Omega_m': 0.29556709457055186, 'b1': 0.5358438271230872}
 2023-07-02 10:34:08,330 [prior] Evaluating prior at array([0.29556709, 0.53584383])
 2023-07-02 10:34:08,330 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,330 [model] Got input parameters: {'Omega_m': 0.29556709457055186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5358438271230872, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,330 [classy] Got parameters {'Omega_m': 0.29556709457055186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,330 [classy] Computing new state
 2023-07-02 10:34:08,330 [classy] Setting parameters: {'Omega_m': 0.29556709457055186, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3460123446448}
 2023-07-02 10:34:08,374 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,376 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185186
 2023-07-02 10:34:08,376 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5358438271230872, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,376 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,395 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.575124
 2023-07-02 10:34:08,396 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,396 [model] Posterior to be computed for parameters {'Omega_m': 0.31180231686296445, 'b1': 0.5022504517628039}
 2023-07-02 10:34:08,396 [prior] Evaluating prior at array([0.31180232, 0.50225045])
 2023-07-02 10:34:08,396 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,396 [model] Got input parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5022504517628039, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,396 [classy] Got parameters {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,396 [classy] Re-using computed results
 2023-07-02 10:34:08,396 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34223258208854}
 2023-07-02 10:34:08,396 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,396 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5022504517628039, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,396 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,415 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82041
 2023-07-02 10:34:08,415 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,415 [mcmc] New sample, #462:
   Omega_m:0.3118023, b1:0.5132132
 2023-07-02 10:34:08,415 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.5143764509625448}
 2023-07-02 10:34:08,415 [prior] Evaluating prior at array([0.30310314, 0.51437645])
 2023-07-02 10:34:08,416 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,416 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5143764509625448, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,416 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,416 [classy] Computing new state
 2023-07-02 10:34:08,416 [classy] Setting parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
 2023-07-02 10:34:08,460 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0057272
 2023-07-02 10:34:08,462 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5143764509625448, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,462 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,481 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91048
 2023-07-02 10:34:08,481 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,481 [mcmc] New sample, #463:
   Omega_m:0.3118023, b1:0.5022505
 2023-07-02 10:34:08,481 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.543863615547758}
 2023-07-02 10:34:08,481 [prior] Evaluating prior at array([0.30310314, 0.54386362])
 2023-07-02 10:34:08,481 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,482 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.543863615547758, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,482 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,482 [classy] Re-using computed results
 2023-07-02 10:34:08,482 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
 2023-07-02 10:34:08,482 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,482 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.543863615547758, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,482 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,501 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.755095
 2023-07-02 10:34:08,502 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,502 [mcmc] New sample, #464:
   Omega_m:0.3031031, b1:0.5143765
 2023-07-02 10:34:08,502 [model] Posterior to be computed for parameters {'Omega_m': 0.29592397021648037, 'b1': 0.5538708301526624}
 2023-07-02 10:34:08,502 [prior] Evaluating prior at array([0.29592397, 0.55387083])
 2023-07-02 10:34:08,502 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,502 [model] Got input parameters: {'Omega_m': 0.29592397021648037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5538708301526624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,502 [classy] Got parameters {'Omega_m': 0.29592397021648037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,502 [classy] Computing new state
 2023-07-02 10:34:08,502 [classy] Setting parameters: {'Omega_m': 0.29592397021648037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3009404056425}
 2023-07-02 10:34:08,546 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,548 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0177379
 2023-07-02 10:34:08,548 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5538708301526624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,548 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,568 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.297594
 2023-07-02 10:34:08,568 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,568 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.5374354436810272}
 2023-07-02 10:34:08,568 [prior] Evaluating prior at array([0.30310314, 0.53743544])
 2023-07-02 10:34:08,568 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,568 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5374354436810272, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,568 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,568 [classy] Re-using computed results
 2023-07-02 10:34:08,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
 2023-07-02 10:34:08,568 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,568 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5374354436810272, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,568 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.4137
 2023-07-02 10:34:08,587 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,587 [mcmc] New sample, #465:
   Omega_m:0.3031031, b1:0.5438636
 2023-07-02 10:34:08,588 [model] Posterior to be computed for parameters {'Omega_m': 0.2757534248458676, 'b1': 0.5755588723467275}
 2023-07-02 10:34:08,588 [prior] Evaluating prior at array([0.27575342, 0.57555887])
 2023-07-02 10:34:08,588 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,588 [model] Got input parameters: {'Omega_m': 0.2757534248458676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5755588723467275, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,588 [classy] Got parameters {'Omega_m': 0.2757534248458676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,588 [classy] Computing new state
 2023-07-02 10:34:08,588 [classy] Setting parameters: {'Omega_m': 0.2757534248458676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.92560334376802}
 2023-07-02 10:34:08,632 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,634 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0911576
 2023-07-02 10:34:08,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5755588723467275, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,634 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,654 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.43262
 2023-07-02 10:34:08,654 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,654 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.5263009532115862}
 2023-07-02 10:34:08,654 [prior] Evaluating prior at array([0.30310314, 0.52630095])
 2023-07-02 10:34:08,655 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,655 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5263009532115862, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,655 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,655 [classy] Re-using computed results
 2023-07-02 10:34:08,655 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
 2023-07-02 10:34:08,655 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,655 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5263009532115862, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,655 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,675 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.01164
 2023-07-02 10:34:08,676 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,676 [mcmc] New sample, #466:
   Omega_m:0.3031031, b1:0.5374354
 2023-07-02 10:34:08,676 [model] Posterior to be computed for parameters {'Omega_m': 0.29899894701923985, 'b1': 0.5320218828187468}
 2023-07-02 10:34:08,676 [prior] Evaluating prior at array([0.29899895, 0.53202188])
 2023-07-02 10:34:08,676 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,676 [model] Got input parameters: {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5320218828187468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,676 [classy] Got parameters {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,676 [classy] Computing new state
 2023-07-02 10:34:08,676 [classy] Setting parameters: {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91451154378714}
 2023-07-02 10:34:08,722 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,724 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117386
 2023-07-02 10:34:08,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5320218828187468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,724 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,746 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.33038
 2023-07-02 10:34:08,746 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,746 [mcmc] New sample, #467:
   Omega_m:0.3031031, b1:0.526301
 2023-07-02 10:34:08,746 [model] Posterior to be computed for parameters {'Omega_m': 0.29899894701923985, 'b1': 0.5507527163785765}
 2023-07-02 10:34:08,746 [prior] Evaluating prior at array([0.29899895, 0.55075272])
 2023-07-02 10:34:08,746 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,746 [model] Got input parameters: {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5507527163785765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,746 [classy] Got parameters {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,746 [classy] Re-using computed results
 2023-07-02 10:34:08,746 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91451154378714}
 2023-07-02 10:34:08,746 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,746 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5507527163785765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,746 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,767 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.113778
 2023-07-02 10:34:08,767 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,767 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.4874373705119748}
 2023-07-02 10:34:08,767 [prior] Evaluating prior at array([0.33098383, 0.48743737])
 2023-07-02 10:34:08,767 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,767 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4874373705119748, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,767 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,767 [classy] Computing new state
 2023-07-02 10:34:08,768 [classy] Setting parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
 2023-07-02 10:34:08,812 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,814 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.020261
 2023-07-02 10:34:08,814 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4874373705119748, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,814 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,833 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.897659
 2023-07-02 10:34:08,833 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,833 [mcmc] New sample, #468:
   Omega_m:0.2989989, b1:0.5320219
 2023-07-02 10:34:08,834 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.5321954594474464}
 2023-07-02 10:34:08,834 [prior] Evaluating prior at array([0.33098383, 0.53219546])
 2023-07-02 10:34:08,834 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,834 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5321954594474464, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,834 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,834 [classy] Re-using computed results
 2023-07-02 10:34:08,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
 2023-07-02 10:34:08,834 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5321954594474464, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,834 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,854 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.13937
 2023-07-02 10:34:08,854 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3494752394501789, 'b1': 0.46166175041244567}
 2023-07-02 10:34:08,854 [prior] Evaluating prior at array([0.34947524, 0.46166175])
 2023-07-02 10:34:08,854 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,854 [model] Got input parameters: {'Omega_m': 0.3494752394501789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46166175041244567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,854 [classy] Got parameters {'Omega_m': 0.3494752394501789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,854 [classy] Computing new state
 2023-07-02 10:34:08,854 [classy] Setting parameters: {'Omega_m': 0.3494752394501789, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.02926686384663}
 2023-07-02 10:34:08,898 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,899 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0769712
 2023-07-02 10:34:08,899 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46166175041244567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,899 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,920 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.37258
 2023-07-02 10:34:08,920 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,920 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.4711131968498434}
 2023-07-02 10:34:08,920 [prior] Evaluating prior at array([0.33098383, 0.4711132 ])
 2023-07-02 10:34:08,920 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,920 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4711131968498434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,920 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,920 [classy] Re-using computed results
 2023-07-02 10:34:08,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
 2023-07-02 10:34:08,920 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:08,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4711131968498434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,920 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:08,940 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61499
 2023-07-02 10:34:08,940 [model] Computed derived parameters: {}
 2023-07-02 10:34:08,940 [mcmc] New sample, #469:
   Omega_m:0.3309838, b1:0.4874374
 2023-07-02 10:34:08,941 [model] Posterior to be computed for parameters {'Omega_m': 0.34089936033326, 'b1': 0.45729170335326175}
 2023-07-02 10:34:08,941 [prior] Evaluating prior at array([0.34089936, 0.4572917 ])
 2023-07-02 10:34:08,941 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:08,941 [model] Got input parameters: {'Omega_m': 0.34089936033326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45729170335326175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,941 [classy] Got parameters {'Omega_m': 0.34089936033326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:08,941 [classy] Computing new state
 2023-07-02 10:34:08,941 [classy] Setting parameters: {'Omega_m': 0.34089936033326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:08,985 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.97270017554806}
 2023-07-02 10:34:08,985 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:08,987 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0464206
 2023-07-02 10:34:08,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45729170335326175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:08,987 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,007 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.446025
 2023-07-02 10:34:09,007 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,007 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.4428598989777455}
 2023-07-02 10:34:09,007 [prior] Evaluating prior at array([0.33098383, 0.4428599 ])
 2023-07-02 10:34:09,007 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,008 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4428598989777455, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,008 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,008 [classy] Re-using computed results
 2023-07-02 10:34:09,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
 2023-07-02 10:34:09,008 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4428598989777455, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,008 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,027 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.544369
 2023-07-02 10:34:09,027 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,027 [mcmc] New sample, #470:
   Omega_m:0.3309838, b1:0.4711132
 2023-07-02 10:34:09,027 [model] Posterior to be computed for parameters {'Omega_m': 0.34686776026927474, 'b1': 0.42071890756387315}
 2023-07-02 10:34:09,027 [prior] Evaluating prior at array([0.34686776, 0.42071891])
 2023-07-02 10:34:09,027 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,027 [model] Got input parameters: {'Omega_m': 0.34686776026927474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42071890756387315, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,028 [classy] Got parameters {'Omega_m': 0.34686776026927474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,028 [classy] Computing new state
 2023-07-02 10:34:09,028 [classy] Setting parameters: {'Omega_m': 0.34686776026927474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,072 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.31384640482958}
 2023-07-02 10:34:09,072 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,074 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0669345
 2023-07-02 10:34:09,074 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42071890756387315, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,074 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,093 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.31617
 2023-07-02 10:34:09,093 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,093 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.5052090479049207}
 2023-07-02 10:34:09,093 [prior] Evaluating prior at array([0.33098383, 0.50520905])
 2023-07-02 10:34:09,093 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,093 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5052090479049207, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,093 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,093 [classy] Re-using computed results
 2023-07-02 10:34:09,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
 2023-07-02 10:34:09,093 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5052090479049207, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,093 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,113 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.62486
 2023-07-02 10:34:09,113 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,113 [model] Posterior to be computed for parameters {'Omega_m': 0.32374866619499143, 'b1': 0.4529451754183492}
 2023-07-02 10:34:09,113 [prior] Evaluating prior at array([0.32374867, 0.45294518])
 2023-07-02 10:34:09,113 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,114 [model] Got input parameters: {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4529451754183492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,114 [classy] Got parameters {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,114 [classy] Computing new state
 2023-07-02 10:34:09,114 [classy] Setting parameters: {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92598632718128}
 2023-07-02 10:34:09,160 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,162 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00777023
 2023-07-02 10:34:09,162 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4529451754183492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,162 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,181 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.087198
 2023-07-02 10:34:09,181 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,182 [mcmc] New sample, #471:
   Omega_m:0.3309838, b1:0.4428599
 2023-07-02 10:34:09,182 [model] Posterior to be computed for parameters {'Omega_m': 0.32374866619499143, 'b1': 0.43206677367818797}
 2023-07-02 10:34:09,182 [prior] Evaluating prior at array([0.32374867, 0.43206677])
 2023-07-02 10:34:09,182 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,182 [model] Got input parameters: {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43206677367818797, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,182 [classy] Got parameters {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,182 [classy] Re-using computed results
 2023-07-02 10:34:09,182 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92598632718128}
 2023-07-02 10:34:09,182 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,182 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43206677367818797, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,182 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,202 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.54795
 2023-07-02 10:34:09,202 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,202 [model] Posterior to be computed for parameters {'Omega_m': 0.3336503038364659, 'b1': 0.43914304174447555}
 2023-07-02 10:34:09,202 [prior] Evaluating prior at array([0.3336503 , 0.43914304])
 2023-07-02 10:34:09,202 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,202 [model] Got input parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43914304174447555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,202 [classy] Got parameters {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,202 [classy] Computing new state
 2023-07-02 10:34:09,202 [classy] Setting parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7871979380322}
 2023-07-02 10:34:09,246 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.026292
 2023-07-02 10:34:09,248 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43914304174447555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,248 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,268 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.846923
 2023-07-02 10:34:09,268 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,268 [mcmc] New sample, #472:
   Omega_m:0.3237487, b1:0.4529452
 2023-07-02 10:34:09,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3336503038364659, 'b1': 0.38514090415126606}
 2023-07-02 10:34:09,268 [prior] Evaluating prior at array([0.3336503, 0.3851409])
 2023-07-02 10:34:09,268 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,268 [model] Got input parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38514090415126606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,268 [classy] Got parameters {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,268 [classy] Re-using computed results
 2023-07-02 10:34:09,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7871979380322}
 2023-07-02 10:34:09,268 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,268 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38514090415126606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,268 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,288 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5553
 2023-07-02 10:34:09,288 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,288 [model] Posterior to be computed for parameters {'Omega_m': 0.34371613926958433, 'b1': 0.42511202877292564}
 2023-07-02 10:34:09,288 [prior] Evaluating prior at array([0.34371614, 0.42511203])
 2023-07-02 10:34:09,288 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,288 [model] Got input parameters: {'Omega_m': 0.34371613926958433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42511202877292564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,288 [classy] Got parameters {'Omega_m': 0.34371613926958433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,288 [classy] Computing new state
 2023-07-02 10:34:09,288 [classy] Setting parameters: {'Omega_m': 0.34371613926958433, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.66044241927366}
 2023-07-02 10:34:09,332 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.05567
 2023-07-02 10:34:09,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42511202877292564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,334 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,354 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.58869
 2023-07-02 10:34:09,354 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3336503038364659, 'b1': 0.467354445036929}
 2023-07-02 10:34:09,354 [prior] Evaluating prior at array([0.3336503 , 0.46735445])
 2023-07-02 10:34:09,354 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,354 [model] Got input parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.467354445036929, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,354 [classy] Got parameters {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,355 [classy] Re-using computed results
 2023-07-02 10:34:09,355 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7871979380322}
 2023-07-02 10:34:09,355 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.467354445036929, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,355 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,374 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15325
 2023-07-02 10:34:09,374 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,374 [mcmc] New sample, #473:
   Omega_m:0.3336503, b1:0.439143
 2023-07-02 10:34:09,374 [model] Posterior to be computed for parameters {'Omega_m': 0.30785972658723815, 'b1': 0.5033045583019504}
 2023-07-02 10:34:09,374 [prior] Evaluating prior at array([0.30785973, 0.50330456])
 2023-07-02 10:34:09,374 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,374 [model] Got input parameters: {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5033045583019504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,374 [classy] Got parameters {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,375 [classy] Computing new state
 2023-07-02 10:34:09,375 [classy] Setting parameters: {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8202415108137}
 2023-07-02 10:34:09,418 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,420 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.001529
 2023-07-02 10:34:09,420 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5033045583019504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,420 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,440 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34942
 2023-07-02 10:34:09,440 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,440 [mcmc] New sample, #474:
   Omega_m:0.3336503, b1:0.4673544
 2023-07-02 10:34:09,440 [model] Posterior to be computed for parameters {'Omega_m': 0.30785972658723815, 'b1': 0.5246063922512886}
 2023-07-02 10:34:09,440 [prior] Evaluating prior at array([0.30785973, 0.52460639])
 2023-07-02 10:34:09,440 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,440 [model] Got input parameters: {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5246063922512886, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,440 [classy] Got parameters {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,440 [classy] Re-using computed results
 2023-07-02 10:34:09,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8202415108137}
 2023-07-02 10:34:09,440 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5246063922512886, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,440 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,460 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26979
 2023-07-02 10:34:09,460 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,460 [mcmc] New sample, #475:
   Omega_m:0.3078597, b1:0.5033046
 2023-07-02 10:34:09,460 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5191444234803674}
 2023-07-02 10:34:09,460 [prior] Evaluating prior at array([0.31177814, 0.51914442])
 2023-07-02 10:34:09,461 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,461 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191444234803674, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,461 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,461 [classy] Computing new state
 2023-07-02 10:34:09,461 [classy] Setting parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
 2023-07-02 10:34:09,504 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000232975
 2023-07-02 10:34:09,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191444234803674, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,506 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,526 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40395
 2023-07-02 10:34:09,526 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,526 [mcmc] New sample, #476:
   Omega_m:0.3078597, b1:0.5246064
 2023-07-02 10:34:09,526 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5406754199151753}
 2023-07-02 10:34:09,526 [prior] Evaluating prior at array([0.31177814, 0.54067542])
 2023-07-02 10:34:09,526 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,526 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5406754199151753, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,526 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,526 [classy] Re-using computed results
 2023-07-02 10:34:09,526 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
 2023-07-02 10:34:09,527 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5406754199151753, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,527 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,546 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.446116
 2023-07-02 10:34:09,546 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,546 [model] Posterior to be computed for parameters {'Omega_m': 0.3004490386855843, 'b1': 0.5349363304632826}
 2023-07-02 10:34:09,546 [prior] Evaluating prior at array([0.30044904, 0.53493633])
 2023-07-02 10:34:09,547 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,547 [model] Got input parameters: {'Omega_m': 0.3004490386855843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5349363304632826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,547 [classy] Got parameters {'Omega_m': 0.3004490386855843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,547 [classy] Computing new state
 2023-07-02 10:34:09,547 [classy] Setting parameters: {'Omega_m': 0.3004490386855843, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73348283010247}
 2023-07-02 10:34:09,591 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,592 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00935672
 2023-07-02 10:34:09,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5349363304632826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,593 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,612 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44798
 2023-07-02 10:34:09,613 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,613 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5463018317387807}
 2023-07-02 10:34:09,613 [prior] Evaluating prior at array([0.31177814, 0.54630183])
 2023-07-02 10:34:09,613 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,613 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5463018317387807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,613 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,613 [classy] Re-using computed results
 2023-07-02 10:34:09,613 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
 2023-07-02 10:34:09,613 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5463018317387807, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,613 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.63832
 2023-07-02 10:34:09,632 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,633 [model] Posterior to be computed for parameters {'Omega_m': 0.288658377585924, 'b1': 0.5513716199066377}
 2023-07-02 10:34:09,633 [prior] Evaluating prior at array([0.28865838, 0.55137162])
 2023-07-02 10:34:09,633 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,633 [model] Got input parameters: {'Omega_m': 0.288658377585924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5513716199066377, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,633 [classy] Got parameters {'Omega_m': 0.288658377585924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,633 [classy] Computing new state
 2023-07-02 10:34:09,633 [classy] Setting parameters: {'Omega_m': 0.288658377585924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.22802773929757}
 2023-07-02 10:34:09,677 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0371889
 2023-07-02 10:34:09,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5513716199066377, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,679 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,698 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.52523
 2023-07-02 10:34:09,698 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,698 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5282927642057617}
 2023-07-02 10:34:09,698 [prior] Evaluating prior at array([0.31177814, 0.52829276])
 2023-07-02 10:34:09,698 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,698 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282927642057617, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,698 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,698 [classy] Re-using computed results
 2023-07-02 10:34:09,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
 2023-07-02 10:34:09,698 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282927642057617, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,698 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,718 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.519
 2023-07-02 10:34:09,718 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,718 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.5354565790967422}
 2023-07-02 10:34:09,718 [prior] Evaluating prior at array([0.30007581, 0.53545658])
 2023-07-02 10:34:09,719 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,719 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5354565790967422, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,719 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,719 [classy] Computing new state
 2023-07-02 10:34:09,719 [classy] Setting parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
 2023-07-02 10:34:09,764 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,765 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00994268
 2023-07-02 10:34:09,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5354565790967422, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,785 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38608
 2023-07-02 10:34:09,785 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,785 [mcmc] New sample, #477:
   Omega_m:0.3117781, b1:0.5191444
 2023-07-02 10:34:09,785 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.5070957897741949}
 2023-07-02 10:34:09,785 [prior] Evaluating prior at array([0.30007581, 0.50709579])
 2023-07-02 10:34:09,785 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,785 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070957897741949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,785 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,785 [classy] Re-using computed results
 2023-07-02 10:34:09,785 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
 2023-07-02 10:34:09,785 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,785 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070957897741949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,785 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,805 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.479917
 2023-07-02 10:34:09,805 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,805 [model] Posterior to be computed for parameters {'Omega_m': 0.2979747866710345, 'b1': 0.5383852505595529}
 2023-07-02 10:34:09,805 [prior] Evaluating prior at array([0.29797479, 0.53838525])
 2023-07-02 10:34:09,805 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,805 [model] Got input parameters: {'Omega_m': 0.2979747866710345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5383852505595529, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,805 [classy] Got parameters {'Omega_m': 0.2979747866710345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,805 [classy] Computing new state
 2023-07-02 10:34:09,805 [classy] Setting parameters: {'Omega_m': 0.2979747866710345, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0428329909519}
 2023-07-02 10:34:09,849 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0135927
 2023-07-02 10:34:09,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5383852505595529, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,851 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,870 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.99959
 2023-07-02 10:34:09,870 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,870 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.5428226601527582}
 2023-07-02 10:34:09,871 [prior] Evaluating prior at array([0.30007581, 0.54282266])
 2023-07-02 10:34:09,871 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,871 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5428226601527582, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,871 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,871 [classy] Re-using computed results
 2023-07-02 10:34:09,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
 2023-07-02 10:34:09,871 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5428226601527582, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,871 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,890 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.920418
 2023-07-02 10:34:09,890 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,890 [mcmc] New sample, #478:
   Omega_m:0.3000758, b1:0.5354566
 2023-07-02 10:34:09,890 [model] Posterior to be computed for parameters {'Omega_m': 0.28648010184992745, 'b1': 0.5617740525213949}
 2023-07-02 10:34:09,890 [prior] Evaluating prior at array([0.2864801 , 0.56177405])
 2023-07-02 10:34:09,890 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,890 [model] Got input parameters: {'Omega_m': 0.28648010184992745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5617740525213949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,891 [classy] Got parameters {'Omega_m': 0.28648010184992745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,891 [classy] Computing new state
 2023-07-02 10:34:09,891 [classy] Setting parameters: {'Omega_m': 0.28648010184992745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:09,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.50990461007672}
 2023-07-02 10:34:09,935 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:09,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0445118
 2023-07-02 10:34:09,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5617740525213949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,937 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,957 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.54927
 2023-07-02 10:34:09,957 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.571768274655137}
 2023-07-02 10:34:09,957 [prior] Evaluating prior at array([0.30007581, 0.57176827])
 2023-07-02 10:34:09,957 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,957 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.571768274655137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,957 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,957 [classy] Re-using computed results
 2023-07-02 10:34:09,957 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
 2023-07-02 10:34:09,957 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:09,957 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.571768274655137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,957 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:09,977 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.89166
 2023-07-02 10:34:09,977 [model] Computed derived parameters: {}
 2023-07-02 10:34:09,977 [model] Posterior to be computed for parameters {'Omega_m': 0.30977281475773333, 'b1': 0.5293057731496983}
 2023-07-02 10:34:09,977 [prior] Evaluating prior at array([0.30977281, 0.52930577])
 2023-07-02 10:34:09,977 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:09,977 [model] Got input parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5293057731496983, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:09,977 [classy] Got parameters {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:09,977 [classy] Computing new state
 2023-07-02 10:34:09,978 [classy] Setting parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,021 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5876236222148}
 2023-07-02 10:34:10,021 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,023 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000656209
 2023-07-02 10:34:10,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5293057731496983, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,023 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,043 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72153
 2023-07-02 10:34:10,043 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,043 [mcmc] New sample, #479:
   Omega_m:0.3000758, b1:0.5428227
 2023-07-02 10:34:10,043 [model] Posterior to be computed for parameters {'Omega_m': 0.30977281475773333, 'b1': 0.48830271168512285}
 2023-07-02 10:34:10,043 [prior] Evaluating prior at array([0.30977281, 0.48830271])
 2023-07-02 10:34:10,043 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,043 [model] Got input parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48830271168512285, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,043 [classy] Got parameters {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,043 [classy] Re-using computed results
 2023-07-02 10:34:10,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5876236222148}
 2023-07-02 10:34:10,043 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,043 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48830271168512285, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,043 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,063 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.5402
 2023-07-02 10:34:10,063 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,063 [mcmc] New sample, #480:
   Omega_m:0.3097728, b1:0.5293058
 2023-07-02 10:34:10,063 [mcmc] Learn + convergence test @ 480 samples accepted.
 2023-07-02 10:34:10,063 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:10,068 [mcmc]  - Acceptance rate: 0.440
 2023-07-02 10:34:10,068 [mcmc]  - Condition number = 7.86485
 2023-07-02 10:34:10,069 [mcmc]  - Eigenvalues = array([0.00964271, 0.07583844])
 2023-07-02 10:34:10,069 [mcmc]  - Convergence of means: R-1 = 0.075838 after 384 accepted steps
 2023-07-02 10:34:10,069 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:10,069 [mcmc] array([[ 9.88650245e-05, -1.53620379e-04],
       [-1.53620379e-04,  4.09152797e-04]])
 2023-07-02 10:34:10,079 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:10,079 [model] Posterior to be computed for parameters {'Omega_m': 0.2876550464192195, 'b1': 0.5226701734133745}
 2023-07-02 10:34:10,079 [prior] Evaluating prior at array([0.28765505, 0.52267017])
 2023-07-02 10:34:10,079 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,079 [model] Got input parameters: {'Omega_m': 0.2876550464192195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5226701734133745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,079 [classy] Got parameters {'Omega_m': 0.2876550464192195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,079 [classy] Computing new state
 2023-07-02 10:34:10,079 [classy] Setting parameters: {'Omega_m': 0.2876550464192195, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.35763533817433}
 2023-07-02 10:34:10,127 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,129 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0404747
 2023-07-02 10:34:10,129 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5226701734133745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,129 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,153 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75636
 2023-07-02 10:34:10,153 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,153 [model] Posterior to be computed for parameters {'Omega_m': 0.30977281475773333, 'b1': 0.4973908866124182}
 2023-07-02 10:34:10,153 [prior] Evaluating prior at array([0.30977281, 0.49739089])
 2023-07-02 10:34:10,153 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,153 [model] Got input parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4973908866124182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,153 [classy] Got parameters {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,153 [classy] Re-using computed results
 2023-07-02 10:34:10,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5876236222148}
 2023-07-02 10:34:10,153 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4973908866124182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,153 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,174 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34726
 2023-07-02 10:34:10,174 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,175 [mcmc] New sample, #481:
   Omega_m:0.3097728, b1:0.4883027
 2023-07-02 10:34:10,175 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.47961579330240944}
 2023-07-02 10:34:10,175 [prior] Evaluating prior at array([0.32121228, 0.47961579])
 2023-07-02 10:34:10,175 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,175 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47961579330240944, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,175 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,175 [classy] Computing new state
 2023-07-02 10:34:10,175 [classy] Setting parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
 2023-07-02 10:34:10,219 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,221 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00477407
 2023-07-02 10:34:10,221 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47961579330240944, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,221 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,241 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48778
 2023-07-02 10:34:10,241 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,241 [mcmc] New sample, #482:
   Omega_m:0.3097728, b1:0.4973909
 2023-07-02 10:34:10,241 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.5077719680531204}
 2023-07-02 10:34:10,241 [prior] Evaluating prior at array([0.32121228, 0.50777197])
 2023-07-02 10:34:10,242 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,242 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5077719680531204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,242 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,242 [classy] Re-using computed results
 2023-07-02 10:34:10,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
 2023-07-02 10:34:10,242 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5077719680531204, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,242 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76207
 2023-07-02 10:34:10,261 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,261 [mcmc] New sample, #483:
   Omega_m:0.3212123, b1:0.4796158
 2023-07-02 10:34:10,262 [model] Posterior to be computed for parameters {'Omega_m': 0.3402567719919574, 'b1': 0.4781798850034525}
 2023-07-02 10:34:10,262 [prior] Evaluating prior at array([0.34025677, 0.47817989])
 2023-07-02 10:34:10,262 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,262 [model] Got input parameters: {'Omega_m': 0.3402567719919574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4781798850034525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,262 [classy] Got parameters {'Omega_m': 0.3402567719919574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,262 [classy] Computing new state
 2023-07-02 10:34:10,262 [classy] Setting parameters: {'Omega_m': 0.3402567719919574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.04426597993017}
 2023-07-02 10:34:10,306 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,308 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0444206
 2023-07-02 10:34:10,308 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4781798850034525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,308 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,328 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.81572
 2023-07-02 10:34:10,328 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,328 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.4868622028069739}
 2023-07-02 10:34:10,328 [prior] Evaluating prior at array([0.32121228, 0.4868622 ])
 2023-07-02 10:34:10,329 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,329 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4868622028069739, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,329 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,329 [classy] Re-using computed results
 2023-07-02 10:34:10,329 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
 2023-07-02 10:34:10,329 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,329 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4868622028069739, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,329 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,351 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71482
 2023-07-02 10:34:10,351 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,351 [mcmc] New sample, #484:
   Omega_m:0.3212123, b1:0.507772
 2023-07-02 10:34:10,351 [model] Posterior to be computed for parameters {'Omega_m': 0.35616082891674833, 'b1': 0.4325577681619182}
 2023-07-02 10:34:10,351 [prior] Evaluating prior at array([0.35616083, 0.43255777])
 2023-07-02 10:34:10,351 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,351 [model] Got input parameters: {'Omega_m': 0.35616082891674833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4325577681619182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,351 [classy] Got parameters {'Omega_m': 0.35616082891674833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,351 [classy] Computing new state
 2023-07-02 10:34:10,351 [classy] Setting parameters: {'Omega_m': 0.35616082891674833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.30838816793508}
 2023-07-02 10:34:10,395 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,397 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105589
 2023-07-02 10:34:10,397 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4325577681619182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,397 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,417 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.12066
 2023-07-02 10:34:10,417 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,417 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.5094937997039449}
 2023-07-02 10:34:10,417 [prior] Evaluating prior at array([0.32121228, 0.5094938 ])
 2023-07-02 10:34:10,417 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,417 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5094937997039449, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,417 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,417 [classy] Re-using computed results
 2023-07-02 10:34:10,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
 2023-07-02 10:34:10,418 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5094937997039449, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,418 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,437 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57398
 2023-07-02 10:34:10,437 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,437 [model] Posterior to be computed for parameters {'Omega_m': 0.2786443602881498, 'b1': 0.5530059177278788}
 2023-07-02 10:34:10,437 [prior] Evaluating prior at array([0.27864436, 0.55300592])
 2023-07-02 10:34:10,437 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,437 [model] Got input parameters: {'Omega_m': 0.2786443602881498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5530059177278788, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,437 [classy] Got parameters {'Omega_m': 0.2786443602881498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,437 [classy] Computing new state
 2023-07-02 10:34:10,437 [classy] Setting parameters: {'Omega_m': 0.2786443602881498, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.53949171478558}
 2023-07-02 10:34:10,481 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0768105
 2023-07-02 10:34:10,483 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5530059177278788, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,483 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,502 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.27204
 2023-07-02 10:34:10,502 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,502 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.4402588014552185}
 2023-07-02 10:34:10,502 [prior] Evaluating prior at array([0.32121228, 0.4402588 ])
 2023-07-02 10:34:10,503 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,503 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4402588014552185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,503 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,503 [classy] Re-using computed results
 2023-07-02 10:34:10,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
 2023-07-02 10:34:10,503 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4402588014552185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,503 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,523 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.42149
 2023-07-02 10:34:10,523 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,523 [model] Posterior to be computed for parameters {'Omega_m': 0.34374748760247814, 'b1': 0.4518461080164884}
 2023-07-02 10:34:10,523 [prior] Evaluating prior at array([0.34374749, 0.45184611])
 2023-07-02 10:34:10,523 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,523 [model] Got input parameters: {'Omega_m': 0.34374748760247814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4518461080164884, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,523 [classy] Got parameters {'Omega_m': 0.34374748760247814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,523 [classy] Computing new state
 2023-07-02 10:34:10,523 [classy] Setting parameters: {'Omega_m': 0.34374748760247814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.65697863221948}
 2023-07-02 10:34:10,568 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,570 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0557774
 2023-07-02 10:34:10,570 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4518461080164884, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,570 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,589 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.16934
 2023-07-02 10:34:10,589 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,589 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.5324665155345822}
 2023-07-02 10:34:10,589 [prior] Evaluating prior at array([0.32121228, 0.53246652])
 2023-07-02 10:34:10,590 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,590 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5324665155345822, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,590 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,590 [classy] Re-using computed results
 2023-07-02 10:34:10,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
 2023-07-02 10:34:10,590 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,590 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5324665155345822, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,590 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,609 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60425
 2023-07-02 10:34:10,609 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,609 [model] Posterior to be computed for parameters {'Omega_m': 0.3054329834910202, 'b1': 0.5113806972903333}
 2023-07-02 10:34:10,609 [prior] Evaluating prior at array([0.30543298, 0.5113807 ])
 2023-07-02 10:34:10,609 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,609 [model] Got input parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5113806972903333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,610 [classy] Got parameters {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,610 [classy] Computing new state
 2023-07-02 10:34:10,610 [classy] Setting parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11715388676632}
 2023-07-02 10:34:10,654 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,656 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00330551
 2023-07-02 10:34:10,656 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5113806972903333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,656 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,675 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26214
 2023-07-02 10:34:10,676 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,676 [mcmc] New sample, #485:
   Omega_m:0.3212123, b1:0.4868622
 2023-07-02 10:34:10,676 [model] Posterior to be computed for parameters {'Omega_m': 0.3054329834910202, 'b1': 0.5329205877126157}
 2023-07-02 10:34:10,676 [prior] Evaluating prior at array([0.30543298, 0.53292059])
 2023-07-02 10:34:10,676 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,676 [model] Got input parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5329205877126157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,676 [classy] Got parameters {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,676 [classy] Re-using computed results
 2023-07-02 10:34:10,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11715388676632}
 2023-07-02 10:34:10,676 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,676 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5329205877126157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,676 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,695 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.74253
 2023-07-02 10:34:10,695 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,696 [mcmc] New sample, #486:
   Omega_m:0.305433, b1:0.5113807
 2023-07-02 10:34:10,696 [model] Posterior to be computed for parameters {'Omega_m': 0.3466714096573025, 'b1': 0.46884269290370983}
 2023-07-02 10:34:10,696 [prior] Evaluating prior at array([0.34667141, 0.46884269])
 2023-07-02 10:34:10,696 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,696 [model] Got input parameters: {'Omega_m': 0.3466714096573025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46884269290370983, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,696 [classy] Got parameters {'Omega_m': 0.3466714096573025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,696 [classy] Computing new state
 2023-07-02 10:34:10,696 [classy] Setting parameters: {'Omega_m': 0.3466714096573025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.33535407585987}
 2023-07-02 10:34:10,739 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,741 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0662049
 2023-07-02 10:34:10,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46884269290370983, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,741 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,761 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.83556
 2023-07-02 10:34:10,761 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,761 [model] Posterior to be computed for parameters {'Omega_m': 0.3054329834910202, 'b1': 0.5379059386432731}
 2023-07-02 10:34:10,761 [prior] Evaluating prior at array([0.30543298, 0.53790594])
 2023-07-02 10:34:10,762 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,762 [model] Got input parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5379059386432731, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,762 [classy] Got parameters {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,762 [classy] Re-using computed results
 2023-07-02 10:34:10,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11715388676632}
 2023-07-02 10:34:10,762 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,762 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5379059386432731, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,762 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,781 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2588
 2023-07-02 10:34:10,782 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,782 [model] Posterior to be computed for parameters {'Omega_m': 0.3066714828185073, 'b1': 0.5309961585574482}
 2023-07-02 10:34:10,782 [prior] Evaluating prior at array([0.30667148, 0.53099616])
 2023-07-02 10:34:10,782 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,782 [model] Got input parameters: {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5309961585574482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,782 [classy] Got parameters {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,782 [classy] Computing new state
 2023-07-02 10:34:10,782 [classy] Setting parameters: {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,826 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.96536631029784}
 2023-07-02 10:34:10,826 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00230461
 2023-07-02 10:34:10,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5309961585574482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,828 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,847 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84926
 2023-07-02 10:34:10,847 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,847 [mcmc] New sample, #487:
   Omega_m:0.305433, b1:0.5329206
 2023-07-02 10:34:10,848 [model] Posterior to be computed for parameters {'Omega_m': 0.3066714828185073, 'b1': 0.5058593757988544}
 2023-07-02 10:34:10,848 [prior] Evaluating prior at array([0.30667148, 0.50585938])
 2023-07-02 10:34:10,848 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,848 [model] Got input parameters: {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5058593757988544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,848 [classy] Got parameters {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,848 [classy] Re-using computed results
 2023-07-02 10:34:10,848 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.96536631029784}
 2023-07-02 10:34:10,848 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,848 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5058593757988544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,848 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,867 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25892
 2023-07-02 10:34:10,867 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,868 [mcmc] New sample, #488:
   Omega_m:0.3066715, b1:0.5309962
 2023-07-02 10:34:10,868 [model] Posterior to be computed for parameters {'Omega_m': 0.31286773444713223, 'b1': 0.49623139536944677}
 2023-07-02 10:34:10,868 [prior] Evaluating prior at array([0.31286773, 0.4962314 ])
 2023-07-02 10:34:10,868 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,868 [model] Got input parameters: {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49623139536944677, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,868 [classy] Got parameters {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,868 [classy] Computing new state
 2023-07-02 10:34:10,868 [classy] Setting parameters: {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:10,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21397528964653}
 2023-07-02 10:34:10,912 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:10,914 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000211395
 2023-07-02 10:34:10,914 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49623139536944677, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,914 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,934 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72575
 2023-07-02 10:34:10,934 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,934 [mcmc] New sample, #489:
   Omega_m:0.3066715, b1:0.5058594
 2023-07-02 10:34:10,934 [model] Posterior to be computed for parameters {'Omega_m': 0.31286773444713223, 'b1': 0.44778581706410786}
 2023-07-02 10:34:10,934 [prior] Evaluating prior at array([0.31286773, 0.44778582])
 2023-07-02 10:34:10,934 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,934 [model] Got input parameters: {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44778581706410786, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,934 [classy] Got parameters {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,934 [classy] Re-using computed results
 2023-07-02 10:34:10,934 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21397528964653}
 2023-07-02 10:34:10,934 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:10,934 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44778581706410786, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,934 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:10,956 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.19744
 2023-07-02 10:34:10,957 [model] Computed derived parameters: {}
 2023-07-02 10:34:10,957 [model] Posterior to be computed for parameters {'Omega_m': 0.31733409461281564, 'b1': 0.48929138859708965}
 2023-07-02 10:34:10,957 [prior] Evaluating prior at array([0.31733409, 0.48929139])
 2023-07-02 10:34:10,957 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:10,957 [model] Got input parameters: {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48929138859708965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:10,957 [classy] Got parameters {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:10,957 [classy] Computing new state
 2023-07-02 10:34:10,957 [classy] Setting parameters: {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.68051795120985}
 2023-07-02 10:34:11,001 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00162761
 2023-07-02 10:34:11,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48929138859708965, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,003 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,022 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77636
 2023-07-02 10:34:11,023 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,023 [mcmc] New sample, #490:
   Omega_m:0.3128677, b1:0.4962314
 2023-07-02 10:34:11,023 [model] Posterior to be computed for parameters {'Omega_m': 0.31733409461281564, 'b1': 0.4502550344028314}
 2023-07-02 10:34:11,023 [prior] Evaluating prior at array([0.31733409, 0.45025503])
 2023-07-02 10:34:11,023 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,023 [model] Got input parameters: {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4502550344028314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,023 [classy] Got parameters {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,023 [classy] Re-using computed results
 2023-07-02 10:34:11,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.68051795120985}
 2023-07-02 10:34:11,023 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4502550344028314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,023 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,043 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.52291
 2023-07-02 10:34:11,043 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,043 [model] Posterior to be computed for parameters {'Omega_m': 0.32340872317006497, 'b1': 0.47985239089807324}
 2023-07-02 10:34:11,043 [prior] Evaluating prior at array([0.32340872, 0.47985239])
 2023-07-02 10:34:11,043 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,043 [model] Got input parameters: {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47985239089807324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,043 [classy] Got parameters {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,043 [classy] Computing new state
 2023-07-02 10:34:11,043 [classy] Setting parameters: {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9656353100497}
 2023-07-02 10:34:11,088 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00732628
 2023-07-02 10:34:11,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47985239089807324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,089 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,109 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4859
 2023-07-02 10:34:11,109 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,109 [mcmc] New sample, #491:
   Omega_m:0.3173341, b1:0.4892914
 2023-07-02 10:34:11,109 [model] Posterior to be computed for parameters {'Omega_m': 0.32340872317006497, 'b1': 0.4539720339372655}
 2023-07-02 10:34:11,109 [prior] Evaluating prior at array([0.32340872, 0.45397203])
 2023-07-02 10:34:11,109 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,109 [model] Got input parameters: {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4539720339372655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,109 [classy] Got parameters {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,109 [classy] Re-using computed results
 2023-07-02 10:34:11,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9656353100497}
 2023-07-02 10:34:11,109 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4539720339372655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,109 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,131 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0105943
 2023-07-02 10:34:11,131 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,131 [mcmc] New sample, #492:
   Omega_m:0.3234087, b1:0.4798524
 2023-07-02 10:34:11,131 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.44520944540855784}
 2023-07-02 10:34:11,131 [prior] Evaluating prior at array([0.32904804, 0.44520945])
 2023-07-02 10:34:11,131 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,131 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44520944540855784, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,131 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,131 [classy] Computing new state
 2023-07-02 10:34:11,131 [classy] Setting parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
 2023-07-02 10:34:11,178 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,180 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163582
 2023-07-02 10:34:11,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44520944540855784, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,180 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,199 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.42269
 2023-07-02 10:34:11,199 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,200 [mcmc] New sample, #493:
   Omega_m:0.3234087, b1:0.453972
 2023-07-02 10:34:11,200 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.4245721285514948}
 2023-07-02 10:34:11,200 [prior] Evaluating prior at array([0.32904804, 0.42457213])
 2023-07-02 10:34:11,200 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,200 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4245721285514948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,200 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,200 [classy] Re-using computed results
 2023-07-02 10:34:11,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
 2023-07-02 10:34:11,200 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,200 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4245721285514948, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,200 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,220 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.65487
 2023-07-02 10:34:11,220 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,220 [model] Posterior to be computed for parameters {'Omega_m': 0.2839196966240372, 'b1': 0.5153316425440403}
 2023-07-02 10:34:11,220 [prior] Evaluating prior at array([0.2839197 , 0.51533164])
 2023-07-02 10:34:11,220 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,220 [model] Got input parameters: {'Omega_m': 0.2839196966240372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5153316425440403, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,220 [classy] Got parameters {'Omega_m': 0.2839196966240372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,220 [classy] Computing new state
 2023-07-02 10:34:11,220 [classy] Setting parameters: {'Omega_m': 0.2839196966240372, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.84364960344837}
 2023-07-02 10:34:11,265 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0540292
 2023-07-02 10:34:11,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5153316425440403, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,266 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.62467
 2023-07-02 10:34:11,287 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,287 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.4949225915041542}
 2023-07-02 10:34:11,287 [prior] Evaluating prior at array([0.32904804, 0.49492259])
 2023-07-02 10:34:11,287 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,287 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4949225915041542, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,287 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,287 [classy] Re-using computed results
 2023-07-02 10:34:11,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
 2023-07-02 10:34:11,287 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4949225915041542, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,287 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,307 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.788821
 2023-07-02 10:34:11,307 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,307 [mcmc] New sample, #494:
   Omega_m:0.329048, b1:0.4452094
 2023-07-02 10:34:11,307 [model] Posterior to be computed for parameters {'Omega_m': 0.2907598772433001, 'b1': 0.5544162459200938}
 2023-07-02 10:34:11,307 [prior] Evaluating prior at array([0.29075988, 0.55441625])
 2023-07-02 10:34:11,307 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,307 [model] Got input parameters: {'Omega_m': 0.2907598772433001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5544162459200938, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,307 [classy] Got parameters {'Omega_m': 0.2907598772433001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,307 [classy] Computing new state
 2023-07-02 10:34:11,307 [classy] Setting parameters: {'Omega_m': 0.2907598772433001, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.95782073641158}
 2023-07-02 10:34:11,351 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,353 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0307848
 2023-07-02 10:34:11,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5544162459200938, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,353 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,373 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.06137
 2023-07-02 10:34:11,373 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,373 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.5187889953109394}
 2023-07-02 10:34:11,373 [prior] Evaluating prior at array([0.32904804, 0.518789  ])
 2023-07-02 10:34:11,373 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,373 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187889953109394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,373 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,373 [classy] Re-using computed results
 2023-07-02 10:34:11,373 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
 2023-07-02 10:34:11,373 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,373 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187889953109394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,373 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,393 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.5944
 2023-07-02 10:34:11,393 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,393 [model] Posterior to be computed for parameters {'Omega_m': 0.337995520386764, 'b1': 0.4810196385817501}
 2023-07-02 10:34:11,393 [prior] Evaluating prior at array([0.33799552, 0.48101964])
 2023-07-02 10:34:11,394 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,394 [model] Got input parameters: {'Omega_m': 0.337995520386764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4810196385817501, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,394 [classy] Got parameters {'Omega_m': 0.337995520386764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,394 [classy] Computing new state
 2023-07-02 10:34:11,394 [classy] Setting parameters: {'Omega_m': 0.337995520386764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,438 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.29707682698384}
 2023-07-02 10:34:11,438 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,439 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.037713
 2023-07-02 10:34:11,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4810196385817501, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,440 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.12921
 2023-07-02 10:34:11,459 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,459 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.48427276970913385}
 2023-07-02 10:34:11,459 [prior] Evaluating prior at array([0.32904804, 0.48427277])
 2023-07-02 10:34:11,459 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,459 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48427276970913385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,459 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,460 [classy] Re-using computed results
 2023-07-02 10:34:11,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
 2023-07-02 10:34:11,460 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48427276970913385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66519
 2023-07-02 10:34:11,479 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,479 [mcmc] New sample, #495:
   Omega_m:0.329048, b1:0.4949226
 2023-07-02 10:34:11,479 [model] Posterior to be computed for parameters {'Omega_m': 0.31429874856944495, 'b1': 0.5071907964647161}
 2023-07-02 10:34:11,479 [prior] Evaluating prior at array([0.31429875, 0.5071908 ])
 2023-07-02 10:34:11,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,480 [model] Got input parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5071907964647161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,480 [classy] Got parameters {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,480 [classy] Computing new state
 2023-07-02 10:34:11,480 [classy] Setting parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04231280591648}
 2023-07-02 10:34:11,523 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00040348
 2023-07-02 10:34:11,525 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5071907964647161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,525 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,545 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83819
 2023-07-02 10:34:11,545 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,545 [mcmc] New sample, #496:
   Omega_m:0.329048, b1:0.4842728
 2023-07-02 10:34:11,545 [model] Posterior to be computed for parameters {'Omega_m': 0.31429874856944495, 'b1': 0.489110175699167}
 2023-07-02 10:34:11,545 [prior] Evaluating prior at array([0.31429875, 0.48911018])
 2023-07-02 10:34:11,545 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,545 [model] Got input parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489110175699167, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,546 [classy] Got parameters {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,546 [classy] Re-using computed results
 2023-07-02 10:34:11,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04231280591648}
 2023-07-02 10:34:11,546 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489110175699167, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,546 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,567 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50578
 2023-07-02 10:34:11,567 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,567 [mcmc] New sample, #497:
   Omega_m:0.3142987, b1:0.5071908
 2023-07-02 10:34:11,567 [model] Posterior to be computed for parameters {'Omega_m': 0.34191966598971385, 'b1': 0.4461917036448533}
 2023-07-02 10:34:11,567 [prior] Evaluating prior at array([0.34191967, 0.4461917 ])
 2023-07-02 10:34:11,567 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,567 [model] Got input parameters: {'Omega_m': 0.34191966598971385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4461917036448533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,567 [classy] Got parameters {'Omega_m': 0.34191966598971385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,567 [classy] Computing new state
 2023-07-02 10:34:11,567 [classy] Setting parameters: {'Omega_m': 0.34191966598971385, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.85932444806298}
 2023-07-02 10:34:11,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0496803
 2023-07-02 10:34:11,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4461917036448533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,613 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,633 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.740624
 2023-07-02 10:34:11,633 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,634 [model] Posterior to be computed for parameters {'Omega_m': 0.31429874856944495, 'b1': 0.5011307796774415}
 2023-07-02 10:34:11,634 [prior] Evaluating prior at array([0.31429875, 0.50113078])
 2023-07-02 10:34:11,634 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,634 [model] Got input parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5011307796774415, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,634 [classy] Got parameters {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,634 [classy] Re-using computed results
 2023-07-02 10:34:11,634 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04231280591648}
 2023-07-02 10:34:11,634 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5011307796774415, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,634 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,654 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92159
 2023-07-02 10:34:11,654 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,654 [mcmc] New sample, #498:
   Omega_m:0.3142987, b1:0.4891102
 2023-07-02 10:34:11,654 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.4919851706651371}
 2023-07-02 10:34:11,654 [prior] Evaluating prior at array([0.32018456, 0.49198517])
 2023-07-02 10:34:11,654 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,655 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4919851706651371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,655 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,655 [classy] Computing new state
 2023-07-02 10:34:11,655 [classy] Setting parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,699 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
 2023-07-02 10:34:11,699 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,701 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00376979
 2023-07-02 10:34:11,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4919851706651371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78653
 2023-07-02 10:34:11,721 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,721 [mcmc] New sample, #499:
   Omega_m:0.3142987, b1:0.5011308
 2023-07-02 10:34:11,721 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.4578581486724014}
 2023-07-02 10:34:11,721 [prior] Evaluating prior at array([0.32018456, 0.45785815])
 2023-07-02 10:34:11,721 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,721 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4578581486724014, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,721 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,721 [classy] Re-using computed results
 2023-07-02 10:34:11,721 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
 2023-07-02 10:34:11,721 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4578581486724014, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,721 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,741 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0775476
 2023-07-02 10:34:11,741 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,741 [model] Posterior to be computed for parameters {'Omega_m': 0.3292262943898907, 'b1': 0.47793576959192724}
 2023-07-02 10:34:11,741 [prior] Evaluating prior at array([0.32922629, 0.47793577])
 2023-07-02 10:34:11,742 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,742 [model] Got input parameters: {'Omega_m': 0.3292262943898907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47793576959192724, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,742 [classy] Got parameters {'Omega_m': 0.3292262943898907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,742 [classy] Computing new state
 2023-07-02 10:34:11,742 [classy] Setting parameters: {'Omega_m': 0.3292262943898907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,787 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29216029083068}
 2023-07-02 10:34:11,788 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,789 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0167008
 2023-07-02 10:34:11,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47793576959192724, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,789 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,809 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.85172
 2023-07-02 10:34:11,809 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,809 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.5029801116990682}
 2023-07-02 10:34:11,809 [prior] Evaluating prior at array([0.32018456, 0.50298011])
 2023-07-02 10:34:11,810 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,810 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029801116990682, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,810 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,810 [classy] Re-using computed results
 2023-07-02 10:34:11,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
 2023-07-02 10:34:11,810 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029801116990682, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,810 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,829 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39189
 2023-07-02 10:34:11,829 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,829 [mcmc] New sample, #500:
   Omega_m:0.3201846, b1:0.4919852
 2023-07-02 10:34:11,829 [model] Posterior to be computed for parameters {'Omega_m': 0.35558158292288444, 'b1': 0.4479788227078772}
 2023-07-02 10:34:11,829 [prior] Evaluating prior at array([0.35558158, 0.44797882])
 2023-07-02 10:34:11,830 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,830 [model] Got input parameters: {'Omega_m': 0.35558158292288444, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4479788227078772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,830 [classy] Got parameters {'Omega_m': 0.35558158292288444, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,830 [classy] Computing new state
 2023-07-02 10:34:11,830 [classy] Setting parameters: {'Omega_m': 0.35558158292288444, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,874 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.37035377757368}
 2023-07-02 10:34:11,875 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,876 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102949
 2023-07-02 10:34:11,876 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4479788227078772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,876 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,896 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.03981
 2023-07-02 10:34:11,896 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,896 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.4974214964933156}
 2023-07-02 10:34:11,896 [prior] Evaluating prior at array([0.32018456, 0.4974215 ])
 2023-07-02 10:34:11,896 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,896 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4974214964933156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,896 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,896 [classy] Re-using computed results
 2023-07-02 10:34:11,897 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
 2023-07-02 10:34:11,897 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,897 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4974214964933156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,897 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,916 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67489
 2023-07-02 10:34:11,916 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,916 [mcmc] New sample, #501:
   Omega_m:0.3201846, b1:0.5029801
 2023-07-02 10:34:11,916 [model] Posterior to be computed for parameters {'Omega_m': 0.3043702957252894, 'b1': 0.5219943275435732}
 2023-07-02 10:34:11,917 [prior] Evaluating prior at array([0.3043703 , 0.52199433])
 2023-07-02 10:34:11,917 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,917 [model] Got input parameters: {'Omega_m': 0.3043702957252894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5219943275435732, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,917 [classy] Got parameters {'Omega_m': 0.3043702957252894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,917 [classy] Computing new state
 2023-07-02 10:34:11,917 [classy] Setting parameters: {'Omega_m': 0.3043702957252894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:11,963 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24782602547376}
 2023-07-02 10:34:11,963 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:11,965 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00432232
 2023-07-02 10:34:11,965 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5219943275435732, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,965 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:11,985 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.22297
 2023-07-02 10:34:11,985 [model] Computed derived parameters: {}
 2023-07-02 10:34:11,985 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.5232027580406549}
 2023-07-02 10:34:11,985 [prior] Evaluating prior at array([0.32018456, 0.52320276])
 2023-07-02 10:34:11,985 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:11,985 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5232027580406549, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,985 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:11,985 [classy] Re-using computed results
 2023-07-02 10:34:11,985 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
 2023-07-02 10:34:11,985 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:11,985 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5232027580406549, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:11,985 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,005 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.123277
 2023-07-02 10:34:12,005 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,005 [model] Posterior to be computed for parameters {'Omega_m': 0.30914366468903215, 'b1': 0.5145772783790518}
 2023-07-02 10:34:12,005 [prior] Evaluating prior at array([0.30914366, 0.51457728])
 2023-07-02 10:34:12,005 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,005 [model] Got input parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5145772783790518, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,005 [classy] Got parameters {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,005 [classy] Computing new state
 2023-07-02 10:34:12,005 [classy] Setting parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,051 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6639848881993}
 2023-07-02 10:34:12,051 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,054 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000892373
 2023-07-02 10:34:12,054 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5145772783790518, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,054 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,073 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68101
 2023-07-02 10:34:12,074 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,074 [mcmc] New sample, #502:
   Omega_m:0.3201846, b1:0.4974215
 2023-07-02 10:34:12,074 [model] Posterior to be computed for parameters {'Omega_m': 0.30914366468903215, 'b1': 0.47217468032976423}
 2023-07-02 10:34:12,074 [prior] Evaluating prior at array([0.30914366, 0.47217468])
 2023-07-02 10:34:12,074 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,074 [model] Got input parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47217468032976423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,074 [classy] Got parameters {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,074 [classy] Re-using computed results
 2023-07-02 10:34:12,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6639848881993}
 2023-07-02 10:34:12,074 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,074 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47217468032976423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,074 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,094 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.16686
 2023-07-02 10:34:12,094 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,094 [model] Posterior to be computed for parameters {'Omega_m': 0.30806010437272374, 'b1': 0.5162609571811367}
 2023-07-02 10:34:12,094 [prior] Evaluating prior at array([0.3080601 , 0.51626096])
 2023-07-02 10:34:12,094 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,094 [model] Got input parameters: {'Omega_m': 0.30806010437272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5162609571811367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,094 [classy] Got parameters {'Omega_m': 0.30806010437272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,094 [classy] Computing new state
 2023-07-02 10:34:12,094 [classy] Setting parameters: {'Omega_m': 0.30806010437272374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79581679673825}
 2023-07-02 10:34:12,141 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,143 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0014159
 2023-07-02 10:34:12,143 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5162609571811367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,143 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,164 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60262
 2023-07-02 10:34:12,164 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,164 [model] Posterior to be computed for parameters {'Omega_m': 0.30914366468903215, 'b1': 0.4930934681429082}
 2023-07-02 10:34:12,164 [prior] Evaluating prior at array([0.30914366, 0.49309347])
 2023-07-02 10:34:12,164 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,164 [model] Got input parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4930934681429082, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,164 [classy] Got parameters {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,164 [classy] Re-using computed results
 2023-07-02 10:34:12,165 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6639848881993}
 2023-07-02 10:34:12,165 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,165 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4930934681429082, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,165 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,184 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87314
 2023-07-02 10:34:12,184 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,184 [mcmc] New sample, #503:
   Omega_m:0.3091437, b1:0.5145773
 2023-07-02 10:34:12,185 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.4724229204548411}
 2023-07-02 10:34:12,185 [prior] Evaluating prior at array([0.32244655, 0.47242292])
 2023-07-02 10:34:12,185 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,185 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4724229204548411, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,185 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,185 [classy] Computing new state
 2023-07-02 10:34:12,185 [classy] Setting parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
 2023-07-02 10:34:12,229 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00614055
 2023-07-02 10:34:12,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4724229204548411, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,230 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,250 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08399
 2023-07-02 10:34:12,251 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,251 [mcmc] New sample, #504:
   Omega_m:0.3091437, b1:0.4930935
 2023-07-02 10:34:12,251 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.472988497226236}
 2023-07-02 10:34:12,251 [prior] Evaluating prior at array([0.32244655, 0.4729885 ])
 2023-07-02 10:34:12,251 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,251 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.472988497226236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,251 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,251 [classy] Re-using computed results
 2023-07-02 10:34:12,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
 2023-07-02 10:34:12,251 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.472988497226236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,251 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,271 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12646
 2023-07-02 10:34:12,271 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,271 [mcmc] New sample, #505:
   Omega_m:0.3224465, b1:0.4724229
 2023-07-02 10:34:12,271 [model] Posterior to be computed for parameters {'Omega_m': 0.33916422142999336, 'b1': 0.4470119185376681}
 2023-07-02 10:34:12,271 [prior] Evaluating prior at array([0.33916422, 0.44701192])
 2023-07-02 10:34:12,271 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,271 [model] Got input parameters: {'Omega_m': 0.33916422142999336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4470119185376681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,272 [classy] Got parameters {'Omega_m': 0.33916422142999336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,272 [classy] Computing new state
 2023-07-02 10:34:12,272 [classy] Setting parameters: {'Omega_m': 0.33916422142999336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.16622334514827}
 2023-07-02 10:34:12,316 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0411153
 2023-07-02 10:34:12,318 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4470119185376681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,318 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,337 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.242553
 2023-07-02 10:34:12,337 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,338 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.42161342621185954}
 2023-07-02 10:34:12,338 [prior] Evaluating prior at array([0.32244655, 0.42161343])
 2023-07-02 10:34:12,338 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,338 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42161342621185954, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,338 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,338 [classy] Re-using computed results
 2023-07-02 10:34:12,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
 2023-07-02 10:34:12,338 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42161342621185954, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,338 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,359 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.16691
 2023-07-02 10:34:12,359 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,359 [model] Posterior to be computed for parameters {'Omega_m': 0.3268219573413302, 'b1': 0.4661898157927221}
 2023-07-02 10:34:12,360 [prior] Evaluating prior at array([0.32682196, 0.46618982])
 2023-07-02 10:34:12,360 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,360 [model] Got input parameters: {'Omega_m': 0.3268219573413302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4661898157927221, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,360 [classy] Got parameters {'Omega_m': 0.3268219573413302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,360 [classy] Computing new state
 2023-07-02 10:34:12,360 [classy] Setting parameters: {'Omega_m': 0.3268219573413302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,404 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.56919739640236}
 2023-07-02 10:34:12,404 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,406 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123724
 2023-07-02 10:34:12,406 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4661898157927221, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,406 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,426 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76775
 2023-07-02 10:34:12,426 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,426 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.4080867823067048}
 2023-07-02 10:34:12,426 [prior] Evaluating prior at array([0.32244655, 0.40808678])
 2023-07-02 10:34:12,426 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,426 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4080867823067048, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,426 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,426 [classy] Re-using computed results
 2023-07-02 10:34:12,426 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
 2023-07-02 10:34:12,426 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,426 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4080867823067048, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,426 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,447 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.8965
 2023-07-02 10:34:12,447 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,447 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.49532987709028226}
 2023-07-02 10:34:12,447 [prior] Evaluating prior at array([0.30806837, 0.49532988])
 2023-07-02 10:34:12,447 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,447 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49532987709028226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,447 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,447 [classy] Computing new state
 2023-07-02 10:34:12,447 [classy] Setting parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,491 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
 2023-07-02 10:34:12,491 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,493 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00141136
 2023-07-02 10:34:12,493 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49532987709028226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,493 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,513 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81726
 2023-07-02 10:34:12,513 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,513 [mcmc] New sample, #506:
   Omega_m:0.3224465, b1:0.4729885
 2023-07-02 10:34:12,513 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.5202226877504821}
 2023-07-02 10:34:12,513 [prior] Evaluating prior at array([0.30806837, 0.52022269])
 2023-07-02 10:34:12,513 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,513 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5202226877504821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,513 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,514 [classy] Re-using computed results
 2023-07-02 10:34:12,514 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
 2023-07-02 10:34:12,514 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,514 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5202226877504821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,514 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,533 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48953
 2023-07-02 10:34:12,533 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,533 [mcmc] New sample, #507:
   Omega_m:0.3080684, b1:0.4953299
 2023-07-02 10:34:12,533 [model] Posterior to be computed for parameters {'Omega_m': 0.28684664934873944, 'b1': 0.553197838371393}
 2023-07-02 10:34:12,533 [prior] Evaluating prior at array([0.28684665, 0.55319784])
 2023-07-02 10:34:12,533 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,533 [model] Got input parameters: {'Omega_m': 0.28684664934873944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.553197838371393, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,533 [classy] Got parameters {'Omega_m': 0.28684664934873944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,533 [classy] Computing new state
 2023-07-02 10:34:12,533 [classy] Setting parameters: {'Omega_m': 0.28684664934873944, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.46234393171096}
 2023-07-02 10:34:12,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0432303
 2023-07-02 10:34:12,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.553197838371393, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,581 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,601 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1693
 2023-07-02 10:34:12,601 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,601 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.38426491990651035}
 2023-07-02 10:34:12,601 [prior] Evaluating prior at array([0.30806837, 0.38426492])
 2023-07-02 10:34:12,602 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,602 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38426491990651035, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,602 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,602 [classy] Re-using computed results
 2023-07-02 10:34:12,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
 2023-07-02 10:34:12,602 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38426491990651035, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,602 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,621 [fs_likelihood.fslikelihood] Computed log-likelihood = -36.2506
 2023-07-02 10:34:12,621 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,621 [model] Posterior to be computed for parameters {'Omega_m': 0.2884344834863504, 'b1': 0.5507305989953419}
 2023-07-02 10:34:12,621 [prior] Evaluating prior at array([0.28843448, 0.5507306 ])
 2023-07-02 10:34:12,621 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,621 [model] Got input parameters: {'Omega_m': 0.2884344834863504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5507305989953419, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,621 [classy] Got parameters {'Omega_m': 0.2884344834863504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,622 [classy] Computing new state
 2023-07-02 10:34:12,622 [classy] Setting parameters: {'Omega_m': 0.2884344834863504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.25691592411786}
 2023-07-02 10:34:12,666 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0379093
 2023-07-02 10:34:12,668 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5507305989953419, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,668 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,688 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.58953
 2023-07-02 10:34:12,688 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,688 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.5457473617190787}
 2023-07-02 10:34:12,688 [prior] Evaluating prior at array([0.30806837, 0.54574736])
 2023-07-02 10:34:12,688 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,688 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5457473617190787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,688 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,688 [classy] Re-using computed results
 2023-07-02 10:34:12,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
 2023-07-02 10:34:12,688 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5457473617190787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,688 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.345743
 2023-07-02 10:34:12,708 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,708 [model] Posterior to be computed for parameters {'Omega_m': 0.2959569323215222, 'b1': 0.5390419209836764}
 2023-07-02 10:34:12,709 [prior] Evaluating prior at array([0.29595693, 0.53904192])
 2023-07-02 10:34:12,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,709 [model] Got input parameters: {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5390419209836764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,709 [classy] Got parameters {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,709 [classy] Computing new state
 2023-07-02 10:34:12,709 [classy] Setting parameters: {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.29677926777404}
 2023-07-02 10:34:12,753 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0176667
 2023-07-02 10:34:12,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5390419209836764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,755 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,776 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.626362
 2023-07-02 10:34:12,776 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,776 [mcmc] New sample, #508:
   Omega_m:0.3080684, b1:0.5202227
 2023-07-02 10:34:12,776 [model] Posterior to be computed for parameters {'Omega_m': 0.2959569323215222, 'b1': 0.5436420521006314}
 2023-07-02 10:34:12,777 [prior] Evaluating prior at array([0.29595693, 0.54364205])
 2023-07-02 10:34:12,777 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,777 [model] Got input parameters: {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5436420521006314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,777 [classy] Got parameters {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,777 [classy] Re-using computed results
 2023-07-02 10:34:12,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.29677926777404}
 2023-07-02 10:34:12,777 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5436420521006314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,777 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,797 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.468652
 2023-07-02 10:34:12,797 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,797 [mcmc] New sample, #509:
   Omega_m:0.2959569, b1:0.5390419
 2023-07-02 10:34:12,797 [model] Posterior to be computed for parameters {'Omega_m': 0.29829523346935716, 'b1': 0.5400087074531332}
 2023-07-02 10:34:12,797 [prior] Evaluating prior at array([0.29829523, 0.54000871])
 2023-07-02 10:34:12,797 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,797 [model] Got input parameters: {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5400087074531332, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,797 [classy] Got parameters {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,797 [classy] Computing new state
 2023-07-02 10:34:12,797 [classy] Setting parameters: {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.00264105327338}
 2023-07-02 10:34:12,844 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129972
 2023-07-02 10:34:12,847 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5400087074531332, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,847 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,870 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.970597
 2023-07-02 10:34:12,870 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,870 [mcmc] New sample, #510:
   Omega_m:0.2959569, b1:0.5436421
 2023-07-02 10:34:12,871 [model] Posterior to be computed for parameters {'Omega_m': 0.29829523346935716, 'b1': 0.5359778031254079}
 2023-07-02 10:34:12,871 [prior] Evaluating prior at array([0.29829523, 0.5359778 ])
 2023-07-02 10:34:12,871 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,871 [model] Got input parameters: {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5359778031254079, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,871 [classy] Got parameters {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,871 [classy] Re-using computed results
 2023-07-02 10:34:12,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.00264105327338}
 2023-07-02 10:34:12,871 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5359778031254079, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,871 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,890 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.12861
 2023-07-02 10:34:12,890 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,890 [mcmc] New sample, #511:
   Omega_m:0.2982952, b1:0.5400087
 2023-07-02 10:34:12,891 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5037500247381678}
 2023-07-02 10:34:12,891 [prior] Evaluating prior at array([0.31903597, 0.50375002])
 2023-07-02 10:34:12,891 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,891 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5037500247381678, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,891 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,891 [classy] Computing new state
 2023-07-02 10:34:12,891 [classy] Setting parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:12,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
 2023-07-02 10:34:12,935 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:12,936 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0027923
 2023-07-02 10:34:12,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5037500247381678, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,936 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53017
 2023-07-02 10:34:12,957 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,957 [mcmc] New sample, #512:
   Omega_m:0.2982952, b1:0.5359778
 2023-07-02 10:34:12,957 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5305375474146355}
 2023-07-02 10:34:12,957 [prior] Evaluating prior at array([0.31903597, 0.53053755])
 2023-07-02 10:34:12,957 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,957 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305375474146355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,957 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,957 [classy] Re-using computed results
 2023-07-02 10:34:12,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
 2023-07-02 10:34:12,958 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:12,958 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305375474146355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,958 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:12,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10939
 2023-07-02 10:34:12,978 [model] Computed derived parameters: {}
 2023-07-02 10:34:12,978 [model] Posterior to be computed for parameters {'Omega_m': 0.32907784545320684, 'b1': 0.4881465652238691}
 2023-07-02 10:34:12,978 [prior] Evaluating prior at array([0.32907785, 0.48814657])
 2023-07-02 10:34:12,978 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:12,978 [model] Got input parameters: {'Omega_m': 0.32907784545320684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4881465652238691, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:12,978 [classy] Got parameters {'Omega_m': 0.32907784545320684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:12,978 [classy] Computing new state
 2023-07-02 10:34:12,978 [classy] Setting parameters: {'Omega_m': 0.32907784545320684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.30921156342626}
 2023-07-02 10:34:13,023 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0164153
 2023-07-02 10:34:13,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4881465652238691, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,025 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,045 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41295
 2023-07-02 10:34:13,045 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,045 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5063582201700612}
 2023-07-02 10:34:13,045 [prior] Evaluating prior at array([0.31903597, 0.50635822])
 2023-07-02 10:34:13,045 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,045 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5063582201700612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,045 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,045 [classy] Re-using computed results
 2023-07-02 10:34:13,045 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
 2023-07-02 10:34:13,045 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5063582201700612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,045 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,065 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35721
 2023-07-02 10:34:13,065 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,065 [mcmc] New sample, #513:
   Omega_m:0.319036, b1:0.50375
 2023-07-02 10:34:13,065 [model] Posterior to be computed for parameters {'Omega_m': 0.2967908058250944, 'b1': 0.540923637630819}
 2023-07-02 10:34:13,065 [prior] Evaluating prior at array([0.29679081, 0.54092364])
 2023-07-02 10:34:13,065 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,065 [model] Got input parameters: {'Omega_m': 0.2967908058250944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.540923637630819, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,066 [classy] Got parameters {'Omega_m': 0.2967908058250944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,066 [classy] Computing new state
 2023-07-02 10:34:13,066 [classy] Setting parameters: {'Omega_m': 0.2967908058250944, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,111 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19165463580433}
 2023-07-02 10:34:13,111 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,113 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159151
 2023-07-02 10:34:13,113 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.540923637630819, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,113 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,135 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.719399
 2023-07-02 10:34:13,135 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,135 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5274775741735493}
 2023-07-02 10:34:13,136 [prior] Evaluating prior at array([0.31903597, 0.52747757])
 2023-07-02 10:34:13,136 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,136 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5274775741735493, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,136 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,136 [classy] Re-using computed results
 2023-07-02 10:34:13,136 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
 2023-07-02 10:34:13,136 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,136 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5274775741735493, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,136 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.480471
 2023-07-02 10:34:13,156 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3045926526944758, 'b1': 0.5288008199220247}
 2023-07-02 10:34:13,156 [prior] Evaluating prior at array([0.30459265, 0.52880082])
 2023-07-02 10:34:13,157 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,157 [model] Got input parameters: {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5288008199220247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,157 [classy] Got parameters {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,157 [classy] Computing new state
 2023-07-02 10:34:13,157 [classy] Setting parameters: {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22044885211443}
 2023-07-02 10:34:13,201 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,203 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0040974
 2023-07-02 10:34:13,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5288008199220247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,203 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,222 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02047
 2023-07-02 10:34:13,222 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,222 [mcmc] New sample, #514:
   Omega_m:0.319036, b1:0.5063582
 2023-07-02 10:34:13,223 [model] Posterior to be computed for parameters {'Omega_m': 0.3045926526944758, 'b1': 0.5750502179088995}
 2023-07-02 10:34:13,223 [prior] Evaluating prior at array([0.30459265, 0.57505022])
 2023-07-02 10:34:13,223 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,223 [model] Got input parameters: {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5750502179088995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,223 [classy] Got parameters {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,223 [classy] Re-using computed results
 2023-07-02 10:34:13,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22044885211443}
 2023-07-02 10:34:13,223 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5750502179088995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,223 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.51356
 2023-07-02 10:34:13,243 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3329935482126437, 'b1': 0.4846703871030373}
 2023-07-02 10:34:13,243 [prior] Evaluating prior at array([0.33299355, 0.48467039])
 2023-07-02 10:34:13,243 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,243 [model] Got input parameters: {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4846703871030373, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,243 [classy] Got parameters {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,243 [classy] Computing new state
 2023-07-02 10:34:13,243 [classy] Setting parameters: {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.86177602254241}
 2023-07-02 10:34:13,287 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,288 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247368
 2023-07-02 10:34:13,289 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4846703871030373, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,289 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,308 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.475105
 2023-07-02 10:34:13,308 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,308 [mcmc] New sample, #515:
   Omega_m:0.3045927, b1:0.5288008
 2023-07-02 10:34:13,308 [model] Posterior to be computed for parameters {'Omega_m': 0.3329935482126437, 'b1': 0.536250374737656}
 2023-07-02 10:34:13,308 [prior] Evaluating prior at array([0.33299355, 0.53625037])
 2023-07-02 10:34:13,309 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,309 [model] Got input parameters: {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.536250374737656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,309 [classy] Got parameters {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,309 [classy] Re-using computed results
 2023-07-02 10:34:13,309 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.86177602254241}
 2023-07-02 10:34:13,309 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.536250374737656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,309 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,328 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.5
 2023-07-02 10:34:13,328 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,328 [model] Posterior to be computed for parameters {'Omega_m': 0.32248407342681396, 'b1': 0.501000423974664}
 2023-07-02 10:34:13,328 [prior] Evaluating prior at array([0.32248407, 0.50100042])
 2023-07-02 10:34:13,328 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,328 [model] Got input parameters: {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.501000423974664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,328 [classy] Got parameters {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,329 [classy] Computing new state
 2023-07-02 10:34:13,329 [classy] Setting parameters: {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,372 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07367588992582}
 2023-07-02 10:34:13,373 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,374 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0061848
 2023-07-02 10:34:13,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.501000423974664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,374 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,394 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07894
 2023-07-02 10:34:13,394 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,394 [mcmc] New sample, #516:
   Omega_m:0.3329935, b1:0.4846704
 2023-07-02 10:34:13,394 [model] Posterior to be computed for parameters {'Omega_m': 0.32248407342681396, 'b1': 0.48824752371618907}
 2023-07-02 10:34:13,394 [prior] Evaluating prior at array([0.32248407, 0.48824752])
 2023-07-02 10:34:13,394 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,394 [model] Got input parameters: {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48824752371618907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,394 [classy] Got parameters {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,394 [classy] Re-using computed results
 2023-07-02 10:34:13,394 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07367588992582}
 2023-07-02 10:34:13,394 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48824752371618907, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,394 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,414 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63086
 2023-07-02 10:34:13,414 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,414 [mcmc] New sample, #517:
   Omega_m:0.3224841, b1:0.5010004
 2023-07-02 10:34:13,414 [model] Posterior to be computed for parameters {'Omega_m': 0.32397525072247496, 'b1': 0.48593047355749697}
 2023-07-02 10:34:13,414 [prior] Evaluating prior at array([0.32397525, 0.48593047])
 2023-07-02 10:34:13,415 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,415 [model] Got input parameters: {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48593047355749697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,415 [classy] Got parameters {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,415 [classy] Computing new state
 2023-07-02 10:34:13,415 [classy] Setting parameters: {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89957713272946}
 2023-07-02 10:34:13,458 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,460 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00807345
 2023-07-02 10:34:13,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48593047355749697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49928
 2023-07-02 10:34:13,480 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,480 [mcmc] New sample, #518:
   Omega_m:0.3224841, b1:0.4882475
 2023-07-02 10:34:13,480 [model] Posterior to be computed for parameters {'Omega_m': 0.32397525072247496, 'b1': 0.4865474541046453}
 2023-07-02 10:34:13,480 [prior] Evaluating prior at array([0.32397525, 0.48654745])
 2023-07-02 10:34:13,480 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,480 [model] Got input parameters: {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4865474541046453, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,480 [classy] Got parameters {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,480 [classy] Re-using computed results
 2023-07-02 10:34:13,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89957713272946}
 2023-07-02 10:34:13,480 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4865474541046453, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49196
 2023-07-02 10:34:13,499 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,499 [mcmc] New sample, #519:
   Omega_m:0.3239753, b1:0.4859305
 2023-07-02 10:34:13,499 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.5075545252847312}
 2023-07-02 10:34:13,499 [prior] Evaluating prior at array([0.31045579, 0.50755453])
 2023-07-02 10:34:13,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,500 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5075545252847312, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,500 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,500 [classy] Computing new state
 2023-07-02 10:34:13,500 [classy] Setting parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,543 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
 2023-07-02 10:34:13,543 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,545 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000455923
 2023-07-02 10:34:13,545 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5075545252847312, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,545 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,566 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79516
 2023-07-02 10:34:13,566 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,566 [mcmc] New sample, #520:
   Omega_m:0.3239753, b1:0.4865475
 2023-07-02 10:34:13,566 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.47103066484752953}
 2023-07-02 10:34:13,566 [prior] Evaluating prior at array([0.31045579, 0.47103066])
 2023-07-02 10:34:13,566 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,566 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47103066484752953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,566 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,566 [classy] Re-using computed results
 2023-07-02 10:34:13,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
 2023-07-02 10:34:13,566 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47103066484752953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,566 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,585 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.849818
 2023-07-02 10:34:13,586 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,586 [model] Posterior to be computed for parameters {'Omega_m': 0.26781637744500997, 'b1': 0.5738093287443314}
 2023-07-02 10:34:13,586 [prior] Evaluating prior at array([0.26781638, 0.57380933])
 2023-07-02 10:34:13,586 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,586 [model] Got input parameters: {'Omega_m': 0.26781637744500997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5738093287443314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,586 [classy] Got parameters {'Omega_m': 0.26781637744500997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,586 [classy] Computing new state
 2023-07-02 10:34:13,586 [classy] Setting parameters: {'Omega_m': 0.26781637744500997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.00370750356993}
 2023-07-02 10:34:13,630 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,632 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.137629
 2023-07-02 10:34:13,632 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5738093287443314, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,632 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,651 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.8092
 2023-07-02 10:34:13,651 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,651 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.5009915285883733}
 2023-07-02 10:34:13,651 [prior] Evaluating prior at array([0.31045579, 0.50099153])
 2023-07-02 10:34:13,652 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,652 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5009915285883733, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,652 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,652 [classy] Re-using computed results
 2023-07-02 10:34:13,652 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
 2023-07-02 10:34:13,652 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5009915285883733, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,652 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,672 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64389
 2023-07-02 10:34:13,672 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,672 [mcmc] New sample, #521:
   Omega_m:0.3104558, b1:0.5075545
 2023-07-02 10:34:13,672 [model] Posterior to be computed for parameters {'Omega_m': 0.35345616051831985, 'b1': 0.43417585576205}
 2023-07-02 10:34:13,672 [prior] Evaluating prior at array([0.35345616, 0.43417586])
 2023-07-02 10:34:13,672 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,672 [model] Got input parameters: {'Omega_m': 0.35345616051831985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43417585576205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,672 [classy] Got parameters {'Omega_m': 0.35345616051831985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,672 [classy] Computing new state
 2023-07-02 10:34:13,672 [classy] Setting parameters: {'Omega_m': 0.35345616051831985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,716 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.59851703486868}
 2023-07-02 10:34:13,716 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,717 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0935194
 2023-07-02 10:34:13,718 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43417585576205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,718 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,737 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.1004
 2023-07-02 10:34:13,737 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,737 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.5093538630087164}
 2023-07-02 10:34:13,737 [prior] Evaluating prior at array([0.31045579, 0.50935386])
 2023-07-02 10:34:13,737 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,737 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5093538630087164, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,737 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,737 [classy] Re-using computed results
 2023-07-02 10:34:13,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
 2023-07-02 10:34:13,737 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,737 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5093538630087164, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,737 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79656
 2023-07-02 10:34:13,756 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,756 [mcmc] New sample, #522:
   Omega_m:0.3104558, b1:0.5009915
 2023-07-02 10:34:13,757 [model] Posterior to be computed for parameters {'Omega_m': 0.2955766192553714, 'b1': 0.5324737066756817}
 2023-07-02 10:34:13,757 [prior] Evaluating prior at array([0.29557662, 0.53247371])
 2023-07-02 10:34:13,757 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,757 [model] Got input parameters: {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5324737066756817, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,757 [classy] Got parameters {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,757 [classy] Computing new state
 2023-07-02 10:34:13,757 [classy] Setting parameters: {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.34481007152823}
 2023-07-02 10:34:13,801 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,802 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0184976
 2023-07-02 10:34:13,802 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5324737066756817, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,803 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.551695
 2023-07-02 10:34:13,822 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,822 [mcmc] New sample, #523:
   Omega_m:0.3104558, b1:0.5093539
 2023-07-02 10:34:13,822 [model] Posterior to be computed for parameters {'Omega_m': 0.2955766192553714, 'b1': 0.5366569261785293}
 2023-07-02 10:34:13,823 [prior] Evaluating prior at array([0.29557662, 0.53665693])
 2023-07-02 10:34:13,823 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,823 [model] Got input parameters: {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366569261785293, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,823 [classy] Got parameters {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,823 [classy] Re-using computed results
 2023-07-02 10:34:13,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.34481007152823}
 2023-07-02 10:34:13,823 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,823 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366569261785293, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,823 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,842 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.574729
 2023-07-02 10:34:13,842 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,842 [mcmc] New sample, #524:
   Omega_m:0.2955766, b1:0.5324737
 2023-07-02 10:34:13,842 [model] Posterior to be computed for parameters {'Omega_m': 0.2969264084429165, 'b1': 0.5345595704447057}
 2023-07-02 10:34:13,842 [prior] Evaluating prior at array([0.29692641, 0.53455957])
 2023-07-02 10:34:13,842 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,842 [model] Got input parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5345595704447057, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,842 [classy] Got parameters {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,843 [classy] Computing new state
 2023-07-02 10:34:13,843 [classy] Setting parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,886 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.174583717974}
 2023-07-02 10:34:13,886 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,888 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156393
 2023-07-02 10:34:13,888 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5345595704447057, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,888 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,907 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.896116
 2023-07-02 10:34:13,907 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,908 [mcmc] New sample, #525:
   Omega_m:0.2955766, b1:0.5366569
 2023-07-02 10:34:13,908 [model] Posterior to be computed for parameters {'Omega_m': 0.2969264084429165, 'b1': 0.548243766317192}
 2023-07-02 10:34:13,908 [prior] Evaluating prior at array([0.29692641, 0.54824377])
 2023-07-02 10:34:13,908 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,908 [model] Got input parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.548243766317192, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,908 [classy] Got parameters {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,908 [classy] Re-using computed results
 2023-07-02 10:34:13,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.174583717974}
 2023-07-02 10:34:13,908 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.548243766317192, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,908 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,928 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.290385
 2023-07-02 10:34:13,928 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,928 [model] Posterior to be computed for parameters {'Omega_m': 0.2809456529794828, 'b1': 0.5593910992577528}
 2023-07-02 10:34:13,928 [prior] Evaluating prior at array([0.28094565, 0.5593911 ])
 2023-07-02 10:34:13,928 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,928 [model] Got input parameters: {'Omega_m': 0.2809456529794828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5593910992577528, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,928 [classy] Got parameters {'Omega_m': 0.2809456529794828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,928 [classy] Computing new state
 2023-07-02 10:34:13,928 [classy] Setting parameters: {'Omega_m': 0.2809456529794828, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:13,972 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.2345674521532}
 2023-07-02 10:34:13,972 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:13,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0663397
 2023-07-02 10:34:13,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5593910992577528, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,974 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:13,993 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.70358
 2023-07-02 10:34:13,993 [model] Computed derived parameters: {}
 2023-07-02 10:34:13,994 [model] Posterior to be computed for parameters {'Omega_m': 0.2969264084429165, 'b1': 0.5149500474456896}
 2023-07-02 10:34:13,994 [prior] Evaluating prior at array([0.29692641, 0.51495005])
 2023-07-02 10:34:13,994 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:13,994 [model] Got input parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5149500474456896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,994 [classy] Got parameters {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:13,994 [classy] Re-using computed results
 2023-07-02 10:34:13,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.174583717974}
 2023-07-02 10:34:13,994 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:13,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5149500474456896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:13,994 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,013 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0392728
 2023-07-02 10:34:14,013 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,014 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.49732462572515457}
 2023-07-02 10:34:14,014 [prior] Evaluating prior at array([0.32088959, 0.49732463])
 2023-07-02 10:34:14,014 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,014 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49732462572515457, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,014 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,014 [classy] Computing new state
 2023-07-02 10:34:14,014 [classy] Setting parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
 2023-07-02 10:34:14,058 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00444565
 2023-07-02 10:34:14,059 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49732462572515457, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,059 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,079 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58803
 2023-07-02 10:34:14,079 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,079 [mcmc] New sample, #526:
   Omega_m:0.2969264, b1:0.5345596
 2023-07-02 10:34:14,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.48072130998151774}
 2023-07-02 10:34:14,079 [prior] Evaluating prior at array([0.32088959, 0.48072131])
 2023-07-02 10:34:14,080 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,080 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48072130998151774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,080 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,080 [classy] Re-using computed results
 2023-07-02 10:34:14,080 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
 2023-07-02 10:34:14,080 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,080 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48072130998151774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,080 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,099 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53391
 2023-07-02 10:34:14,099 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,099 [mcmc] New sample, #527:
   Omega_m:0.3208896, b1:0.4973246
 2023-07-02 10:34:14,099 [model] Posterior to be computed for parameters {'Omega_m': 0.32998748087741514, 'b1': 0.46658465499003154}
 2023-07-02 10:34:14,099 [prior] Evaluating prior at array([0.32998748, 0.46658465])
 2023-07-02 10:34:14,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,099 [model] Got input parameters: {'Omega_m': 0.32998748087741514, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46658465499003154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,099 [classy] Got parameters {'Omega_m': 0.32998748087741514, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,099 [classy] Computing new state
 2023-07-02 10:34:14,099 [classy] Setting parameters: {'Omega_m': 0.32998748087741514, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,145 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.20483975668554}
 2023-07-02 10:34:14,145 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,147 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.018202
 2023-07-02 10:34:14,147 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46658465499003154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,147 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,167 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65273
 2023-07-02 10:34:14,167 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,167 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.4914201906985417}
 2023-07-02 10:34:14,167 [prior] Evaluating prior at array([0.32088959, 0.49142019])
 2023-07-02 10:34:14,167 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,167 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4914201906985417, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,167 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,167 [classy] Re-using computed results
 2023-07-02 10:34:14,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
 2023-07-02 10:34:14,167 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4914201906985417, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,167 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,187 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74012
 2023-07-02 10:34:14,187 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,187 [mcmc] New sample, #528:
   Omega_m:0.3208896, b1:0.4807213
 2023-07-02 10:34:14,187 [model] Posterior to be computed for parameters {'Omega_m': 0.3394240710259384, 'b1': 0.4626205893459687}
 2023-07-02 10:34:14,187 [prior] Evaluating prior at array([0.33942407, 0.46262059])
 2023-07-02 10:34:14,187 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,187 [model] Got input parameters: {'Omega_m': 0.3394240710259384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4626205893459687, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,187 [classy] Got parameters {'Omega_m': 0.3394240710259384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,187 [classy] Computing new state
 2023-07-02 10:34:14,187 [classy] Setting parameters: {'Omega_m': 0.3394240710259384, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1371836551355}
 2023-07-02 10:34:14,231 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,233 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0418906
 2023-07-02 10:34:14,233 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4626205893459687, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,233 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,252 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.169645
 2023-07-02 10:34:14,252 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,252 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.5125021485812256}
 2023-07-02 10:34:14,252 [prior] Evaluating prior at array([0.32088959, 0.51250215])
 2023-07-02 10:34:14,253 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,253 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5125021485812256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,253 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,253 [classy] Re-using computed results
 2023-07-02 10:34:14,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
 2023-07-02 10:34:14,253 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5125021485812256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,253 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,272 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.30125
 2023-07-02 10:34:14,272 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,273 [mcmc] New sample, #529:
   Omega_m:0.3208896, b1:0.4914202
 2023-07-02 10:34:14,273 [model] Posterior to be computed for parameters {'Omega_m': 0.3742789649137844, 'b1': 0.42954363691730113}
 2023-07-02 10:34:14,273 [prior] Evaluating prior at array([0.37427896, 0.42954364])
 2023-07-02 10:34:14,273 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,273 [model] Got input parameters: {'Omega_m': 0.3742789649137844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42954363691730113, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,273 [classy] Got parameters {'Omega_m': 0.3742789649137844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,273 [classy] Computing new state
 2023-07-02 10:34:14,273 [classy] Setting parameters: {'Omega_m': 0.3742789649137844, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.41593136378663}
 2023-07-02 10:34:14,317 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.202697
 2023-07-02 10:34:14,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42954363691730113, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,319 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,338 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.0553
 2023-07-02 10:34:14,338 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,338 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.5276839073412256}
 2023-07-02 10:34:14,338 [prior] Evaluating prior at array([0.32088959, 0.52768391])
 2023-07-02 10:34:14,338 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,338 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5276839073412256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,339 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,339 [classy] Re-using computed results
 2023-07-02 10:34:14,339 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
 2023-07-02 10:34:14,339 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,339 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5276839073412256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,339 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,358 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.32306
 2023-07-02 10:34:14,358 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,358 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.5169274422190248}
 2023-07-02 10:34:14,358 [prior] Evaluating prior at array([0.31804162, 0.51692744])
 2023-07-02 10:34:14,358 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,358 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5169274422190248, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,358 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,358 [classy] Computing new state
 2023-07-02 10:34:14,358 [classy] Setting parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
 2023-07-02 10:34:14,402 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00207043
 2023-07-02 10:34:14,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5169274422190248, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,404 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,424 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.53143
 2023-07-02 10:34:14,424 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,424 [mcmc] New sample, #530:
   Omega_m:0.3208896, b1:0.5125021
 2023-07-02 10:34:14,424 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.5300526785045339}
 2023-07-02 10:34:14,424 [prior] Evaluating prior at array([0.31804162, 0.53005268])
 2023-07-02 10:34:14,424 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,424 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5300526785045339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,424 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,424 [classy] Re-using computed results
 2023-07-02 10:34:14,424 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
 2023-07-02 10:34:14,424 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5300526785045339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,424 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,443 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.593656
 2023-07-02 10:34:14,443 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,443 [model] Posterior to be computed for parameters {'Omega_m': 0.25254614923597263, 'b1': 0.6186968923383961}
 2023-07-02 10:34:14,444 [prior] Evaluating prior at array([0.25254615, 0.61869689])
 2023-07-02 10:34:14,444 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,444 [model] Got input parameters: {'Omega_m': 0.25254614923597263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6186968923383961, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,444 [classy] Got parameters {'Omega_m': 0.25254614923597263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,444 [classy] Computing new state
 2023-07-02 10:34:14,444 [classy] Setting parameters: {'Omega_m': 0.25254614923597263, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,487 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.1558554817771}
 2023-07-02 10:34:14,487 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,489 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.258344
 2023-07-02 10:34:14,489 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6186968923383961, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,489 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,508 [fs_likelihood.fslikelihood] Computed log-likelihood = -25.8119
 2023-07-02 10:34:14,508 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,508 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.5186987346080698}
 2023-07-02 10:34:14,508 [prior] Evaluating prior at array([0.31804162, 0.51869873])
 2023-07-02 10:34:14,509 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,509 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5186987346080698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,509 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,509 [classy] Re-using computed results
 2023-07-02 10:34:14,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
 2023-07-02 10:34:14,509 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5186987346080698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,528 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.30354
 2023-07-02 10:34:14,528 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,529 [model] Posterior to be computed for parameters {'Omega_m': 0.3309140129975722, 'b1': 0.49692581139883557}
 2023-07-02 10:34:14,529 [prior] Evaluating prior at array([0.33091401, 0.49692581])
 2023-07-02 10:34:14,529 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,529 [model] Got input parameters: {'Omega_m': 0.3309140129975722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49692581139883557, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,529 [classy] Got parameters {'Omega_m': 0.3309140129975722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,529 [classy] Computing new state
 2023-07-02 10:34:14,529 [classy] Setting parameters: {'Omega_m': 0.3309140129975722, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09880081260047}
 2023-07-02 10:34:14,573 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0201133
 2023-07-02 10:34:14,575 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49692581139883557, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,575 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,594 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.187871
 2023-07-02 10:34:14,594 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,594 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.48229945233365085}
 2023-07-02 10:34:14,594 [prior] Evaluating prior at array([0.31804162, 0.48229945])
 2023-07-02 10:34:14,594 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,594 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48229945233365085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,594 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,594 [classy] Re-using computed results
 2023-07-02 10:34:14,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
 2023-07-02 10:34:14,595 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,595 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48229945233365085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,595 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,613 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46262
 2023-07-02 10:34:14,614 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,614 [mcmc] New sample, #531:
   Omega_m:0.3180416, b1:0.5169274
 2023-07-02 10:34:14,614 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.4727187946889358}
 2023-07-02 10:34:14,614 [prior] Evaluating prior at array([0.32420742, 0.47271879])
 2023-07-02 10:34:14,614 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,614 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4727187946889358, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,614 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,614 [classy] Computing new state
 2023-07-02 10:34:14,614 [classy] Setting parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
 2023-07-02 10:34:14,658 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,660 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0083901
 2023-07-02 10:34:14,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4727187946889358, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,660 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,680 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1659
 2023-07-02 10:34:14,680 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,680 [mcmc] New sample, #532:
   Omega_m:0.3180416, b1:0.4822995
 2023-07-02 10:34:14,680 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.49706249878377906}
 2023-07-02 10:34:14,680 [prior] Evaluating prior at array([0.32420742, 0.4970625 ])
 2023-07-02 10:34:14,680 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,680 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49706249878377906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,680 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,680 [classy] Re-using computed results
 2023-07-02 10:34:14,680 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
 2023-07-02 10:34:14,680 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,680 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49706249878377906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,680 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,700 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99052
 2023-07-02 10:34:14,700 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,700 [mcmc] New sample, #533:
   Omega_m:0.3242074, b1:0.4727188
 2023-07-02 10:34:14,700 [model] Posterior to be computed for parameters {'Omega_m': 0.4057375928175148, 'b1': 0.37037769299753937}
 2023-07-02 10:34:14,700 [prior] Evaluating prior at array([0.40573759, 0.37037769])
 2023-07-02 10:34:14,700 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,700 [model] Got input parameters: {'Omega_m': 0.4057375928175148, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37037769299753937, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,700 [classy] Got parameters {'Omega_m': 0.4057375928175148, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,700 [classy] Computing new state
 2023-07-02 10:34:14,700 [classy] Setting parameters: {'Omega_m': 0.4057375928175148, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,744 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.32538784219003}
 2023-07-02 10:34:14,744 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,746 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.430951
 2023-07-02 10:34:14,746 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37037769299753937, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,746 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,765 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.2374
 2023-07-02 10:34:14,765 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,765 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.5041277243174977}
 2023-07-02 10:34:14,765 [prior] Evaluating prior at array([0.32420742, 0.50412772])
 2023-07-02 10:34:14,765 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,765 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5041277243174977, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,766 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,766 [classy] Re-using computed results
 2023-07-02 10:34:14,766 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
 2023-07-02 10:34:14,766 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5041277243174977, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,786 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32215
 2023-07-02 10:34:14,786 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,786 [model] Posterior to be computed for parameters {'Omega_m': 0.3486394467695948, 'b1': 0.459099046753606}
 2023-07-02 10:34:14,786 [prior] Evaluating prior at array([0.34863945, 0.45909905])
 2023-07-02 10:34:14,786 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,786 [model] Got input parameters: {'Omega_m': 0.3486394467695948, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.459099046753606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,786 [classy] Got parameters {'Omega_m': 0.3486394467695948, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,786 [classy] Computing new state
 2023-07-02 10:34:14,786 [classy] Setting parameters: {'Omega_m': 0.3486394467695948, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,830 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.12027525009282}
 2023-07-02 10:34:14,830 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0736839
 2023-07-02 10:34:14,832 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.459099046753606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,832 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,851 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.61308
 2023-07-02 10:34:14,851 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,852 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.510588638679861}
 2023-07-02 10:34:14,852 [prior] Evaluating prior at array([0.32420742, 0.51058864])
 2023-07-02 10:34:14,852 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,852 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510588638679861, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,852 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,852 [classy] Re-using computed results
 2023-07-02 10:34:14,852 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
 2023-07-02 10:34:14,852 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,852 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510588638679861, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,852 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,871 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.458527
 2023-07-02 10:34:14,871 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,871 [model] Posterior to be computed for parameters {'Omega_m': 0.30523756247332773, 'b1': 0.5265386082254843}
 2023-07-02 10:34:14,871 [prior] Evaluating prior at array([0.30523756, 0.52653861])
 2023-07-02 10:34:14,871 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,871 [model] Got input parameters: {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5265386082254843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,871 [classy] Got parameters {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,871 [classy] Computing new state
 2023-07-02 10:34:14,872 [classy] Setting parameters: {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:14,915 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14115013602412}
 2023-07-02 10:34:14,915 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:14,917 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00348146
 2023-07-02 10:34:14,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5265386082254843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,917 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,937 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.153
 2023-07-02 10:34:14,937 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,937 [mcmc] New sample, #534:
   Omega_m:0.3242074, b1:0.4970625
 2023-07-02 10:34:14,937 [model] Posterior to be computed for parameters {'Omega_m': 0.30523756247332773, 'b1': 0.5398967333955982}
 2023-07-02 10:34:14,937 [prior] Evaluating prior at array([0.30523756, 0.53989673])
 2023-07-02 10:34:14,937 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,937 [model] Got input parameters: {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5398967333955982, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,937 [classy] Got parameters {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,937 [classy] Re-using computed results
 2023-07-02 10:34:14,937 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14115013602412}
 2023-07-02 10:34:14,937 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:14,938 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5398967333955982, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,938 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:14,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.04669
 2023-07-02 10:34:14,957 [model] Computed derived parameters: {}
 2023-07-02 10:34:14,957 [mcmc] New sample, #535:
   Omega_m:0.3052376, b1:0.5265386
 2023-07-02 10:34:14,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3153610714768006, 'b1': 0.5241664253958245}
 2023-07-02 10:34:14,957 [prior] Evaluating prior at array([0.31536107, 0.52416643])
 2023-07-02 10:34:14,957 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:14,957 [model] Got input parameters: {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241664253958245, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:14,957 [classy] Got parameters {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:14,957 [classy] Computing new state
 2023-07-02 10:34:14,957 [classy] Setting parameters: {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91533241195924}
 2023-07-02 10:34:15,001 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000706452
 2023-07-02 10:34:15,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241664253958245, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,003 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,023 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.27115
 2023-07-02 10:34:15,023 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,023 [mcmc] New sample, #536:
   Omega_m:0.3052376, b1:0.5398967
 2023-07-02 10:34:15,023 [model] Posterior to be computed for parameters {'Omega_m': 0.3153610714768006, 'b1': 0.5082600859606241}
 2023-07-02 10:34:15,023 [prior] Evaluating prior at array([0.31536107, 0.50826009])
 2023-07-02 10:34:15,023 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,023 [model] Got input parameters: {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5082600859606241, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,023 [classy] Got parameters {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,023 [classy] Re-using computed results
 2023-07-02 10:34:15,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91533241195924}
 2023-07-02 10:34:15,023 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5082600859606241, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,023 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,043 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.7269
 2023-07-02 10:34:15,043 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,043 [mcmc] New sample, #537:
   Omega_m:0.3153611, b1:0.5241664
 2023-07-02 10:34:15,043 [model] Posterior to be computed for parameters {'Omega_m': 0.30986375112911274, 'b1': 0.5168020393695545}
 2023-07-02 10:34:15,043 [prior] Evaluating prior at array([0.30986375, 0.51680204])
 2023-07-02 10:34:15,043 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,044 [model] Got input parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5168020393695545, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,044 [classy] Got parameters {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,044 [classy] Computing new state
 2023-07-02 10:34:15,044 [classy] Setting parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5765990208315}
 2023-07-02 10:34:15,087 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000626182
 2023-07-02 10:34:15,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5168020393695545, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,089 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,109 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62627
 2023-07-02 10:34:15,109 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,109 [mcmc] New sample, #538:
   Omega_m:0.3153611, b1:0.5082601
 2023-07-02 10:34:15,109 [model] Posterior to be computed for parameters {'Omega_m': 0.30986375112911274, 'b1': 0.4796261148221118}
 2023-07-02 10:34:15,109 [prior] Evaluating prior at array([0.30986375, 0.47962611])
 2023-07-02 10:34:15,109 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,109 [model] Got input parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4796261148221118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,109 [classy] Got parameters {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,109 [classy] Re-using computed results
 2023-07-02 10:34:15,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5765990208315}
 2023-07-02 10:34:15,109 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4796261148221118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,109 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,131 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.413385
 2023-07-02 10:34:15,131 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,132 [model] Posterior to be computed for parameters {'Omega_m': 0.33003535821164065, 'b1': 0.4854585998418444}
 2023-07-02 10:34:15,132 [prior] Evaluating prior at array([0.33003536, 0.4854586 ])
 2023-07-02 10:34:15,132 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,132 [model] Got input parameters: {'Omega_m': 0.33003535821164065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4854585998418444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,132 [classy] Got parameters {'Omega_m': 0.33003535821164065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,132 [classy] Computing new state
 2023-07-02 10:34:15,132 [classy] Setting parameters: {'Omega_m': 0.33003535821164065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,177 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.19935233230783}
 2023-07-02 10:34:15,177 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,179 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0182985
 2023-07-02 10:34:15,179 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4854585998418444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,179 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,198 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3398
 2023-07-02 10:34:15,198 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,198 [model] Posterior to be computed for parameters {'Omega_m': 0.30986375112911274, 'b1': 0.46817791628454336}
 2023-07-02 10:34:15,198 [prior] Evaluating prior at array([0.30986375, 0.46817792])
 2023-07-02 10:34:15,199 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,199 [model] Got input parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46817791628454336, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,199 [classy] Got parameters {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,199 [classy] Re-using computed results
 2023-07-02 10:34:15,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5765990208315}
 2023-07-02 10:34:15,199 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46817791628454336, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,199 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,218 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.66685
 2023-07-02 10:34:15,218 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,218 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.5220597727436418}
 2023-07-02 10:34:15,218 [prior] Evaluating prior at array([0.30648005, 0.52205977])
 2023-07-02 10:34:15,218 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,218 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5220597727436418, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,218 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,218 [classy] Computing new state
 2023-07-02 10:34:15,218 [classy] Setting parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
 2023-07-02 10:34:15,262 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,264 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00244642
 2023-07-02 10:34:15,264 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5220597727436418, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,264 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37936
 2023-07-02 10:34:15,284 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,284 [mcmc] New sample, #539:
   Omega_m:0.3098638, b1:0.516802
 2023-07-02 10:34:15,284 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.4562033062552549}
 2023-07-02 10:34:15,284 [prior] Evaluating prior at array([0.30648005, 0.45620331])
 2023-07-02 10:34:15,284 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,284 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4562033062552549, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,284 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,284 [classy] Re-using computed results
 2023-07-02 10:34:15,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
 2023-07-02 10:34:15,285 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4562033062552549, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,285 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46358
 2023-07-02 10:34:15,304 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,304 [model] Posterior to be computed for parameters {'Omega_m': 0.36030100945801946, 'b1': 0.4384306359455362}
 2023-07-02 10:34:15,304 [prior] Evaluating prior at array([0.36030101, 0.43843064])
 2023-07-02 10:34:15,304 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,304 [model] Got input parameters: {'Omega_m': 0.36030100945801946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4384306359455362, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,304 [classy] Got parameters {'Omega_m': 0.36030100945801946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,304 [classy] Computing new state
 2023-07-02 10:34:15,304 [classy] Setting parameters: {'Omega_m': 0.36030100945801946, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,348 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.86818117488713}
 2023-07-02 10:34:15,348 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,350 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125327
 2023-07-02 10:34:15,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4384306359455362, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,350 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,369 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.63056
 2023-07-02 10:34:15,370 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,370 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.5227867378041536}
 2023-07-02 10:34:15,370 [prior] Evaluating prior at array([0.30648005, 0.52278674])
 2023-07-02 10:34:15,370 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,370 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5227867378041536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,370 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,370 [classy] Re-using computed results
 2023-07-02 10:34:15,370 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
 2023-07-02 10:34:15,370 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,370 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5227867378041536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,370 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,390 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35344
 2023-07-02 10:34:15,391 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,391 [mcmc] New sample, #540:
   Omega_m:0.30648, b1:0.5220598
 2023-07-02 10:34:15,391 [model] Posterior to be computed for parameters {'Omega_m': 0.2885560610632319, 'b1': 0.5506377345536866}
 2023-07-02 10:34:15,391 [prior] Evaluating prior at array([0.28855606, 0.55063773])
 2023-07-02 10:34:15,391 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,391 [model] Got input parameters: {'Omega_m': 0.2885560610632319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5506377345536866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,391 [classy] Got parameters {'Omega_m': 0.2885560610632319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,391 [classy] Computing new state
 2023-07-02 10:34:15,391 [classy] Setting parameters: {'Omega_m': 0.2885560610632319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.24122881330186}
 2023-07-02 10:34:15,435 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0375173
 2023-07-02 10:34:15,437 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5506377345536866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,437 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,456 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.54793
 2023-07-02 10:34:15,456 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,456 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.5640151924742844}
 2023-07-02 10:34:15,456 [prior] Evaluating prior at array([0.30648005, 0.56401519])
 2023-07-02 10:34:15,456 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,456 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5640151924742844, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,456 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,456 [classy] Re-using computed results
 2023-07-02 10:34:15,456 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
 2023-07-02 10:34:15,456 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,457 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5640151924742844, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,457 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,476 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.0294
 2023-07-02 10:34:15,476 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,476 [model] Posterior to be computed for parameters {'Omega_m': 0.30276841155490936, 'b1': 0.5285540232083292}
 2023-07-02 10:34:15,476 [prior] Evaluating prior at array([0.30276841, 0.52855402])
 2023-07-02 10:34:15,476 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,476 [model] Got input parameters: {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5285540232083292, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,476 [classy] Got parameters {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,476 [classy] Computing new state
 2023-07-02 10:34:15,476 [classy] Setting parameters: {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4455568792512}
 2023-07-02 10:34:15,520 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0061335
 2023-07-02 10:34:15,522 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5285540232083292, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,522 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,541 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91616
 2023-07-02 10:34:15,542 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,542 [mcmc] New sample, #541:
   Omega_m:0.30648, b1:0.5227867
 2023-07-02 10:34:15,542 [model] Posterior to be computed for parameters {'Omega_m': 0.30276841155490936, 'b1': 0.5294590749939853}
 2023-07-02 10:34:15,542 [prior] Evaluating prior at array([0.30276841, 0.52945907])
 2023-07-02 10:34:15,542 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,542 [model] Got input parameters: {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5294590749939853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,542 [classy] Got parameters {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,542 [classy] Re-using computed results
 2023-07-02 10:34:15,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4455568792512}
 2023-07-02 10:34:15,542 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,542 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5294590749939853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,542 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,561 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.88479
 2023-07-02 10:34:15,561 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,561 [mcmc] New sample, #542:
   Omega_m:0.3027684, b1:0.528554
 2023-07-02 10:34:15,561 [model] Posterior to be computed for parameters {'Omega_m': 0.3287326538909308, 'b1': 0.48911481009667834}
 2023-07-02 10:34:15,562 [prior] Evaluating prior at array([0.32873265, 0.48911481])
 2023-07-02 10:34:15,562 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,562 [model] Got input parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48911481009667834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,562 [classy] Got parameters {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,562 [classy] Computing new state
 2023-07-02 10:34:15,562 [classy] Setting parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3488921595526}
 2023-07-02 10:34:15,606 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,608 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0157605
 2023-07-02 10:34:15,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48911481009667834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,608 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,627 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.43605
 2023-07-02 10:34:15,627 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,627 [mcmc] New sample, #543:
   Omega_m:0.3027684, b1:0.5294591
 2023-07-02 10:34:15,627 [model] Posterior to be computed for parameters {'Omega_m': 0.3287326538909308, 'b1': 0.5023084131207975}
 2023-07-02 10:34:15,627 [prior] Evaluating prior at array([0.32873265, 0.50230841])
 2023-07-02 10:34:15,628 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,628 [model] Got input parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5023084131207975, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,628 [classy] Got parameters {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,628 [classy] Re-using computed results
 2023-07-02 10:34:15,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3488921595526}
 2023-07-02 10:34:15,628 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5023084131207975, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,628 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,648 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0706315
 2023-07-02 10:34:15,648 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,648 [model] Posterior to be computed for parameters {'Omega_m': 0.3444973132799683, 'b1': 0.46461905989622776}
 2023-07-02 10:34:15,648 [prior] Evaluating prior at array([0.34449731, 0.46461906])
 2023-07-02 10:34:15,648 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,648 [model] Got input parameters: {'Omega_m': 0.3444973132799683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46461905989622776, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,648 [classy] Got parameters {'Omega_m': 0.3444973132799683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,648 [classy] Computing new state
 2023-07-02 10:34:15,648 [classy] Setting parameters: {'Omega_m': 0.3444973132799683, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.57425491359498}
 2023-07-02 10:34:15,692 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,694 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0583732
 2023-07-02 10:34:15,694 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46461905989622776, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,694 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,713 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.21276
 2023-07-02 10:34:15,713 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,714 [model] Posterior to be computed for parameters {'Omega_m': 0.3287326538909308, 'b1': 0.5180436646946928}
 2023-07-02 10:34:15,714 [prior] Evaluating prior at array([0.32873265, 0.51804366])
 2023-07-02 10:34:15,714 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,714 [model] Got input parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5180436646946928, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,714 [classy] Got parameters {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,714 [classy] Re-using computed results
 2023-07-02 10:34:15,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3488921595526}
 2023-07-02 10:34:15,714 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5180436646946928, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,714 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,733 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21671
 2023-07-02 10:34:15,733 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,733 [model] Posterior to be computed for parameters {'Omega_m': 0.2944983735743141, 'b1': 0.5423093865371431}
 2023-07-02 10:34:15,733 [prior] Evaluating prior at array([0.29449837, 0.54230939])
 2023-07-02 10:34:15,733 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,733 [model] Got input parameters: {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5423093865371431, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,734 [classy] Got parameters {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,734 [classy] Computing new state
 2023-07-02 10:34:15,734 [classy] Setting parameters: {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4812802738758}
 2023-07-02 10:34:15,777 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,779 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0209632
 2023-07-02 10:34:15,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5423093865371431, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,779 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,799 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.240779
 2023-07-02 10:34:15,799 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,799 [mcmc] New sample, #544:
   Omega_m:0.3287327, b1:0.4891148
 2023-07-02 10:34:15,799 [model] Posterior to be computed for parameters {'Omega_m': 0.2944983735743141, 'b1': 0.5389394175172902}
 2023-07-02 10:34:15,799 [prior] Evaluating prior at array([0.29449837, 0.53893942])
 2023-07-02 10:34:15,799 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,799 [model] Got input parameters: {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5389394175172902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,799 [classy] Got parameters {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,799 [classy] Re-using computed results
 2023-07-02 10:34:15,799 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4812802738758}
 2023-07-02 10:34:15,799 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,799 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5389394175172902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,799 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,819 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.295449
 2023-07-02 10:34:15,819 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,819 [mcmc] New sample, #545:
   Omega_m:0.2944984, b1:0.5423094
 2023-07-02 10:34:15,819 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.4788438682794477}
 2023-07-02 10:34:15,819 [prior] Evaluating prior at array([0.33317389, 0.47884387])
 2023-07-02 10:34:15,819 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,819 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4788438682794477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,819 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,819 [classy] Computing new state
 2023-07-02 10:34:15,819 [classy] Setting parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,863 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
 2023-07-02 10:34:15,863 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0251593
 2023-07-02 10:34:15,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4788438682794477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,865 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,884 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.87954
 2023-07-02 10:34:15,884 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,884 [mcmc] New sample, #546:
   Omega_m:0.2944984, b1:0.5389394
 2023-07-02 10:34:15,884 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.43304443969117223}
 2023-07-02 10:34:15,884 [prior] Evaluating prior at array([0.33317389, 0.43304444])
 2023-07-02 10:34:15,884 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,884 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43304443969117223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,884 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,884 [classy] Re-using computed results
 2023-07-02 10:34:15,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
 2023-07-02 10:34:15,884 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43304443969117223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,884 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,904 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.88247
 2023-07-02 10:34:15,904 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,904 [model] Posterior to be computed for parameters {'Omega_m': 0.3396662398576064, 'b1': 0.4687558035070648}
 2023-07-02 10:34:15,904 [prior] Evaluating prior at array([0.33966624, 0.4687558 ])
 2023-07-02 10:34:15,904 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,904 [model] Got input parameters: {'Omega_m': 0.3396662398576064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4687558035070648, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,904 [classy] Got parameters {'Omega_m': 0.3396662398576064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,904 [classy] Computing new state
 2023-07-02 10:34:15,905 [classy] Setting parameters: {'Omega_m': 0.3396662398576064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:15,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.11013980766754}
 2023-07-02 10:34:15,948 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:15,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0426192
 2023-07-02 10:34:15,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4687558035070648, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,950 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:15,970 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.586026
 2023-07-02 10:34:15,970 [model] Computed derived parameters: {}
 2023-07-02 10:34:15,980 [mcmc] Progress @ 2023-07-02 10:34:15 : 1411 steps taken, and 546 accepted.
 2023-07-02 10:34:15,980 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.46139290275356704}
 2023-07-02 10:34:15,980 [prior] Evaluating prior at array([0.33317389, 0.4613929 ])
 2023-07-02 10:34:15,981 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:15,981 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46139290275356704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,981 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:15,981 [classy] Re-using computed results
 2023-07-02 10:34:15,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
 2023-07-02 10:34:15,981 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:15,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46139290275356704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:15,981 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,001 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14332
 2023-07-02 10:34:16,001 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,001 [mcmc] New sample, #547:
   Omega_m:0.3331739, b1:0.4788439
 2023-07-02 10:34:16,001 [model] Posterior to be computed for parameters {'Omega_m': 0.335504454211472, 'b1': 0.45777158483943986}
 2023-07-02 10:34:16,001 [prior] Evaluating prior at array([0.33550445, 0.45777158])
 2023-07-02 10:34:16,002 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,002 [model] Got input parameters: {'Omega_m': 0.335504454211472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45777158483943986, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,002 [classy] Got parameters {'Omega_m': 0.335504454211472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,002 [classy] Computing new state
 2023-07-02 10:34:16,002 [classy] Setting parameters: {'Omega_m': 0.335504454211472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,046 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.57735576085673}
 2023-07-02 10:34:16,046 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0309266
 2023-07-02 10:34:16,048 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45777158483943986, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,048 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,067 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.717662
 2023-07-02 10:34:16,067 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,067 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.44570874619334866}
 2023-07-02 10:34:16,067 [prior] Evaluating prior at array([0.33317389, 0.44570875])
 2023-07-02 10:34:16,067 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,067 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44570874619334866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,067 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,068 [classy] Re-using computed results
 2023-07-02 10:34:16,068 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
 2023-07-02 10:34:16,068 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44570874619334866, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,068 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,087 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.020215
 2023-07-02 10:34:16,087 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,087 [model] Posterior to be computed for parameters {'Omega_m': 0.32257144637319035, 'b1': 0.4778674030572008}
 2023-07-02 10:34:16,087 [prior] Evaluating prior at array([0.32257145, 0.4778674 ])
 2023-07-02 10:34:16,087 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,088 [model] Got input parameters: {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4778674030572008, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,088 [classy] Got parameters {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,088 [classy] Computing new state
 2023-07-02 10:34:16,088 [classy] Setting parameters: {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06345424376704}
 2023-07-02 10:34:16,133 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,135 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00628852
 2023-07-02 10:34:16,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4778674030572008, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,135 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,156 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42429
 2023-07-02 10:34:16,156 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,156 [mcmc] New sample, #548:
   Omega_m:0.3331739, b1:0.4613929
 2023-07-02 10:34:16,156 [model] Posterior to be computed for parameters {'Omega_m': 0.32257144637319035, 'b1': 0.49862824477713624}
 2023-07-02 10:34:16,156 [prior] Evaluating prior at array([0.32257145, 0.49862824])
 2023-07-02 10:34:16,156 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,156 [model] Got input parameters: {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49862824477713624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,156 [classy] Got parameters {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,156 [classy] Re-using computed results
 2023-07-02 10:34:16,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06345424376704}
 2023-07-02 10:34:16,156 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49862824477713624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,156 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,176 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23296
 2023-07-02 10:34:16,176 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,176 [mcmc] New sample, #549:
   Omega_m:0.3225714, b1:0.4778674
 2023-07-02 10:34:16,176 [model] Posterior to be computed for parameters {'Omega_m': 0.32836670863896106, 'b1': 0.4896233374521399}
 2023-07-02 10:34:16,176 [prior] Evaluating prior at array([0.32836671, 0.48962334])
 2023-07-02 10:34:16,176 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,176 [model] Got input parameters: {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4896233374521399, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,176 [classy] Got parameters {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,177 [classy] Computing new state
 2023-07-02 10:34:16,177 [classy] Setting parameters: {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39099589080354}
 2023-07-02 10:34:16,220 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150807
 2023-07-02 10:34:16,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4896233374521399, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,222 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.49835
 2023-07-02 10:34:16,242 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,242 [mcmc] New sample, #550:
   Omega_m:0.3225714, b1:0.4986282
 2023-07-02 10:34:16,242 [model] Posterior to be computed for parameters {'Omega_m': 0.32836670863896106, 'b1': 0.4691245253120672}
 2023-07-02 10:34:16,242 [prior] Evaluating prior at array([0.32836671, 0.46912453])
 2023-07-02 10:34:16,242 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,243 [model] Got input parameters: {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4691245253120672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,243 [classy] Got parameters {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,243 [classy] Re-using computed results
 2023-07-02 10:34:16,243 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39099589080354}
 2023-07-02 10:34:16,243 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,243 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4691245253120672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,243 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,262 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87155
 2023-07-02 10:34:16,262 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,262 [mcmc] New sample, #551:
   Omega_m:0.3283667, b1:0.4896233
 2023-07-02 10:34:16,262 [model] Posterior to be computed for parameters {'Omega_m': 0.32678173130872135, 'b1': 0.4715873256680284}
 2023-07-02 10:34:16,262 [prior] Evaluating prior at array([0.32678173, 0.47158733])
 2023-07-02 10:34:16,263 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,263 [model] Got input parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4715873256680284, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,263 [classy] Got parameters {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,263 [classy] Computing new state
 2023-07-02 10:34:16,263 [classy] Setting parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57384767432077}
 2023-07-02 10:34:16,306 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,308 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123054
 2023-07-02 10:34:16,308 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4715873256680284, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,308 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,327 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05985
 2023-07-02 10:34:16,328 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,328 [mcmc] New sample, #552:
   Omega_m:0.3283667, b1:0.4691245
 2023-07-02 10:34:16,328 [model] Posterior to be computed for parameters {'Omega_m': 0.32678173130872135, 'b1': 0.44329725119594615}
 2023-07-02 10:34:16,328 [prior] Evaluating prior at array([0.32678173, 0.44329725])
 2023-07-02 10:34:16,328 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,328 [model] Got input parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44329725119594615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,328 [classy] Got parameters {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,328 [classy] Re-using computed results
 2023-07-02 10:34:16,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57384767432077}
 2023-07-02 10:34:16,328 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,328 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44329725119594615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,328 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,348 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.13831
 2023-07-02 10:34:16,348 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,348 [model] Posterior to be computed for parameters {'Omega_m': 0.34104823326330724, 'b1': 0.449419471641522}
 2023-07-02 10:34:16,348 [prior] Evaluating prior at array([0.34104823, 0.44941947])
 2023-07-02 10:34:16,348 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,348 [model] Got input parameters: {'Omega_m': 0.34104823326330724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.449419471641522, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,348 [classy] Got parameters {'Omega_m': 0.34104823326330724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,348 [classy] Computing new state
 2023-07-02 10:34:16,348 [classy] Setting parameters: {'Omega_m': 0.34104823326330724, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,392 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9561400373312}
 2023-07-02 10:34:16,392 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,394 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0468897
 2023-07-02 10:34:16,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.449419471641522, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,394 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,414 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.48121
 2023-07-02 10:34:16,414 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,414 [model] Posterior to be computed for parameters {'Omega_m': 0.32678173130872135, 'b1': 0.422309050519154}
 2023-07-02 10:34:16,414 [prior] Evaluating prior at array([0.32678173, 0.42230905])
 2023-07-02 10:34:16,414 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,414 [model] Got input parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.422309050519154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,414 [classy] Got parameters {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,414 [classy] Re-using computed results
 2023-07-02 10:34:16,414 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57384767432077}
 2023-07-02 10:34:16,414 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,414 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.422309050519154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,414 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,434 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.05292
 2023-07-02 10:34:16,434 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,434 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.47071570276152114}
 2023-07-02 10:34:16,434 [prior] Evaluating prior at array([0.32734268, 0.4707157 ])
 2023-07-02 10:34:16,434 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,434 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47071570276152114, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,434 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,434 [classy] Computing new state
 2023-07-02 10:34:16,434 [classy] Setting parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
 2023-07-02 10:34:16,478 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,480 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132561
 2023-07-02 10:34:16,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47071570276152114, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,500 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99606
 2023-07-02 10:34:16,500 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,500 [mcmc] New sample, #553:
   Omega_m:0.3267817, b1:0.4715873
 2023-07-02 10:34:16,500 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.4400329831026975}
 2023-07-02 10:34:16,500 [prior] Evaluating prior at array([0.32734268, 0.44003298])
 2023-07-02 10:34:16,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,500 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4400329831026975, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,500 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,500 [classy] Re-using computed results
 2023-07-02 10:34:16,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
 2023-07-02 10:34:16,500 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4400329831026975, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,500 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,520 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.63577
 2023-07-02 10:34:16,520 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,520 [model] Posterior to be computed for parameters {'Omega_m': 0.3412016119405975, 'b1': 0.4491811457968425}
 2023-07-02 10:34:16,520 [prior] Evaluating prior at array([0.34120161, 0.44918115])
 2023-07-02 10:34:16,520 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,520 [model] Got input parameters: {'Omega_m': 0.3412016119405975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4491811457968425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,520 [classy] Got parameters {'Omega_m': 0.3412016119405975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,520 [classy] Computing new state
 2023-07-02 10:34:16,520 [classy] Setting parameters: {'Omega_m': 0.3412016119405975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.93908241059165}
 2023-07-02 10:34:16,564 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,566 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0473754
 2023-07-02 10:34:16,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4491811457968425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,566 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,586 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.51829
 2023-07-02 10:34:16,586 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,586 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.4840401309562115}
 2023-07-02 10:34:16,586 [prior] Evaluating prior at array([0.32734268, 0.48404013])
 2023-07-02 10:34:16,586 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,586 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4840401309562115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,586 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,586 [classy] Re-using computed results
 2023-07-02 10:34:16,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
 2023-07-02 10:34:16,586 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,586 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4840401309562115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,586 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,606 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03684
 2023-07-02 10:34:16,606 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,606 [mcmc] New sample, #554:
   Omega_m:0.3273427, b1:0.4707157
 2023-07-02 10:34:16,606 [model] Posterior to be computed for parameters {'Omega_m': 0.3523354420496836, 'b1': 0.4452053891669828}
 2023-07-02 10:34:16,606 [prior] Evaluating prior at array([0.35233544, 0.44520539])
 2023-07-02 10:34:16,606 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,606 [model] Got input parameters: {'Omega_m': 0.3523354420496836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4452053891669828, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,607 [classy] Got parameters {'Omega_m': 0.3523354420496836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,607 [classy] Computing new state
 2023-07-02 10:34:16,607 [classy] Setting parameters: {'Omega_m': 0.3523354420496836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.71933054335227}
 2023-07-02 10:34:16,650 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0887129
 2023-07-02 10:34:16,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4452053891669828, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,652 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,671 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.12387
 2023-07-02 10:34:16,672 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,672 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.4498700782205796}
 2023-07-02 10:34:16,672 [prior] Evaluating prior at array([0.32734268, 0.44987008])
 2023-07-02 10:34:16,672 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,672 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4498700782205796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,672 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,672 [classy] Re-using computed results
 2023-07-02 10:34:16,672 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
 2023-07-02 10:34:16,672 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,672 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4498700782205796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,672 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0470865
 2023-07-02 10:34:16,692 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.5100160376984385}
 2023-07-02 10:34:16,692 [prior] Evaluating prior at array([0.31062544, 0.51001604])
 2023-07-02 10:34:16,692 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,692 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5100160376984385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,692 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,692 [classy] Computing new state
 2023-07-02 10:34:16,692 [classy] Setting parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
 2023-07-02 10:34:16,736 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,738 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000415187
 2023-07-02 10:34:16,738 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5100160376984385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,738 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,758 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79923
 2023-07-02 10:34:16,758 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,758 [mcmc] New sample, #555:
   Omega_m:0.3273427, b1:0.4840401
 2023-07-02 10:34:16,758 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.5497728022164425}
 2023-07-02 10:34:16,758 [prior] Evaluating prior at array([0.31062544, 0.5497728 ])
 2023-07-02 10:34:16,758 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,758 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5497728022164425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,758 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,758 [classy] Re-using computed results
 2023-07-02 10:34:16,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
 2023-07-02 10:34:16,758 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,758 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5497728022164425, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,758 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,777 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.0067
 2023-07-02 10:34:16,778 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,778 [model] Posterior to be computed for parameters {'Omega_m': 0.28956282242490256, 'b1': 0.5427439640140743}
 2023-07-02 10:34:16,778 [prior] Evaluating prior at array([0.28956282, 0.54274396])
 2023-07-02 10:34:16,778 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,778 [model] Got input parameters: {'Omega_m': 0.28956282242490256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5427439640140743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,778 [classy] Got parameters {'Omega_m': 0.28956282242490256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,778 [classy] Computing new state
 2023-07-02 10:34:16,778 [classy] Setting parameters: {'Omega_m': 0.28956282242490256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,822 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.11152995899099}
 2023-07-02 10:34:16,822 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,824 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0343539
 2023-07-02 10:34:16,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5427439640140743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,824 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,843 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.2228
 2023-07-02 10:34:16,843 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,843 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.4848255436293355}
 2023-07-02 10:34:16,843 [prior] Evaluating prior at array([0.31062544, 0.48482554])
 2023-07-02 10:34:16,843 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,844 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4848255436293355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,844 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,844 [classy] Re-using computed results
 2023-07-02 10:34:16,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
 2023-07-02 10:34:16,844 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,844 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4848255436293355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,844 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,864 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36336
 2023-07-02 10:34:16,864 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,864 [mcmc] New sample, #556:
   Omega_m:0.3106254, b1:0.510016
 2023-07-02 10:34:16,864 [model] Posterior to be computed for parameters {'Omega_m': 0.2888608337685909, 'b1': 0.5186442476360211}
 2023-07-02 10:34:16,864 [prior] Evaluating prior at array([0.28886083, 0.51864425])
 2023-07-02 10:34:16,864 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,864 [model] Got input parameters: {'Omega_m': 0.2888608337685909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5186442476360211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,864 [classy] Got parameters {'Omega_m': 0.2888608337685909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,864 [classy] Computing new state
 2023-07-02 10:34:16,864 [classy] Setting parameters: {'Omega_m': 0.2888608337685909, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.201922881403}
 2023-07-02 10:34:16,908 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,910 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0365439
 2023-07-02 10:34:16,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5186442476360211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,910 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,929 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.58873
 2023-07-02 10:34:16,929 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.42169762913828684}
 2023-07-02 10:34:16,929 [prior] Evaluating prior at array([0.31062544, 0.42169763])
 2023-07-02 10:34:16,930 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,930 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42169762913828684, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,930 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,930 [classy] Re-using computed results
 2023-07-02 10:34:16,930 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
 2023-07-02 10:34:16,930 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:16,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42169762913828684, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,930 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:16,949 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.6306
 2023-07-02 10:34:16,949 [model] Computed derived parameters: {}
 2023-07-02 10:34:16,949 [model] Posterior to be computed for parameters {'Omega_m': 0.3165448489039054, 'b1': 0.4756277318607595}
 2023-07-02 10:34:16,949 [prior] Evaluating prior at array([0.31654485, 0.47562773])
 2023-07-02 10:34:16,949 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:16,949 [model] Got input parameters: {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4756277318607595, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,949 [classy] Got parameters {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:16,949 [classy] Computing new state
 2023-07-02 10:34:16,949 [classy] Setting parameters: {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:16,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77429325573698}
 2023-07-02 10:34:16,994 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:16,996 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00120348
 2023-07-02 10:34:16,996 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4756277318607595, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:16,996 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,016 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64801
 2023-07-02 10:34:17,016 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,016 [mcmc] New sample, #557:
   Omega_m:0.3106254, b1:0.4848255
 2023-07-02 10:34:17,016 [model] Posterior to be computed for parameters {'Omega_m': 0.3165448489039054, 'b1': 0.4651667974868253}
 2023-07-02 10:34:17,016 [prior] Evaluating prior at array([0.31654485, 0.4651668 ])
 2023-07-02 10:34:17,017 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,017 [model] Got input parameters: {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4651667974868253, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,017 [classy] Got parameters {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,017 [classy] Re-using computed results
 2023-07-02 10:34:17,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77429325573698}
 2023-07-02 10:34:17,017 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,017 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4651667974868253, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,017 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,038 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.177217
 2023-07-02 10:34:17,038 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,038 [model] Posterior to be computed for parameters {'Omega_m': 0.30511801097629115, 'b1': 0.4933832038026727}
 2023-07-02 10:34:17,038 [prior] Evaluating prior at array([0.30511801, 0.4933832 ])
 2023-07-02 10:34:17,038 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,038 [model] Got input parameters: {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4933832038026727, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,038 [classy] Got parameters {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,038 [classy] Computing new state
 2023-07-02 10:34:17,039 [classy] Setting parameters: {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1558405140349}
 2023-07-02 10:34:17,083 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,084 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00359159
 2023-07-02 10:34:17,084 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4933832038026727, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,084 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,104 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.715657
 2023-07-02 10:34:17,104 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,104 [mcmc] New sample, #558:
   Omega_m:0.3165448, b1:0.4756277
 2023-07-02 10:34:17,104 [model] Posterior to be computed for parameters {'Omega_m': 0.30511801097629115, 'b1': 0.4631054968930223}
 2023-07-02 10:34:17,104 [prior] Evaluating prior at array([0.30511801, 0.4631055 ])
 2023-07-02 10:34:17,104 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,104 [model] Got input parameters: {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4631054968930223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,104 [classy] Got parameters {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,104 [classy] Re-using computed results
 2023-07-02 10:34:17,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1558405140349}
 2023-07-02 10:34:17,104 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,104 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4631054968930223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,104 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,125 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.36033
 2023-07-02 10:34:17,125 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.48740947062432205}
 2023-07-02 10:34:17,125 [prior] Evaluating prior at array([0.30896251, 0.48740947])
 2023-07-02 10:34:17,126 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,126 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48740947062432205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,126 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,126 [classy] Computing new state
 2023-07-02 10:34:17,126 [classy] Setting parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,171 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000969591
 2023-07-02 10:34:17,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48740947062432205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,173 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,194 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20784
 2023-07-02 10:34:17,194 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,194 [mcmc] New sample, #559:
   Omega_m:0.305118, b1:0.4933832
 2023-07-02 10:34:17,194 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.44693862254810013}
 2023-07-02 10:34:17,194 [prior] Evaluating prior at array([0.30896251, 0.44693862])
 2023-07-02 10:34:17,194 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,194 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44693862254810013, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,194 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,194 [classy] Re-using computed results
 2023-07-02 10:34:17,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,194 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,194 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44693862254810013, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,194 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,215 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.7044
 2023-07-02 10:34:17,216 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,216 [model] Posterior to be computed for parameters {'Omega_m': 0.3290862865472117, 'b1': 0.4561403508724592}
 2023-07-02 10:34:17,216 [prior] Evaluating prior at array([0.32908629, 0.45614035])
 2023-07-02 10:34:17,216 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,216 [model] Got input parameters: {'Omega_m': 0.3290862865472117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4561403508724592, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,216 [classy] Got parameters {'Omega_m': 0.3290862865472117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,216 [classy] Computing new state
 2023-07-02 10:34:17,216 [classy] Setting parameters: {'Omega_m': 0.3290862865472117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,261 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3082419495965}
 2023-07-02 10:34:17,261 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,263 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0164314
 2023-07-02 10:34:17,263 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4561403508724592, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,263 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.969876
 2023-07-02 10:34:17,284 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,284 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.46421764612128774}
 2023-07-02 10:34:17,284 [prior] Evaluating prior at array([0.30896251, 0.46421765])
 2023-07-02 10:34:17,284 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,284 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46421764612128774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,284 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,284 [classy] Re-using computed results
 2023-07-02 10:34:17,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,285 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46421764612128774, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,285 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.96603
 2023-07-02 10:34:17,304 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,304 [model] Posterior to be computed for parameters {'Omega_m': 0.2862665091378119, 'b1': 0.5226754116799859}
 2023-07-02 10:34:17,304 [prior] Evaluating prior at array([0.28626651, 0.52267541])
 2023-07-02 10:34:17,304 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,304 [model] Got input parameters: {'Omega_m': 0.2862665091378119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5226754116799859, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,304 [classy] Got parameters {'Omega_m': 0.2862665091378119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,304 [classy] Computing new state
 2023-07-02 10:34:17,305 [classy] Setting parameters: {'Omega_m': 0.2862665091378119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,349 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.53764835325944}
 2023-07-02 10:34:17,349 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,351 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.045268
 2023-07-02 10:34:17,351 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5226754116799859, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,351 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,371 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.6369
 2023-07-02 10:34:17,371 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,371 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.41340429321664374}
 2023-07-02 10:34:17,371 [prior] Evaluating prior at array([0.30896251, 0.41340429])
 2023-07-02 10:34:17,371 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,371 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41340429321664374, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,371 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,371 [classy] Re-using computed results
 2023-07-02 10:34:17,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,371 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,371 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41340429321664374, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,371 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,391 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.5581
 2023-07-02 10:34:17,391 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,391 [model] Posterior to be computed for parameters {'Omega_m': 0.3604808183438888, 'b1': 0.4073582878050974}
 2023-07-02 10:34:17,391 [prior] Evaluating prior at array([0.36048082, 0.40735829])
 2023-07-02 10:34:17,391 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,391 [model] Got input parameters: {'Omega_m': 0.3604808183438888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4073582878050974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,391 [classy] Got parameters {'Omega_m': 0.3604808183438888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,391 [classy] Computing new state
 2023-07-02 10:34:17,391 [classy] Setting parameters: {'Omega_m': 0.3604808183438888, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.84917048579166}
 2023-07-02 10:34:17,435 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,437 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.126218
 2023-07-02 10:34:17,437 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4073582878050974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,437 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,456 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.91909
 2023-07-02 10:34:17,456 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,456 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.49743446946431746}
 2023-07-02 10:34:17,456 [prior] Evaluating prior at array([0.30896251, 0.49743447])
 2023-07-02 10:34:17,456 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,457 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49743446946431746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,457 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,457 [classy] Re-using computed results
 2023-07-02 10:34:17,457 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,457 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,457 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49743446946431746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,457 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,476 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.19375
 2023-07-02 10:34:17,476 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,476 [mcmc] New sample, #560:
   Omega_m:0.3089625, b1:0.4874095
 2023-07-02 10:34:17,476 [mcmc] Learn + convergence test @ 560 samples accepted.
 2023-07-02 10:34:17,476 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:17,481 [mcmc]  - Acceptance rate: 0.458
 2023-07-02 10:34:17,482 [mcmc]  - Condition number = 6.51786
 2023-07-02 10:34:17,482 [mcmc]  - Eigenvalues = array([0.0126918 , 0.08272334])
 2023-07-02 10:34:17,482 [mcmc]  - Convergence of means: R-1 = 0.082723 after 448 accepted steps
 2023-07-02 10:34:17,482 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:17,482 [mcmc] array([[ 9.69406425e-05, -1.55540497e-04],
       [-1.55540497e-04,  4.21144443e-04]])
 2023-07-02 10:34:17,492 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:17,492 [model] Posterior to be computed for parameters {'Omega_m': 0.3328675817018873, 'b1': 0.4590789691789578}
 2023-07-02 10:34:17,492 [prior] Evaluating prior at array([0.33286758, 0.45907897])
 2023-07-02 10:34:17,493 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,493 [model] Got input parameters: {'Omega_m': 0.3328675817018873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4590789691789578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,493 [classy] Got parameters {'Omega_m': 0.3328675817018873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,493 [classy] Computing new state
 2023-07-02 10:34:17,493 [classy] Setting parameters: {'Omega_m': 0.3328675817018873, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.87609464967395}
 2023-07-02 10:34:17,538 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,540 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244437
 2023-07-02 10:34:17,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4590789691789578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,540 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,560 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08242
 2023-07-02 10:34:17,560 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.4880039345539698}
 2023-07-02 10:34:17,560 [prior] Evaluating prior at array([0.30896251, 0.48800393])
 2023-07-02 10:34:17,560 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,560 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4880039345539698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,560 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,560 [classy] Re-using computed results
 2023-07-02 10:34:17,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,561 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4880039345539698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,561 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,580 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.28042
 2023-07-02 10:34:17,580 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,581 [model] Posterior to be computed for parameters {'Omega_m': 0.2759428857891994, 'b1': 0.5504141949045585}
 2023-07-02 10:34:17,581 [prior] Evaluating prior at array([0.27594289, 0.55041419])
 2023-07-02 10:34:17,581 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,581 [model] Got input parameters: {'Omega_m': 0.2759428857891994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5504141949045585, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,581 [classy] Got parameters {'Omega_m': 0.2759428857891994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,581 [classy] Computing new state
 2023-07-02 10:34:17,581 [classy] Setting parameters: {'Omega_m': 0.2759428857891994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.90019267056047}
 2023-07-02 10:34:17,625 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.090176
 2023-07-02 10:34:17,627 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5504141949045585, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,627 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,646 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.36109
 2023-07-02 10:34:17,647 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.5476331317798704}
 2023-07-02 10:34:17,647 [prior] Evaluating prior at array([0.30896251, 0.54763313])
 2023-07-02 10:34:17,647 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,647 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5476331317798704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,647 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,647 [classy] Re-using computed results
 2023-07-02 10:34:17,647 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
 2023-07-02 10:34:17,647 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,647 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5476331317798704, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,647 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,667 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.963049
 2023-07-02 10:34:17,667 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,668 [model] Posterior to be computed for parameters {'Omega_m': 0.310897316481309, 'b1': 0.4943300864840143}
 2023-07-02 10:34:17,668 [prior] Evaluating prior at array([0.31089732, 0.49433009])
 2023-07-02 10:34:17,668 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,668 [model] Got input parameters: {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943300864840143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,668 [classy] Got parameters {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,668 [classy] Computing new state
 2023-07-02 10:34:17,668 [classy] Setting parameters: {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,711 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45148278673094}
 2023-07-02 10:34:17,712 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,714 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00035737
 2023-07-02 10:34:17,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943300864840143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,714 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,734 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34062
 2023-07-02 10:34:17,734 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,734 [mcmc] New sample, #561:
   Omega_m:0.3089625, b1:0.4974345
 2023-07-02 10:34:17,734 [model] Posterior to be computed for parameters {'Omega_m': 0.310897316481309, 'b1': 0.5166955998628603}
 2023-07-02 10:34:17,734 [prior] Evaluating prior at array([0.31089732, 0.5166956 ])
 2023-07-02 10:34:17,734 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,734 [model] Got input parameters: {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166955998628603, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,734 [classy] Got parameters {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,734 [classy] Re-using computed results
 2023-07-02 10:34:17,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45148278673094}
 2023-07-02 10:34:17,734 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,734 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166955998628603, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,734 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,754 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60666
 2023-07-02 10:34:17,754 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,754 [mcmc] New sample, #562:
   Omega_m:0.3108973, b1:0.4943301
 2023-07-02 10:34:17,754 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.5039690287981492}
 2023-07-02 10:34:17,754 [prior] Evaluating prior at array([0.31882915, 0.50396903])
 2023-07-02 10:34:17,754 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,754 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5039690287981492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,754 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,754 [classy] Computing new state
 2023-07-02 10:34:17,754 [classy] Setting parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,798 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
 2023-07-02 10:34:17,798 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,800 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0026326
 2023-07-02 10:34:17,800 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5039690287981492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,800 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,820 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54788
 2023-07-02 10:34:17,820 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,820 [mcmc] New sample, #563:
   Omega_m:0.3108973, b1:0.5166956
 2023-07-02 10:34:17,820 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.47006799039162317}
 2023-07-02 10:34:17,820 [prior] Evaluating prior at array([0.31882915, 0.47006799])
 2023-07-02 10:34:17,821 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,821 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47006799039162317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,821 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,821 [classy] Re-using computed results
 2023-07-02 10:34:17,821 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
 2023-07-02 10:34:17,821 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,821 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47006799039162317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,821 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,840 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41508
 2023-07-02 10:34:17,840 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,840 [mcmc] New sample, #564:
   Omega_m:0.3188292, b1:0.503969
 2023-07-02 10:34:17,840 [model] Posterior to be computed for parameters {'Omega_m': 0.3577674026022992, 'b1': 0.4075918778582508}
 2023-07-02 10:34:17,840 [prior] Evaluating prior at array([0.3577674 , 0.40759188])
 2023-07-02 10:34:17,840 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,840 [model] Got input parameters: {'Omega_m': 0.3577674026022992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4075918778582508, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,840 [classy] Got parameters {'Omega_m': 0.3577674026022992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,840 [classy] Computing new state
 2023-07-02 10:34:17,840 [classy] Setting parameters: {'Omega_m': 0.3577674026022992, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.1370105134144}
 2023-07-02 10:34:17,884 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,886 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113069
 2023-07-02 10:34:17,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4075918778582508, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,886 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,905 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.24626
 2023-07-02 10:34:17,905 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,906 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.5122573992281159}
 2023-07-02 10:34:17,906 [prior] Evaluating prior at array([0.31882915, 0.5122574 ])
 2023-07-02 10:34:17,906 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,906 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122573992281159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,906 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,906 [classy] Re-using computed results
 2023-07-02 10:34:17,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
 2023-07-02 10:34:17,906 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122573992281159, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,906 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8727
 2023-07-02 10:34:17,926 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,926 [mcmc] New sample, #565:
   Omega_m:0.3188292, b1:0.470068
 2023-07-02 10:34:17,926 [model] Posterior to be computed for parameters {'Omega_m': 0.34118478434882804, 'b1': 0.4763879669241002}
 2023-07-02 10:34:17,926 [prior] Evaluating prior at array([0.34118478, 0.47638797])
 2023-07-02 10:34:17,926 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,926 [model] Got input parameters: {'Omega_m': 0.34118478434882804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4763879669241002, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,926 [classy] Got parameters {'Omega_m': 0.34118478434882804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,926 [classy] Computing new state
 2023-07-02 10:34:17,926 [classy] Setting parameters: {'Omega_m': 0.34118478434882804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:17,970 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.94095534834648}
 2023-07-02 10:34:17,970 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:17,972 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0473219
 2023-07-02 10:34:17,972 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4763879669241002, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,972 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:17,991 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.02694
 2023-07-02 10:34:17,991 [model] Computed derived parameters: {}
 2023-07-02 10:34:17,992 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.47039459427515506}
 2023-07-02 10:34:17,992 [prior] Evaluating prior at array([0.31882915, 0.47039459])
 2023-07-02 10:34:17,992 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:17,992 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47039459427515506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,992 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:17,992 [classy] Re-using computed results
 2023-07-02 10:34:17,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
 2023-07-02 10:34:17,992 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:17,992 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47039459427515506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:17,992 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,011 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45461
 2023-07-02 10:34:18,011 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,011 [model] Posterior to be computed for parameters {'Omega_m': 0.3434834197371073, 'b1': 0.47269982456895515}
 2023-07-02 10:34:18,011 [prior] Evaluating prior at array([0.34348342, 0.47269982])
 2023-07-02 10:34:18,011 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,011 [model] Got input parameters: {'Omega_m': 0.3434834197371073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47269982456895515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,011 [classy] Got parameters {'Omega_m': 0.3434834197371073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,011 [classy] Computing new state
 2023-07-02 10:34:18,012 [classy] Setting parameters: {'Omega_m': 0.3434834197371073, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.68615106961454}
 2023-07-02 10:34:18,055 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0548763
 2023-07-02 10:34:18,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47269982456895515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,057 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,077 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.68007
 2023-07-02 10:34:18,077 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,078 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.506043777338209}
 2023-07-02 10:34:18,078 [prior] Evaluating prior at array([0.31882915, 0.50604378])
 2023-07-02 10:34:18,078 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,078 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.506043777338209, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,078 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,078 [classy] Re-using computed results
 2023-07-02 10:34:18,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
 2023-07-02 10:34:18,078 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.506043777338209, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,078 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,097 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41524
 2023-07-02 10:34:18,097 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,098 [mcmc] New sample, #566:
   Omega_m:0.3188292, b1:0.5122574
 2023-07-02 10:34:18,098 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.4847200916920089}
 2023-07-02 10:34:18,098 [prior] Evaluating prior at array([0.33211915, 0.48472009])
 2023-07-02 10:34:18,098 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,098 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4847200916920089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,098 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,098 [classy] Computing new state
 2023-07-02 10:34:18,098 [classy] Setting parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,144 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
 2023-07-02 10:34:18,144 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,145 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0227367
 2023-07-02 10:34:18,146 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4847200916920089, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,146 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,165 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.767404
 2023-07-02 10:34:18,165 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,165 [mcmc] New sample, #567:
   Omega_m:0.3188292, b1:0.5060438
 2023-07-02 10:34:18,166 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.46325562182273516}
 2023-07-02 10:34:18,166 [prior] Evaluating prior at array([0.33211915, 0.46325562])
 2023-07-02 10:34:18,166 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,166 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46325562182273516, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,166 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,166 [classy] Re-using computed results
 2023-07-02 10:34:18,166 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
 2023-07-02 10:34:18,166 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46325562182273516, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,166 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,186 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3271
 2023-07-02 10:34:18,186 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,186 [mcmc] New sample, #568:
   Omega_m:0.3321191, b1:0.4847201
 2023-07-02 10:34:18,186 [model] Posterior to be computed for parameters {'Omega_m': 0.34488762013828034, 'b1': 0.44276870433858456}
 2023-07-02 10:34:18,186 [prior] Evaluating prior at array([0.34488762, 0.4427687 ])
 2023-07-02 10:34:18,186 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,186 [model] Got input parameters: {'Omega_m': 0.34488762013828034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44276870433858456, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,186 [classy] Got parameters {'Omega_m': 0.34488762013828034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,186 [classy] Computing new state
 2023-07-02 10:34:18,186 [classy] Setting parameters: {'Omega_m': 0.34488762013828034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,230 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.53126424036347}
 2023-07-02 10:34:18,230 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,232 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0597456
 2023-07-02 10:34:18,232 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44276870433858456, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,232 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,251 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.47869
 2023-07-02 10:34:18,251 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,252 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.46857828747262825}
 2023-07-02 10:34:18,252 [prior] Evaluating prior at array([0.33211915, 0.46857829])
 2023-07-02 10:34:18,252 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,252 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46857828747262825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,252 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,252 [classy] Re-using computed results
 2023-07-02 10:34:18,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
 2023-07-02 10:34:18,252 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,252 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46857828747262825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,252 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,271 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42556
 2023-07-02 10:34:18,271 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,272 [mcmc] New sample, #569:
   Omega_m:0.3321191, b1:0.4632556
 2023-07-02 10:34:18,272 [model] Posterior to be computed for parameters {'Omega_m': 0.28290987132865336, 'b1': 0.5475341792425563}
 2023-07-02 10:34:18,272 [prior] Evaluating prior at array([0.28290987, 0.54753418])
 2023-07-02 10:34:18,272 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,272 [model] Got input parameters: {'Omega_m': 0.28290987132865336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5475341792425563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,272 [classy] Got parameters {'Omega_m': 0.28290987132865336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,272 [classy] Computing new state
 2023-07-02 10:34:18,272 [classy] Setting parameters: {'Omega_m': 0.28290987132865336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.9759878957657}
 2023-07-02 10:34:18,316 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,317 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0580564
 2023-07-02 10:34:18,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5475341792425563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,317 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,337 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.09318
 2023-07-02 10:34:18,337 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,337 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.4105146666016665}
 2023-07-02 10:34:18,337 [prior] Evaluating prior at array([0.33211915, 0.41051467])
 2023-07-02 10:34:18,338 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,338 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4105146666016665, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,338 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,338 [classy] Re-using computed results
 2023-07-02 10:34:18,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
 2023-07-02 10:34:18,338 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4105146666016665, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,338 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.48653
 2023-07-02 10:34:18,357 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,357 [model] Posterior to be computed for parameters {'Omega_m': 0.3691494160591612, 'b1': 0.4091635097441123}
 2023-07-02 10:34:18,357 [prior] Evaluating prior at array([0.36914942, 0.40916351])
 2023-07-02 10:34:18,357 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,357 [model] Got input parameters: {'Omega_m': 0.3691494160591612, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4091635097441123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,357 [classy] Got parameters {'Omega_m': 0.3691494160591612, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,357 [classy] Computing new state
 2023-07-02 10:34:18,357 [classy] Setting parameters: {'Omega_m': 0.3691494160591612, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.94293474479315}
 2023-07-02 10:34:18,402 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.172435
 2023-07-02 10:34:18,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4091635097441123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,404 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,424 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.1906
 2023-07-02 10:34:18,424 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,424 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.483681501245867}
 2023-07-02 10:34:18,424 [prior] Evaluating prior at array([0.33211915, 0.4836815 ])
 2023-07-02 10:34:18,424 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,424 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.483681501245867, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,424 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,424 [classy] Re-using computed results
 2023-07-02 10:34:18,424 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
 2023-07-02 10:34:18,424 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.483681501245867, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,424 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.853962
 2023-07-02 10:34:18,444 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,444 [model] Posterior to be computed for parameters {'Omega_m': 0.3345171149089384, 'b1': 0.4647307638547759}
 2023-07-02 10:34:18,444 [prior] Evaluating prior at array([0.33451711, 0.46473076])
 2023-07-02 10:34:18,444 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,444 [model] Got input parameters: {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4647307638547759, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,444 [classy] Got parameters {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,444 [classy] Computing new state
 2023-07-02 10:34:18,444 [classy] Setting parameters: {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.68896567031166}
 2023-07-02 10:34:18,488 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,490 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0284141
 2023-07-02 10:34:18,490 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4647307638547759, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,490 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,509 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.99169
 2023-07-02 10:34:18,509 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,509 [mcmc] New sample, #570:
   Omega_m:0.3321191, b1:0.4685783
 2023-07-02 10:34:18,510 [model] Posterior to be computed for parameters {'Omega_m': 0.3345171149089384, 'b1': 0.4575059592904157}
 2023-07-02 10:34:18,510 [prior] Evaluating prior at array([0.33451711, 0.45750596])
 2023-07-02 10:34:18,510 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,510 [model] Got input parameters: {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4575059592904157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,510 [classy] Got parameters {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,510 [classy] Re-using computed results
 2023-07-02 10:34:18,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.68896567031166}
 2023-07-02 10:34:18,510 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,510 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4575059592904157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,510 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,530 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.839723
 2023-07-02 10:34:18,530 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,530 [model] Posterior to be computed for parameters {'Omega_m': 0.3251680275444227, 'b1': 0.4797313008111108}
 2023-07-02 10:34:18,530 [prior] Evaluating prior at array([0.32516803, 0.4797313 ])
 2023-07-02 10:34:18,530 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,530 [model] Got input parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4797313008111108, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,530 [classy] Got parameters {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,530 [classy] Computing new state
 2023-07-02 10:34:18,530 [classy] Setting parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76083460052172}
 2023-07-02 10:34:18,574 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00976458
 2023-07-02 10:34:18,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4797313008111108, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,576 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,596 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37746
 2023-07-02 10:34:18,596 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,596 [mcmc] New sample, #571:
   Omega_m:0.3345171, b1:0.4647308
 2023-07-02 10:34:18,596 [model] Posterior to be computed for parameters {'Omega_m': 0.3251680275444227, 'b1': 0.47941505850622906}
 2023-07-02 10:34:18,596 [prior] Evaluating prior at array([0.32516803, 0.47941506])
 2023-07-02 10:34:18,596 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,596 [model] Got input parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47941505850622906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,596 [classy] Got parameters {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,596 [classy] Re-using computed results
 2023-07-02 10:34:18,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76083460052172}
 2023-07-02 10:34:18,596 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47941505850622906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,596 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37347
 2023-07-02 10:34:18,616 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,616 [mcmc] New sample, #572:
   Omega_m:0.325168, b1:0.4797313
 2023-07-02 10:34:18,616 [model] Posterior to be computed for parameters {'Omega_m': 0.30042496489678194, 'b1': 0.519115107418765}
 2023-07-02 10:34:18,616 [prior] Evaluating prior at array([0.30042496, 0.51911511])
 2023-07-02 10:34:18,616 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,616 [model] Got input parameters: {'Omega_m': 0.30042496489678194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.519115107418765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,616 [classy] Got parameters {'Omega_m': 0.30042496489678194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,616 [classy] Computing new state
 2023-07-02 10:34:18,616 [classy] Setting parameters: {'Omega_m': 0.30042496489678194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,661 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73648349023696}
 2023-07-02 10:34:18,661 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00939399
 2023-07-02 10:34:18,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.519115107418765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,663 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,682 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46589
 2023-07-02 10:34:18,682 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,683 [model] Posterior to be computed for parameters {'Omega_m': 0.3251680275444227, 'b1': 0.46384885979996043}
 2023-07-02 10:34:18,683 [prior] Evaluating prior at array([0.32516803, 0.46384886])
 2023-07-02 10:34:18,683 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,683 [model] Got input parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46384885979996043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,683 [classy] Got parameters {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,683 [classy] Re-using computed results
 2023-07-02 10:34:18,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76083460052172}
 2023-07-02 10:34:18,683 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46384885979996043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,683 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,702 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51943
 2023-07-02 10:34:18,702 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,702 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.48359189458111673}
 2023-07-02 10:34:18,702 [prior] Evaluating prior at array([0.32256481, 0.48359189])
 2023-07-02 10:34:18,703 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,703 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48359189458111673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,703 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,703 [classy] Computing new state
 2023-07-02 10:34:18,703 [classy] Setting parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,746 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
 2023-07-02 10:34:18,746 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,748 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00628066
 2023-07-02 10:34:18,748 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48359189458111673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,748 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,767 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60562
 2023-07-02 10:34:18,768 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,768 [mcmc] New sample, #573:
   Omega_m:0.325168, b1:0.4794151
 2023-07-02 10:34:18,768 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.46448513800977925}
 2023-07-02 10:34:18,768 [prior] Evaluating prior at array([0.32256481, 0.46448514])
 2023-07-02 10:34:18,768 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,768 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46448513800977925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,768 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,768 [classy] Re-using computed results
 2023-07-02 10:34:18,768 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
 2023-07-02 10:34:18,768 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,768 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46448513800977925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,768 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,788 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32957
 2023-07-02 10:34:18,788 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,788 [model] Posterior to be computed for parameters {'Omega_m': 0.3423149098023159, 'b1': 0.45190302113114844}
 2023-07-02 10:34:18,788 [prior] Evaluating prior at array([0.34231491, 0.45190302])
 2023-07-02 10:34:18,788 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,788 [model] Got input parameters: {'Omega_m': 0.3423149098023159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45190302113114844, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,788 [classy] Got parameters {'Omega_m': 0.3423149098023159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,788 [classy] Computing new state
 2023-07-02 10:34:18,788 [classy] Setting parameters: {'Omega_m': 0.3423149098023159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,832 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.81548503423645}
 2023-07-02 10:34:18,832 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,834 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.050971
 2023-07-02 10:34:18,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45190302113114844, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,834 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,854 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.762956
 2023-07-02 10:34:18,854 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.4721307328033743}
 2023-07-02 10:34:18,854 [prior] Evaluating prior at array([0.32256481, 0.47213073])
 2023-07-02 10:34:18,854 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,854 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4721307328033743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,854 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,854 [classy] Re-using computed results
 2023-07-02 10:34:18,854 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
 2023-07-02 10:34:18,854 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,854 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4721307328033743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,854 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,873 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06868
 2023-07-02 10:34:18,873 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,874 [model] Posterior to be computed for parameters {'Omega_m': 0.33285293017405154, 'b1': 0.4670846928344826}
 2023-07-02 10:34:18,874 [prior] Evaluating prior at array([0.33285293, 0.46708469])
 2023-07-02 10:34:18,874 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,874 [model] Got input parameters: {'Omega_m': 0.33285293017405154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4670846928344826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,874 [classy] Got parameters {'Omega_m': 0.33285293017405154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,874 [classy] Computing new state
 2023-07-02 10:34:18,874 [classy] Setting parameters: {'Omega_m': 0.33285293017405154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:18,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.87776024357615}
 2023-07-02 10:34:18,918 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:18,919 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244097
 2023-07-02 10:34:18,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4670846928344826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,920 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,939 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29705
 2023-07-02 10:34:18,940 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,940 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.5220972866468442}
 2023-07-02 10:34:18,940 [prior] Evaluating prior at array([0.32256481, 0.52209729])
 2023-07-02 10:34:18,940 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,940 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5220972866468442, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,940 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,940 [classy] Re-using computed results
 2023-07-02 10:34:18,940 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
 2023-07-02 10:34:18,940 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:18,940 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5220972866468442, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,940 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:18,959 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.910166
 2023-07-02 10:34:18,959 [model] Computed derived parameters: {}
 2023-07-02 10:34:18,959 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.48406719709069745}
 2023-07-02 10:34:18,959 [prior] Evaluating prior at array([0.32226858, 0.4840672 ])
 2023-07-02 10:34:18,959 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:18,960 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48406719709069745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:18,960 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:18,960 [classy] Computing new state
 2023-07-02 10:34:18,960 [classy] Setting parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
 2023-07-02 10:34:19,004 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00593268
 2023-07-02 10:34:19,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48406719709069745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,006 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62759
 2023-07-02 10:34:19,026 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,026 [mcmc] New sample, #574:
   Omega_m:0.3225648, b1:0.4835919
 2023-07-02 10:34:19,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.5017720279759543}
 2023-07-02 10:34:19,026 [prior] Evaluating prior at array([0.32226858, 0.50177203])
 2023-07-02 10:34:19,026 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,026 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5017720279759543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,026 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,026 [classy] Re-using computed results
 2023-07-02 10:34:19,026 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
 2023-07-02 10:34:19,026 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,026 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5017720279759543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,026 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,046 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06521
 2023-07-02 10:34:19,046 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,046 [model] Posterior to be computed for parameters {'Omega_m': 0.3327163516282342, 'b1': 0.46730383203428855}
 2023-07-02 10:34:19,046 [prior] Evaluating prior at array([0.33271635, 0.46730383])
 2023-07-02 10:34:19,046 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,046 [model] Got input parameters: {'Omega_m': 0.3327163516282342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46730383203428855, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,046 [classy] Got parameters {'Omega_m': 0.3327163516282342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,046 [classy] Computing new state
 2023-07-02 10:34:19,046 [classy] Setting parameters: {'Omega_m': 0.3327163516282342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,090 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.89329414169708}
 2023-07-02 10:34:19,090 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,092 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0240939
 2023-07-02 10:34:19,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46730383203428855, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,093 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,112 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32105
 2023-07-02 10:34:19,112 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,112 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.39976009914808924}
 2023-07-02 10:34:19,112 [prior] Evaluating prior at array([0.32226858, 0.3997601 ])
 2023-07-02 10:34:19,112 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,112 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39976009914808924, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,112 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,112 [classy] Re-using computed results
 2023-07-02 10:34:19,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
 2023-07-02 10:34:19,112 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39976009914808924, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,112 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,134 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.3102
 2023-07-02 10:34:19,134 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,134 [model] Posterior to be computed for parameters {'Omega_m': 0.3314000913515809, 'b1': 0.4694157612691179}
 2023-07-02 10:34:19,134 [prior] Evaluating prior at array([0.33140009, 0.46941576])
 2023-07-02 10:34:19,134 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,134 [model] Got input parameters: {'Omega_m': 0.3314000913515809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4694157612691179, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,134 [classy] Got parameters {'Omega_m': 0.3314000913515809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,134 [classy] Computing new state
 2023-07-02 10:34:19,134 [classy] Setting parameters: {'Omega_m': 0.3314000913515809, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0432780066275}
 2023-07-02 10:34:19,178 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,180 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0211528
 2023-07-02 10:34:19,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4694157612691179, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,180 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,200 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54361
 2023-07-02 10:34:19,200 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,200 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.4605219610957813}
 2023-07-02 10:34:19,200 [prior] Evaluating prior at array([0.32226858, 0.46052196])
 2023-07-02 10:34:19,200 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,201 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4605219610957813, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,201 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,201 [classy] Re-using computed results
 2023-07-02 10:34:19,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
 2023-07-02 10:34:19,201 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,201 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4605219610957813, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,201 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,220 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.778907
 2023-07-02 10:34:19,220 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,220 [model] Posterior to be computed for parameters {'Omega_m': 0.309568902714246, 'b1': 0.5044437312930161}
 2023-07-02 10:34:19,220 [prior] Evaluating prior at array([0.3095689 , 0.50444373])
 2023-07-02 10:34:19,220 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,220 [model] Got input parameters: {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5044437312930161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,220 [classy] Got parameters {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,220 [classy] Computing new state
 2023-07-02 10:34:19,220 [classy] Setting parameters: {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61235747132253}
 2023-07-02 10:34:19,264 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000727312
 2023-07-02 10:34:19,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5044437312930161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,266 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,286 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65604
 2023-07-02 10:34:19,286 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,286 [mcmc] New sample, #575:
   Omega_m:0.3222686, b1:0.4840672
 2023-07-02 10:34:19,286 [model] Posterior to be computed for parameters {'Omega_m': 0.309568902714246, 'b1': 0.5041431400491372}
 2023-07-02 10:34:19,286 [prior] Evaluating prior at array([0.3095689 , 0.50414314])
 2023-07-02 10:34:19,286 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,286 [model] Got input parameters: {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5041431400491372, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,286 [classy] Got parameters {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,286 [classy] Re-using computed results
 2023-07-02 10:34:19,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61235747132253}
 2023-07-02 10:34:19,286 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5041431400491372, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,286 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,306 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64659
 2023-07-02 10:34:19,306 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,306 [mcmc] New sample, #576:
   Omega_m:0.3095689, b1:0.5044437
 2023-07-02 10:34:19,306 [model] Posterior to be computed for parameters {'Omega_m': 0.31630045365259457, 'b1': 0.49334241964861925}
 2023-07-02 10:34:19,306 [prior] Evaluating prior at array([0.31630045, 0.49334242])
 2023-07-02 10:34:19,306 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,306 [model] Got input parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49334241964861925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,306 [classy] Got parameters {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,306 [classy] Computing new state
 2023-07-02 10:34:19,306 [classy] Setting parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,350 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80337053060526}
 2023-07-02 10:34:19,350 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,352 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00108719
 2023-07-02 10:34:19,352 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49334241964861925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,352 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.86189
 2023-07-02 10:34:19,371 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,371 [mcmc] New sample, #577:
   Omega_m:0.3095689, b1:0.5041431
 2023-07-02 10:34:19,372 [model] Posterior to be computed for parameters {'Omega_m': 0.31630045365259457, 'b1': 0.496674452613616}
 2023-07-02 10:34:19,372 [prior] Evaluating prior at array([0.31630045, 0.49667445])
 2023-07-02 10:34:19,372 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,372 [model] Got input parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.496674452613616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,372 [classy] Got parameters {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,372 [classy] Re-using computed results
 2023-07-02 10:34:19,372 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80337053060526}
 2023-07-02 10:34:19,372 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,372 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.496674452613616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,372 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,392 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91521
 2023-07-02 10:34:19,392 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,392 [mcmc] New sample, #578:
   Omega_m:0.3163005, b1:0.4933424
 2023-07-02 10:34:19,392 [model] Posterior to be computed for parameters {'Omega_m': 0.33061656367639586, 'b1': 0.4737043669667468}
 2023-07-02 10:34:19,392 [prior] Evaluating prior at array([0.33061656, 0.47370437])
 2023-07-02 10:34:19,392 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,392 [model] Got input parameters: {'Omega_m': 0.33061656367639586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4737043669667468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,392 [classy] Got parameters {'Omega_m': 0.33061656367639586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,392 [classy] Computing new state
 2023-07-02 10:34:19,392 [classy] Setting parameters: {'Omega_m': 0.33061656367639586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.13281407870255}
 2023-07-02 10:34:19,436 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0194896
 2023-07-02 10:34:19,438 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4737043669667468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,438 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,458 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66588
 2023-07-02 10:34:19,458 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,458 [model] Posterior to be computed for parameters {'Omega_m': 0.31630045365259457, 'b1': 0.48135175419687165}
 2023-07-02 10:34:19,458 [prior] Evaluating prior at array([0.31630045, 0.48135175])
 2023-07-02 10:34:19,458 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,458 [model] Got input parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48135175419687165, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,458 [classy] Got parameters {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,458 [classy] Re-using computed results
 2023-07-02 10:34:19,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80337053060526}
 2023-07-02 10:34:19,458 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,458 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48135175419687165, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,458 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,477 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18525
 2023-07-02 10:34:19,477 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,478 [mcmc] New sample, #579:
   Omega_m:0.3163005, b1:0.4966745
 2023-07-02 10:34:19,478 [model] Posterior to be computed for parameters {'Omega_m': 0.32207127041761824, 'b1': 0.4720925242018101}
 2023-07-02 10:34:19,478 [prior] Evaluating prior at array([0.32207127, 0.47209252])
 2023-07-02 10:34:19,478 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,478 [model] Got input parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4720925242018101, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,478 [classy] Got parameters {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,478 [classy] Computing new state
 2023-07-02 10:34:19,478 [classy] Setting parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,522 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12199829578879}
 2023-07-02 10:34:19,523 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,524 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00570662
 2023-07-02 10:34:19,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4720925242018101, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,524 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,544 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03267
 2023-07-02 10:34:19,544 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,544 [mcmc] New sample, #580:
   Omega_m:0.3163005, b1:0.4813518
 2023-07-02 10:34:19,544 [model] Posterior to be computed for parameters {'Omega_m': 0.32207127041761824, 'b1': 0.44774432278508847}
 2023-07-02 10:34:19,544 [prior] Evaluating prior at array([0.32207127, 0.44774432])
 2023-07-02 10:34:19,544 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,545 [model] Got input parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44774432278508847, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,545 [classy] Got parameters {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,545 [classy] Re-using computed results
 2023-07-02 10:34:19,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12199829578879}
 2023-07-02 10:34:19,545 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,545 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44774432278508847, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,545 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,564 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.45478
 2023-07-02 10:34:19,564 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,564 [model] Posterior to be computed for parameters {'Omega_m': 0.3402449266571032, 'b1': 0.4429330360696503}
 2023-07-02 10:34:19,564 [prior] Evaluating prior at array([0.34024493, 0.44293304])
 2023-07-02 10:34:19,564 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,564 [model] Got input parameters: {'Omega_m': 0.3402449266571032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4429330360696503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,564 [classy] Got parameters {'Omega_m': 0.3402449266571032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,564 [classy] Computing new state
 2023-07-02 10:34:19,564 [classy] Setting parameters: {'Omega_m': 0.3402449266571032, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,609 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.0455863290492}
 2023-07-02 10:34:19,609 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,611 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0443841
 2023-07-02 10:34:19,611 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4429330360696503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,611 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,630 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.620192
 2023-07-02 10:34:19,630 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,630 [model] Posterior to be computed for parameters {'Omega_m': 0.32207127041761824, 'b1': 0.5123821009017084}
 2023-07-02 10:34:19,630 [prior] Evaluating prior at array([0.32207127, 0.5123821 ])
 2023-07-02 10:34:19,630 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,630 [model] Got input parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123821009017084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,630 [classy] Got parameters {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,630 [classy] Re-using computed results
 2023-07-02 10:34:19,631 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12199829578879}
 2023-07-02 10:34:19,631 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,631 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123821009017084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,631 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.947895
 2023-07-02 10:34:19,650 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,650 [mcmc] New sample, #581:
   Omega_m:0.3220713, b1:0.4720925
 2023-07-02 10:34:19,651 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.514405588826632}
 2023-07-02 10:34:19,651 [prior] Evaluating prior at array([0.32081013, 0.51440559])
 2023-07-02 10:34:19,651 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,651 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.514405588826632, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,651 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,651 [classy] Computing new state
 2023-07-02 10:34:19,651 [classy] Setting parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:19,695 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00436657
 2023-07-02 10:34:19,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.514405588826632, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,697 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,716 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07177
 2023-07-02 10:34:19,716 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,716 [mcmc] New sample, #582:
   Omega_m:0.3220713, b1:0.5123821
 2023-07-02 10:34:19,716 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.49572030167286996}
 2023-07-02 10:34:19,716 [prior] Evaluating prior at array([0.32081013, 0.4957203 ])
 2023-07-02 10:34:19,716 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,716 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49572030167286996, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,716 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,716 [classy] Re-using computed results
 2023-07-02 10:34:19,716 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:19,716 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49572030167286996, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,716 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65796
 2023-07-02 10:34:19,736 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,736 [mcmc] New sample, #583:
   Omega_m:0.3208101, b1:0.5144056
 2023-07-02 10:34:19,736 [model] Posterior to be computed for parameters {'Omega_m': 0.32269572483744435, 'b1': 0.49269488155532387}
 2023-07-02 10:34:19,736 [prior] Evaluating prior at array([0.32269572, 0.49269488])
 2023-07-02 10:34:19,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,736 [model] Got input parameters: {'Omega_m': 0.32269572483744435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49269488155532387, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,736 [classy] Got parameters {'Omega_m': 0.32269572483744435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,736 [classy] Computing new state
 2023-07-02 10:34:19,736 [classy] Setting parameters: {'Omega_m': 0.32269572483744435, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.04892208524046}
 2023-07-02 10:34:19,780 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,782 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00643749
 2023-07-02 10:34:19,782 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49269488155532387, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,782 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,803 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51118
 2023-07-02 10:34:19,803 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,803 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.48747975598648347}
 2023-07-02 10:34:19,803 [prior] Evaluating prior at array([0.32081013, 0.48747976])
 2023-07-02 10:34:19,803 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,803 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48747975598648347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,803 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,803 [classy] Re-using computed results
 2023-07-02 10:34:19,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:19,803 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,803 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48747975598648347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,803 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73881
 2023-07-02 10:34:19,822 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,823 [mcmc] New sample, #584:
   Omega_m:0.3208101, b1:0.4957203
 2023-07-02 10:34:19,823 [model] Posterior to be computed for parameters {'Omega_m': 0.3544554814046757, 'b1': 0.43349605689090864}
 2023-07-02 10:34:19,823 [prior] Evaluating prior at array([0.35445548, 0.43349606])
 2023-07-02 10:34:19,823 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,823 [model] Got input parameters: {'Omega_m': 0.3544554814046757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43349605689090864, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,823 [classy] Got parameters {'Omega_m': 0.3544554814046757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,823 [classy] Computing new state
 2023-07-02 10:34:19,823 [classy] Setting parameters: {'Omega_m': 0.3544554814046757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,869 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.49108284724593}
 2023-07-02 10:34:19,870 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,871 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.097902
 2023-07-02 10:34:19,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43349605689090864, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,871 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,890 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.46302
 2023-07-02 10:34:19,890 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,891 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.5548511060510317}
 2023-07-02 10:34:19,891 [prior] Evaluating prior at array([0.32081013, 0.55485111])
 2023-07-02 10:34:19,891 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,891 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5548511060510317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,891 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,891 [classy] Re-using computed results
 2023-07-02 10:34:19,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:19,891 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,891 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5548511060510317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,891 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,911 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.48431
 2023-07-02 10:34:19,911 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,911 [model] Posterior to be computed for parameters {'Omega_m': 0.34458551923748154, 'b1': 0.4493323333609053}
 2023-07-02 10:34:19,911 [prior] Evaluating prior at array([0.34458552, 0.44933233])
 2023-07-02 10:34:19,911 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,911 [model] Got input parameters: {'Omega_m': 0.34458551923748154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4493323333609053, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,911 [classy] Got parameters {'Omega_m': 0.34458551923748154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,911 [classy] Computing new state
 2023-07-02 10:34:19,911 [classy] Setting parameters: {'Omega_m': 0.34458551923748154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:19,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.56453323800775}
 2023-07-02 10:34:19,958 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:19,960 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0586822
 2023-07-02 10:34:19,960 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4493323333609053, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,960 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:19,979 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.37911
 2023-07-02 10:34:19,979 [model] Computed derived parameters: {}
 2023-07-02 10:34:19,979 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.48525705618702586}
 2023-07-02 10:34:19,979 [prior] Evaluating prior at array([0.32081013, 0.48525706])
 2023-07-02 10:34:19,980 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:19,980 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48525705618702586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,980 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:19,980 [classy] Re-using computed results
 2023-07-02 10:34:19,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:19,980 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:19,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48525705618702586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:19,980 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,000 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69764
 2023-07-02 10:34:20,000 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,000 [mcmc] New sample, #585:
   Omega_m:0.3208101, b1:0.4874798
 2023-07-02 10:34:20,000 [model] Posterior to be computed for parameters {'Omega_m': 0.33698350134927635, 'b1': 0.4593070113191481}
 2023-07-02 10:34:20,000 [prior] Evaluating prior at array([0.3369835 , 0.45930701])
 2023-07-02 10:34:20,000 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,000 [model] Got input parameters: {'Omega_m': 0.33698350134927635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4593070113191481, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,000 [classy] Got parameters {'Omega_m': 0.33698350134927635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,000 [classy] Computing new state
 2023-07-02 10:34:20,000 [classy] Setting parameters: {'Omega_m': 0.33698350134927635, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.41071656787383}
 2023-07-02 10:34:20,047 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0348792
 2023-07-02 10:34:20,048 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4593070113191481, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,049 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,068 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.488039
 2023-07-02 10:34:20,068 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,068 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.489559830250117}
 2023-07-02 10:34:20,068 [prior] Evaluating prior at array([0.32081013, 0.48955983])
 2023-07-02 10:34:20,068 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,068 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489559830250117, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,068 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,068 [classy] Re-using computed results
 2023-07-02 10:34:20,068 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:20,068 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489559830250117, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,068 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,088 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75326
 2023-07-02 10:34:20,088 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,088 [mcmc] New sample, #586:
   Omega_m:0.3208101, b1:0.4852571
 2023-07-02 10:34:20,088 [model] Posterior to be computed for parameters {'Omega_m': 0.33733528308750954, 'b1': 0.4630453543571363}
 2023-07-02 10:34:20,088 [prior] Evaluating prior at array([0.33733528, 0.46304535])
 2023-07-02 10:34:20,088 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,088 [model] Got input parameters: {'Omega_m': 0.33733528308750954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4630453543571363, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,088 [classy] Got parameters {'Omega_m': 0.33733528308750954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,088 [classy] Computing new state
 2023-07-02 10:34:20,088 [classy] Setting parameters: {'Omega_m': 0.33733528308750954, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.37117775021488}
 2023-07-02 10:34:20,137 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0358525
 2023-07-02 10:34:20,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4630453543571363, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,139 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,159 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.38923
 2023-07-02 10:34:20,159 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,159 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.539621897224631}
 2023-07-02 10:34:20,160 [prior] Evaluating prior at array([0.32081013, 0.5396219 ])
 2023-07-02 10:34:20,160 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,160 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.539621897224631, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,160 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,160 [classy] Re-using computed results
 2023-07-02 10:34:20,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:20,160 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.539621897224631, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,160 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,180 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.31746
 2023-07-02 10:34:20,180 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,180 [model] Posterior to be computed for parameters {'Omega_m': 0.3676346496046627, 'b1': 0.4144302596988956}
 2023-07-02 10:34:20,180 [prior] Evaluating prior at array([0.36763465, 0.41443026])
 2023-07-02 10:34:20,180 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,180 [model] Got input parameters: {'Omega_m': 0.3676346496046627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4144302596988956, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,180 [classy] Got parameters {'Omega_m': 0.3676346496046627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,180 [classy] Computing new state
 2023-07-02 10:34:20,180 [classy] Setting parameters: {'Omega_m': 0.3676346496046627, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,227 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.09986397891416}
 2023-07-02 10:34:20,227 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,229 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.163906
 2023-07-02 10:34:20,229 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4144302596988956, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,229 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,248 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.6609
 2023-07-02 10:34:20,248 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.5313958150440904}
 2023-07-02 10:34:20,248 [prior] Evaluating prior at array([0.32081013, 0.53139582])
 2023-07-02 10:34:20,249 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,249 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5313958150440904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,249 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,249 [classy] Re-using computed results
 2023-07-02 10:34:20,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
 2023-07-02 10:34:20,249 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,249 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5313958150440904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,249 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,268 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.13505
 2023-07-02 10:34:20,268 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3289026332147191, 'b1': 0.4765754745843504}
 2023-07-02 10:34:20,269 [prior] Evaluating prior at array([0.32890263, 0.47657547])
 2023-07-02 10:34:20,269 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,269 [model] Got input parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4765754745843504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,269 [classy] Got parameters {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,269 [classy] Computing new state
 2023-07-02 10:34:20,269 [classy] Setting parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,315 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32934705197334}
 2023-07-02 10:34:20,315 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,317 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0160814
 2023-07-02 10:34:20,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4765754745843504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,317 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,336 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.92367
 2023-07-02 10:34:20,336 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,337 [mcmc] New sample, #587:
   Omega_m:0.3208101, b1:0.4895598
 2023-07-02 10:34:20,337 [model] Posterior to be computed for parameters {'Omega_m': 0.3289026332147191, 'b1': 0.511913457355319}
 2023-07-02 10:34:20,337 [prior] Evaluating prior at array([0.32890263, 0.51191346])
 2023-07-02 10:34:20,337 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,337 [model] Got input parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.511913457355319, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,337 [classy] Got parameters {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,337 [classy] Re-using computed results
 2023-07-02 10:34:20,337 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32934705197334}
 2023-07-02 10:34:20,337 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,337 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.511913457355319, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,337 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.90211
 2023-07-02 10:34:20,357 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,357 [model] Posterior to be computed for parameters {'Omega_m': 0.37708108121482425, 'b1': 0.399273534668007}
 2023-07-02 10:34:20,357 [prior] Evaluating prior at array([0.37708108, 0.39927353])
 2023-07-02 10:34:20,357 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,357 [model] Got input parameters: {'Omega_m': 0.37708108121482425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.399273534668007, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,357 [classy] Got parameters {'Omega_m': 0.37708108121482425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,357 [classy] Computing new state
 2023-07-02 10:34:20,357 [classy] Setting parameters: {'Omega_m': 0.37708108121482425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.1309004510357}
 2023-07-02 10:34:20,403 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.220106
 2023-07-02 10:34:20,405 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.399273534668007, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,405 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,425 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.917
 2023-07-02 10:34:20,425 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,425 [model] Posterior to be computed for parameters {'Omega_m': 0.3289026332147191, 'b1': 0.4590033429366307}
 2023-07-02 10:34:20,425 [prior] Evaluating prior at array([0.32890263, 0.45900334])
 2023-07-02 10:34:20,425 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,425 [model] Got input parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4590033429366307, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,425 [classy] Got parameters {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,425 [classy] Re-using computed results
 2023-07-02 10:34:20,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32934705197334}
 2023-07-02 10:34:20,425 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4590033429366307, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,425 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23022
 2023-07-02 10:34:20,445 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,445 [mcmc] New sample, #588:
   Omega_m:0.3289026, b1:0.4765755
 2023-07-02 10:34:20,445 [model] Posterior to be computed for parameters {'Omega_m': 0.32100907256639155, 'b1': 0.47166849875405537}
 2023-07-02 10:34:20,445 [prior] Evaluating prior at array([0.32100907, 0.4716685 ])
 2023-07-02 10:34:20,445 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,445 [model] Got input parameters: {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47166849875405537, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,445 [classy] Got parameters {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,445 [classy] Computing new state
 2023-07-02 10:34:20,445 [classy] Setting parameters: {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,491 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.24659446686888}
 2023-07-02 10:34:20,491 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,493 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00456581
 2023-07-02 10:34:20,493 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47166849875405537, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,493 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,513 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8998
 2023-07-02 10:34:20,513 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,513 [mcmc] New sample, #589:
   Omega_m:0.3289026, b1:0.4590033
 2023-07-02 10:34:20,513 [model] Posterior to be computed for parameters {'Omega_m': 0.32100907256639155, 'b1': 0.4516625191844553}
 2023-07-02 10:34:20,513 [prior] Evaluating prior at array([0.32100907, 0.45166252])
 2023-07-02 10:34:20,513 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,513 [model] Got input parameters: {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4516625191844553, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,513 [classy] Got parameters {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,513 [classy] Re-using computed results
 2023-07-02 10:34:20,513 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.24659446686888}
 2023-07-02 10:34:20,513 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4516625191844553, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,513 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,533 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.983418
 2023-07-02 10:34:20,533 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,533 [model] Posterior to be computed for parameters {'Omega_m': 0.30920681555238894, 'b1': 0.49060512706909953}
 2023-07-02 10:34:20,533 [prior] Evaluating prior at array([0.30920682, 0.49060513])
 2023-07-02 10:34:20,533 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,533 [model] Got input parameters: {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49060512706909953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,533 [classy] Got parameters {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,533 [classy] Computing new state
 2023-07-02 10:34:20,533 [classy] Setting parameters: {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.65631469921092}
 2023-07-02 10:34:20,580 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000866428
 2023-07-02 10:34:20,582 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49060512706909953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,582 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,601 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64164
 2023-07-02 10:34:20,601 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,601 [mcmc] New sample, #590:
   Omega_m:0.3210091, b1:0.4716685
 2023-07-02 10:34:20,601 [model] Posterior to be computed for parameters {'Omega_m': 0.30920681555238894, 'b1': 0.37544542411639775}
 2023-07-02 10:34:20,602 [prior] Evaluating prior at array([0.30920682, 0.37544542])
 2023-07-02 10:34:20,602 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,602 [model] Got input parameters: {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37544542411639775, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,602 [classy] Got parameters {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,602 [classy] Re-using computed results
 2023-07-02 10:34:20,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.65631469921092}
 2023-07-02 10:34:20,602 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37544542411639775, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,602 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.0954
 2023-07-02 10:34:20,622 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,622 [model] Posterior to be computed for parameters {'Omega_m': 0.315205769466246, 'b1': 0.4809798528176567}
 2023-07-02 10:34:20,622 [prior] Evaluating prior at array([0.31520577, 0.48097985])
 2023-07-02 10:34:20,622 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,622 [model] Got input parameters: {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4809798528176567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,622 [classy] Got parameters {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,622 [classy] Computing new state
 2023-07-02 10:34:20,622 [classy] Setting parameters: {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,669 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9338687893775}
 2023-07-02 10:34:20,669 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,670 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000653707
 2023-07-02 10:34:20,670 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4809798528176567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,671 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,690 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.97225
 2023-07-02 10:34:20,690 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,690 [mcmc] New sample, #591:
   Omega_m:0.3092068, b1:0.4906051
 2023-07-02 10:34:20,690 [model] Posterior to be computed for parameters {'Omega_m': 0.315205769466246, 'b1': 0.4935116725125957}
 2023-07-02 10:34:20,690 [prior] Evaluating prior at array([0.31520577, 0.49351167])
 2023-07-02 10:34:20,690 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,690 [model] Got input parameters: {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935116725125957, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,690 [classy] Got parameters {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,690 [classy] Re-using computed results
 2023-07-02 10:34:20,690 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9338687893775}
 2023-07-02 10:34:20,691 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935116725125957, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,691 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,710 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81483
 2023-07-02 10:34:20,710 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,711 [mcmc] New sample, #592:
   Omega_m:0.3152058, b1:0.4809799
 2023-07-02 10:34:20,711 [model] Posterior to be computed for parameters {'Omega_m': 0.2997242142097797, 'b1': 0.5183517058454316}
 2023-07-02 10:34:20,711 [prior] Evaluating prior at array([0.29972421, 0.51835171])
 2023-07-02 10:34:20,711 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,711 [model] Got input parameters: {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183517058454316, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,711 [classy] Got parameters {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,711 [classy] Computing new state
 2023-07-02 10:34:20,711 [classy] Setting parameters: {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.82387556999797}
 2023-07-02 10:34:20,758 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0105118
 2023-07-02 10:34:20,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183517058454316, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,760 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,779 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24208
 2023-07-02 10:34:20,779 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,779 [mcmc] New sample, #593:
   Omega_m:0.3152058, b1:0.4935117
 2023-07-02 10:34:20,780 [model] Posterior to be computed for parameters {'Omega_m': 0.2997242142097797, 'b1': 0.5182346109804218}
 2023-07-02 10:34:20,780 [prior] Evaluating prior at array([0.29972421, 0.51823461])
 2023-07-02 10:34:20,780 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,780 [model] Got input parameters: {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5182346109804218, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,780 [classy] Got parameters {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,780 [classy] Re-using computed results
 2023-07-02 10:34:20,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.82387556999797}
 2023-07-02 10:34:20,780 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5182346109804218, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,780 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,799 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23608
 2023-07-02 10:34:20,799 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,799 [mcmc] New sample, #594:
   Omega_m:0.2997242, b1:0.5183517
 2023-07-02 10:34:20,799 [model] Posterior to be computed for parameters {'Omega_m': 0.3012898083111917, 'b1': 0.5157226275898305}
 2023-07-02 10:34:20,799 [prior] Evaluating prior at array([0.30128981, 0.51572263])
 2023-07-02 10:34:20,800 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,800 [model] Got input parameters: {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5157226275898305, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,800 [classy] Got parameters {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,800 [classy] Computing new state
 2023-07-02 10:34:20,800 [classy] Setting parameters: {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62888503452058}
 2023-07-02 10:34:20,846 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00810553
 2023-07-02 10:34:20,848 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5157226275898305, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,848 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,868 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.53588
 2023-07-02 10:34:20,868 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,868 [mcmc] New sample, #595:
   Omega_m:0.2997242, b1:0.5182346
 2023-07-02 10:34:20,868 [model] Posterior to be computed for parameters {'Omega_m': 0.3012898083111917, 'b1': 0.5539329096874281}
 2023-07-02 10:34:20,868 [prior] Evaluating prior at array([0.30128981, 0.55393291])
 2023-07-02 10:34:20,868 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,868 [model] Got input parameters: {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5539329096874281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,868 [classy] Got parameters {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,868 [classy] Re-using computed results
 2023-07-02 10:34:20,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62888503452058}
 2023-07-02 10:34:20,868 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,868 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5539329096874281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,868 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,887 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.476751
 2023-07-02 10:34:20,887 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,888 [model] Posterior to be computed for parameters {'Omega_m': 0.30051780299900904, 'b1': 0.5169613040257611}
 2023-07-02 10:34:20,888 [prior] Evaluating prior at array([0.3005178, 0.5169613])
 2023-07-02 10:34:20,888 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,888 [model] Got input parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5169613040257611, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,888 [classy] Got parameters {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,888 [classy] Computing new state
 2023-07-02 10:34:20,888 [classy] Setting parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:20,934 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72491798214503}
 2023-07-02 10:34:20,934 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:20,936 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00925082
 2023-07-02 10:34:20,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5169613040257611, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,936 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,955 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39223
 2023-07-02 10:34:20,955 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,955 [mcmc] New sample, #596:
   Omega_m:0.3012898, b1:0.5157226
 2023-07-02 10:34:20,955 [model] Posterior to be computed for parameters {'Omega_m': 0.30051780299900904, 'b1': 0.6407225465572772}
 2023-07-02 10:34:20,956 [prior] Evaluating prior at array([0.3005178 , 0.64072255])
 2023-07-02 10:34:20,956 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,956 [model] Got input parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6407225465572772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,956 [classy] Got parameters {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,956 [classy] Re-using computed results
 2023-07-02 10:34:20,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72491798214503}
 2023-07-02 10:34:20,956 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:20,956 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6407225465572772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,956 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:20,975 [fs_likelihood.fslikelihood] Computed log-likelihood = -37.0099
 2023-07-02 10:34:20,975 [model] Computed derived parameters: {}
 2023-07-02 10:34:20,976 [model] Posterior to be computed for parameters {'Omega_m': 0.282812065443168, 'b1': 0.5453700203196771}
 2023-07-02 10:34:20,976 [prior] Evaluating prior at array([0.28281207, 0.54537002])
 2023-07-02 10:34:20,976 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:20,976 [model] Got input parameters: {'Omega_m': 0.282812065443168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5453700203196771, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:20,976 [classy] Got parameters {'Omega_m': 0.282812065443168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:20,976 [classy] Computing new state
 2023-07-02 10:34:20,976 [classy] Setting parameters: {'Omega_m': 0.282812065443168, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.98882709049585}
 2023-07-02 10:34:21,022 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0584548
 2023-07-02 10:34:21,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5453700203196771, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,024 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,043 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.28221
 2023-07-02 10:34:21,044 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,044 [model] Posterior to be computed for parameters {'Omega_m': 0.30051780299900904, 'b1': 0.4935704175545021}
 2023-07-02 10:34:21,044 [prior] Evaluating prior at array([0.3005178 , 0.49357042])
 2023-07-02 10:34:21,044 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,044 [model] Got input parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935704175545021, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,044 [classy] Got parameters {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,044 [classy] Re-using computed results
 2023-07-02 10:34:21,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72491798214503}
 2023-07-02 10:34:21,044 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935704175545021, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,044 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,064 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.1728
 2023-07-02 10:34:21,064 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,064 [mcmc] New sample, #597:
   Omega_m:0.3005178, b1:0.5169613
 2023-07-02 10:34:21,064 [model] Posterior to be computed for parameters {'Omega_m': 0.3146345604643631, 'b1': 0.4709201915157138}
 2023-07-02 10:34:21,064 [prior] Evaluating prior at array([0.31463456, 0.47092019])
 2023-07-02 10:34:21,064 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,064 [model] Got input parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4709201915157138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,064 [classy] Got parameters {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,064 [classy] Computing new state
 2023-07-02 10:34:21,064 [classy] Setting parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,110 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00212601290167}
 2023-07-02 10:34:21,110 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,112 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000484585
 2023-07-02 10:34:21,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4709201915157138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,112 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,133 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.557505
 2023-07-02 10:34:21,134 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,134 [mcmc] New sample, #598:
   Omega_m:0.3005178, b1:0.4935704
 2023-07-02 10:34:21,134 [model] Posterior to be computed for parameters {'Omega_m': 0.3146345604643631, 'b1': 0.4520860352771344}
 2023-07-02 10:34:21,134 [prior] Evaluating prior at array([0.31463456, 0.45208604])
 2023-07-02 10:34:21,134 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,134 [model] Got input parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4520860352771344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,134 [classy] Got parameters {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,134 [classy] Re-using computed results
 2023-07-02 10:34:21,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00212601290167}
 2023-07-02 10:34:21,134 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4520860352771344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,134 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,154 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21501
 2023-07-02 10:34:21,154 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,154 [model] Posterior to be computed for parameters {'Omega_m': 0.28950977016319035, 'b1': 0.5112327194383182}
 2023-07-02 10:34:21,154 [prior] Evaluating prior at array([0.28950977, 0.51123272])
 2023-07-02 10:34:21,154 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,154 [model] Got input parameters: {'Omega_m': 0.28950977016319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112327194383182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,154 [classy] Got parameters {'Omega_m': 0.28950977016319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,154 [classy] Computing new state
 2023-07-02 10:34:21,154 [classy] Setting parameters: {'Omega_m': 0.28950977016319035, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.11835326864957}
 2023-07-02 10:34:21,200 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0345168
 2023-07-02 10:34:21,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112327194383182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,202 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,222 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.37288
 2023-07-02 10:34:21,222 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,223 [model] Posterior to be computed for parameters {'Omega_m': 0.3146345604643631, 'b1': 0.4738382967158556}
 2023-07-02 10:34:21,223 [prior] Evaluating prior at array([0.31463456, 0.4738383 ])
 2023-07-02 10:34:21,223 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,223 [model] Got input parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4738382967158556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,223 [classy] Got parameters {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,223 [classy] Re-using computed results
 2023-07-02 10:34:21,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00212601290167}
 2023-07-02 10:34:21,223 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4738382967158556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,223 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.988703
 2023-07-02 10:34:21,243 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,243 [mcmc] New sample, #599:
   Omega_m:0.3146346, b1:0.4709202
 2023-07-02 10:34:21,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.4764683309279262}
 2023-07-02 10:34:21,243 [prior] Evaluating prior at array([0.31299539, 0.47646833])
 2023-07-02 10:34:21,243 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,243 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4764683309279262, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,243 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,243 [classy] Computing new state
 2023-07-02 10:34:21,243 [classy] Setting parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,289 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
 2023-07-02 10:34:21,290 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,291 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0002184
 2023-07-02 10:34:21,291 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4764683309279262, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,291 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,311 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.917192
 2023-07-02 10:34:21,311 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,311 [mcmc] New sample, #600:
   Omega_m:0.3146346, b1:0.4738383
 2023-07-02 10:34:21,311 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.45650799551065896}
 2023-07-02 10:34:21,311 [prior] Evaluating prior at array([0.31299539, 0.456508  ])
 2023-07-02 10:34:21,311 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,311 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45650799551065896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,311 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,311 [classy] Re-using computed results
 2023-07-02 10:34:21,311 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
 2023-07-02 10:34:21,311 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45650799551065896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,312 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.88278
 2023-07-02 10:34:21,332 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,332 [model] Posterior to be computed for parameters {'Omega_m': 0.28803829013921967, 'b1': 0.5165118027339112}
 2023-07-02 10:34:21,332 [prior] Evaluating prior at array([0.28803829, 0.5165118 ])
 2023-07-02 10:34:21,332 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,332 [model] Got input parameters: {'Omega_m': 0.28803829013921967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5165118027339112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,332 [classy] Got parameters {'Omega_m': 0.28803829013921967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,332 [classy] Computing new state
 2023-07-02 10:34:21,332 [classy] Setting parameters: {'Omega_m': 0.28803829013921967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3080849802368}
 2023-07-02 10:34:21,380 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,382 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0392022
 2023-07-02 10:34:21,382 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5165118027339112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,382 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,402 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.43915
 2023-07-02 10:34:21,402 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,402 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.4851893495344608}
 2023-07-02 10:34:21,402 [prior] Evaluating prior at array([0.31299539, 0.48518935])
 2023-07-02 10:34:21,402 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,402 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4851893495344608, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,402 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,402 [classy] Re-using computed results
 2023-07-02 10:34:21,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
 2023-07-02 10:34:21,402 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,402 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4851893495344608, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,402 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,423 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.96626
 2023-07-02 10:34:21,423 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,423 [mcmc] New sample, #601:
   Omega_m:0.3129954, b1:0.4764683
 2023-07-02 10:34:21,423 [model] Posterior to be computed for parameters {'Omega_m': 0.29513159474025175, 'b1': 0.5138516700406757}
 2023-07-02 10:34:21,423 [prior] Evaluating prior at array([0.29513159, 0.51385167])
 2023-07-02 10:34:21,423 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,423 [model] Got input parameters: {'Omega_m': 0.29513159474025175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5138516700406757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,423 [classy] Got parameters {'Omega_m': 0.29513159474025175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,423 [classy] Computing new state
 2023-07-02 10:34:21,423 [classy] Setting parameters: {'Omega_m': 0.29513159474025175, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,470 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4010817908082}
 2023-07-02 10:34:21,470 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,472 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0194955
 2023-07-02 10:34:21,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5138516700406757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,472 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,491 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.849759
 2023-07-02 10:34:21,491 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,491 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.4842399143259211}
 2023-07-02 10:34:21,491 [prior] Evaluating prior at array([0.31299539, 0.48423991])
 2023-07-02 10:34:21,492 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,492 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4842399143259211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,492 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,492 [classy] Re-using computed results
 2023-07-02 10:34:21,492 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
 2023-07-02 10:34:21,492 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4842399143259211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,492 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,512 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87061
 2023-07-02 10:34:21,512 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,512 [mcmc] New sample, #602:
   Omega_m:0.3129954, b1:0.4851893
 2023-07-02 10:34:21,512 [model] Posterior to be computed for parameters {'Omega_m': 0.32788641949432357, 'b1': 0.460347376794698}
 2023-07-02 10:34:21,512 [prior] Evaluating prior at array([0.32788642, 0.46034738])
 2023-07-02 10:34:21,512 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,512 [model] Got input parameters: {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.460347376794698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,512 [classy] Got parameters {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,512 [classy] Computing new state
 2023-07-02 10:34:21,512 [classy] Setting parameters: {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.44632177313633}
 2023-07-02 10:34:21,559 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,561 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0142106
 2023-07-02 10:34:21,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.460347376794698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,561 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,583 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32627
 2023-07-02 10:34:21,583 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,584 [mcmc] New sample, #603:
   Omega_m:0.3129954, b1:0.4842399
 2023-07-02 10:34:21,584 [model] Posterior to be computed for parameters {'Omega_m': 0.32788641949432357, 'b1': 0.47677877934968327}
 2023-07-02 10:34:21,584 [prior] Evaluating prior at array([0.32788642, 0.47677878])
 2023-07-02 10:34:21,584 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,584 [model] Got input parameters: {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47677877934968327, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,584 [classy] Got parameters {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,584 [classy] Re-using computed results
 2023-07-02 10:34:21,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.44632177313633}
 2023-07-02 10:34:21,584 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47677877934968327, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,584 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,604 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0679
 2023-07-02 10:34:21,604 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,604 [mcmc] New sample, #604:
   Omega_m:0.3278864, b1:0.4603474
 2023-07-02 10:34:21,604 [model] Posterior to be computed for parameters {'Omega_m': 0.31574844823166354, 'b1': 0.49625405852950244}
 2023-07-02 10:34:21,604 [prior] Evaluating prior at array([0.31574845, 0.49625406])
 2023-07-02 10:34:21,604 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,604 [model] Got input parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49625405852950244, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,604 [classy] Got parameters {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,604 [classy] Computing new state
 2023-07-02 10:34:21,604 [classy] Setting parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.86912751611536}
 2023-07-02 10:34:21,651 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000850658
 2023-07-02 10:34:21,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49625405852950244, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,653 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,673 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90487
 2023-07-02 10:34:21,673 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,673 [mcmc] New sample, #605:
   Omega_m:0.3278864, b1:0.4767788
 2023-07-02 10:34:21,673 [model] Posterior to be computed for parameters {'Omega_m': 0.31574844823166354, 'b1': 0.49301025299765733}
 2023-07-02 10:34:21,673 [prior] Evaluating prior at array([0.31574845, 0.49301025])
 2023-07-02 10:34:21,674 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,674 [model] Got input parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49301025299765733, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,674 [classy] Got parameters {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,674 [classy] Re-using computed results
 2023-07-02 10:34:21,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.86912751611536}
 2023-07-02 10:34:21,674 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,674 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49301025299765733, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,674 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,693 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82913
 2023-07-02 10:34:21,693 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,693 [mcmc] New sample, #606:
   Omega_m:0.3157484, b1:0.4962541
 2023-07-02 10:34:21,693 [model] Posterior to be computed for parameters {'Omega_m': 0.29222157278473726, 'b1': 0.5307589391366052}
 2023-07-02 10:34:21,693 [prior] Evaluating prior at array([0.29222157, 0.53075894])
 2023-07-02 10:34:21,693 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,694 [model] Got input parameters: {'Omega_m': 0.29222157278473726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5307589391366052, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,694 [classy] Got parameters {'Omega_m': 0.29222157278473726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,694 [classy] Computing new state
 2023-07-02 10:34:21,694 [classy] Setting parameters: {'Omega_m': 0.29222157278473726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,740 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7708692822892}
 2023-07-02 10:34:21,740 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,742 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0267073
 2023-07-02 10:34:21,742 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5307589391366052, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,742 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,761 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.651519
 2023-07-02 10:34:21,761 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,762 [model] Posterior to be computed for parameters {'Omega_m': 0.31574844823166354, 'b1': 0.47699224447515953}
 2023-07-02 10:34:21,762 [prior] Evaluating prior at array([0.31574845, 0.47699224])
 2023-07-02 10:34:21,762 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,762 [model] Got input parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47699224447515953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,762 [classy] Got parameters {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,762 [classy] Re-using computed results
 2023-07-02 10:34:21,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.86912751611536}
 2023-07-02 10:34:21,762 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,762 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47699224447515953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,762 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,782 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64814
 2023-07-02 10:34:21,782 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,782 [model] Posterior to be computed for parameters {'Omega_m': 0.3380993439858989, 'b1': 0.4571484170027206}
 2023-07-02 10:34:21,782 [prior] Evaluating prior at array([0.33809934, 0.45714842])
 2023-07-02 10:34:21,782 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,782 [model] Got input parameters: {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4571484170027206, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,782 [classy] Got parameters {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,782 [classy] Computing new state
 2023-07-02 10:34:21,782 [classy] Setting parameters: {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28543484954614}
 2023-07-02 10:34:21,829 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0380097
 2023-07-02 10:34:21,831 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4571484170027206, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,831 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,850 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.244033
 2023-07-02 10:34:21,850 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,850 [mcmc] New sample, #607:
   Omega_m:0.3157484, b1:0.4930103
 2023-07-02 10:34:21,850 [model] Posterior to be computed for parameters {'Omega_m': 0.3380993439858989, 'b1': 0.41367130281924835}
 2023-07-02 10:34:21,850 [prior] Evaluating prior at array([0.33809934, 0.4136713 ])
 2023-07-02 10:34:21,850 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,850 [model] Got input parameters: {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41367130281924835, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,850 [classy] Got parameters {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,850 [classy] Re-using computed results
 2023-07-02 10:34:21,850 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28543484954614}
 2023-07-02 10:34:21,850 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,850 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41367130281924835, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,851 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,870 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.03428
 2023-07-02 10:34:21,870 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,870 [model] Posterior to be computed for parameters {'Omega_m': 0.3391002618085866, 'b1': 0.45554245224872036}
 2023-07-02 10:34:21,870 [prior] Evaluating prior at array([0.33910026, 0.45554245])
 2023-07-02 10:34:21,870 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,870 [model] Got input parameters: {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45554245224872036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,870 [classy] Got parameters {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,870 [classy] Computing new state
 2023-07-02 10:34:21,870 [classy] Setting parameters: {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:21,916 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.17337440615444}
 2023-07-02 10:34:21,916 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:21,918 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0409255
 2023-07-02 10:34:21,918 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45554245224872036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,918 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,938 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.018712
 2023-07-02 10:34:21,938 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,938 [mcmc] New sample, #608:
   Omega_m:0.3380993, b1:0.4571484
 2023-07-02 10:34:21,938 [model] Posterior to be computed for parameters {'Omega_m': 0.3391002618085866, 'b1': 0.5070018450731213}
 2023-07-02 10:34:21,938 [prior] Evaluating prior at array([0.33910026, 0.50700185])
 2023-07-02 10:34:21,938 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,938 [model] Got input parameters: {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070018450731213, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,938 [classy] Got parameters {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,938 [classy] Re-using computed results
 2023-07-02 10:34:21,938 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.17337440615444}
 2023-07-02 10:34:21,939 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:21,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070018450731213, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,939 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:21,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.30346
 2023-07-02 10:34:21,958 [model] Computed derived parameters: {}
 2023-07-02 10:34:21,958 [model] Posterior to be computed for parameters {'Omega_m': 0.32778744649878994, 'b1': 0.47369377520874356}
 2023-07-02 10:34:21,958 [prior] Evaluating prior at array([0.32778745, 0.47369378])
 2023-07-02 10:34:21,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:21,958 [model] Got input parameters: {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47369377520874356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:21,958 [classy] Got parameters {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:21,958 [classy] Computing new state
 2023-07-02 10:34:21,958 [classy] Setting parameters: {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4577324028305}
 2023-07-02 10:34:22,004 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0140344
 2023-07-02 10:34:22,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47369377520874356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,006 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,029 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0484
 2023-07-02 10:34:22,029 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,029 [mcmc] New sample, #609:
   Omega_m:0.3391003, b1:0.4555425
 2023-07-02 10:34:22,029 [model] Posterior to be computed for parameters {'Omega_m': 0.32778744649878994, 'b1': 0.5263300507147055}
 2023-07-02 10:34:22,029 [prior] Evaluating prior at array([0.32778745, 0.52633005])
 2023-07-02 10:34:22,029 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,029 [model] Got input parameters: {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5263300507147055, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,029 [classy] Got parameters {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,029 [classy] Re-using computed results
 2023-07-02 10:34:22,030 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4577324028305}
 2023-07-02 10:34:22,030 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,030 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5263300507147055, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,030 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,049 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.84752
 2023-07-02 10:34:22,049 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,049 [model] Posterior to be computed for parameters {'Omega_m': 0.32906145800181924, 'b1': 0.47164963379805125}
 2023-07-02 10:34:22,049 [prior] Evaluating prior at array([0.32906146, 0.47164963])
 2023-07-02 10:34:22,049 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,049 [model] Got input parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47164963379805125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,050 [classy] Got parameters {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,050 [classy] Computing new state
 2023-07-02 10:34:22,050 [classy] Setting parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31109464996186}
 2023-07-02 10:34:22,096 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163839
 2023-07-02 10:34:22,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47164963379805125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,098 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8789
 2023-07-02 10:34:22,117 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,117 [mcmc] New sample, #610:
   Omega_m:0.3277874, b1:0.4736938
 2023-07-02 10:34:22,118 [model] Posterior to be computed for parameters {'Omega_m': 0.32906145800181924, 'b1': 0.45676367770691684}
 2023-07-02 10:34:22,118 [prior] Evaluating prior at array([0.32906146, 0.45676368])
 2023-07-02 10:34:22,118 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,118 [model] Got input parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45676367770691684, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,118 [classy] Got parameters {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,118 [classy] Re-using computed results
 2023-07-02 10:34:22,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31109464996186}
 2023-07-02 10:34:22,118 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45676367770691684, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,118 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.02988
 2023-07-02 10:34:22,140 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,140 [mcmc] New sample, #611:
   Omega_m:0.3290615, b1:0.4716496
 2023-07-02 10:34:22,140 [model] Posterior to be computed for parameters {'Omega_m': 0.3859305644671005, 'b1': 0.36551764481134263}
 2023-07-02 10:34:22,140 [prior] Evaluating prior at array([0.38593056, 0.36551764])
 2023-07-02 10:34:22,140 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,140 [model] Got input parameters: {'Omega_m': 0.3859305644671005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.36551764481134263, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,140 [classy] Got parameters {'Omega_m': 0.3859305644671005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,140 [classy] Computing new state
 2023-07-02 10:34:22,141 [classy] Setting parameters: {'Omega_m': 0.3859305644671005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.2436217381763}
 2023-07-02 10:34:22,187 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.279005
 2023-07-02 10:34:22,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.36551764481134263, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,188 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,208 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.0436
 2023-07-02 10:34:22,208 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32906145800181924, 'b1': 0.4806656021888392}
 2023-07-02 10:34:22,208 [prior] Evaluating prior at array([0.32906146, 0.4806656 ])
 2023-07-02 10:34:22,208 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,208 [model] Got input parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4806656021888392, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,208 [classy] Got parameters {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,208 [classy] Re-using computed results
 2023-07-02 10:34:22,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31109464996186}
 2023-07-02 10:34:22,208 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4806656021888392, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,208 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,228 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81387
 2023-07-02 10:34:22,228 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,228 [mcmc] New sample, #612:
   Omega_m:0.3290615, b1:0.4567637
 2023-07-02 10:34:22,229 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.4907501811497614}
 2023-07-02 10:34:22,229 [prior] Evaluating prior at array([0.32277624, 0.49075018])
 2023-07-02 10:34:22,229 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,229 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4907501811497614, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,229 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,229 [classy] Computing new state
 2023-07-02 10:34:22,229 [classy] Setting parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,275 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
 2023-07-02 10:34:22,275 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,277 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00653498
 2023-07-02 10:34:22,277 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4907501811497614, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,277 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,296 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55796
 2023-07-02 10:34:22,297 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,297 [mcmc] New sample, #613:
   Omega_m:0.3290615, b1:0.4806656
 2023-07-02 10:34:22,297 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.5229620379470178}
 2023-07-02 10:34:22,297 [prior] Evaluating prior at array([0.32277624, 0.52296204])
 2023-07-02 10:34:22,297 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,297 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5229620379470178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,297 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,297 [classy] Re-using computed results
 2023-07-02 10:34:22,297 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
 2023-07-02 10:34:22,297 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,297 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5229620379470178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,297 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,316 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.1861
 2023-07-02 10:34:22,316 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,317 [model] Posterior to be computed for parameters {'Omega_m': 0.3333211968454511, 'b1': 0.4738308848034012}
 2023-07-02 10:34:22,317 [prior] Evaluating prior at array([0.3333212 , 0.47383088])
 2023-07-02 10:34:22,317 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,317 [model] Got input parameters: {'Omega_m': 0.3333211968454511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4738308848034012, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,317 [classy] Got parameters {'Omega_m': 0.3333211968454511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,317 [classy] Computing new state
 2023-07-02 10:34:22,317 [classy] Setting parameters: {'Omega_m': 0.3333211968454511, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,363 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.82455330259165}
 2023-07-02 10:34:22,363 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,365 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.025507
 2023-07-02 10:34:22,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4738308848034012, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,365 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,385 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09188
 2023-07-02 10:34:22,385 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,385 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.5415457835982515}
 2023-07-02 10:34:22,385 [prior] Evaluating prior at array([0.32277624, 0.54154578])
 2023-07-02 10:34:22,385 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,385 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5415457835982515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,385 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,385 [classy] Re-using computed results
 2023-07-02 10:34:22,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
 2023-07-02 10:34:22,385 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,385 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5415457835982515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,385 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,405 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.1652
 2023-07-02 10:34:22,405 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,405 [model] Posterior to be computed for parameters {'Omega_m': 0.36248923502888203, 'b1': 0.4270309975357941}
 2023-07-02 10:34:22,405 [prior] Evaluating prior at array([0.36248924, 0.427031  ])
 2023-07-02 10:34:22,405 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,405 [model] Got input parameters: {'Omega_m': 0.36248923502888203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4270309975357941, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,405 [classy] Got parameters {'Omega_m': 0.36248923502888203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,405 [classy] Computing new state
 2023-07-02 10:34:22,405 [classy] Setting parameters: {'Omega_m': 0.36248923502888203, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.63742665151466}
 2023-07-02 10:34:22,452 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.13636
 2023-07-02 10:34:22,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4270309975357941, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,454 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,473 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.78423
 2023-07-02 10:34:22,473 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,473 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.4669750119713177}
 2023-07-02 10:34:22,473 [prior] Evaluating prior at array([0.32277624, 0.46697501])
 2023-07-02 10:34:22,474 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,474 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4669750119713177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,474 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,474 [classy] Re-using computed results
 2023-07-02 10:34:22,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
 2023-07-02 10:34:22,474 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4669750119713177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,474 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,493 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62535
 2023-07-02 10:34:22,493 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,494 [model] Posterior to be computed for parameters {'Omega_m': 0.3799945227144013, 'b1': 0.39894390147820913}
 2023-07-02 10:34:22,494 [prior] Evaluating prior at array([0.37999452, 0.3989439 ])
 2023-07-02 10:34:22,494 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,494 [model] Got input parameters: {'Omega_m': 0.3799945227144013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39894390147820913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,494 [classy] Got parameters {'Omega_m': 0.3799945227144013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,494 [classy] Computing new state
 2023-07-02 10:34:22,494 [classy] Setting parameters: {'Omega_m': 0.3799945227144013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,540 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.83665481161862}
 2023-07-02 10:34:22,540 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,542 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.238847
 2023-07-02 10:34:22,542 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39894390147820913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,542 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,561 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.6375
 2023-07-02 10:34:22,561 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,562 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.5095475538057875}
 2023-07-02 10:34:22,562 [prior] Evaluating prior at array([0.32277624, 0.50954755])
 2023-07-02 10:34:22,562 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,562 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5095475538057875, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,562 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,562 [classy] Re-using computed results
 2023-07-02 10:34:22,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
 2023-07-02 10:34:22,562 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,562 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5095475538057875, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,562 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,581 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10311
 2023-07-02 10:34:22,581 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,582 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5169780724528258}
 2023-07-02 10:34:22,582 [prior] Evaluating prior at array([0.3064297 , 0.51697807])
 2023-07-02 10:34:22,582 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,582 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5169780724528258, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,582 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,582 [classy] Computing new state
 2023-07-02 10:34:22,582 [classy] Setting parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
 2023-07-02 10:34:22,628 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00248452
 2023-07-02 10:34:22,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5169780724528258, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,630 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47582
 2023-07-02 10:34:22,650 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,650 [mcmc] New sample, #614:
   Omega_m:0.3227762, b1:0.4907502
 2023-07-02 10:34:22,650 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5188153296267065}
 2023-07-02 10:34:22,650 [prior] Evaluating prior at array([0.3064297 , 0.51881533])
 2023-07-02 10:34:22,650 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,651 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5188153296267065, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,651 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,651 [classy] Re-using computed results
 2023-07-02 10:34:22,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
 2023-07-02 10:34:22,651 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,651 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5188153296267065, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,651 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,670 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45626
 2023-07-02 10:34:22,670 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,670 [mcmc] New sample, #615:
   Omega_m:0.3064297, b1:0.5169781
 2023-07-02 10:34:22,670 [model] Posterior to be computed for parameters {'Omega_m': 0.2828969328262557, 'b1': 0.5565734759874011}
 2023-07-02 10:34:22,670 [prior] Evaluating prior at array([0.28289693, 0.55657348])
 2023-07-02 10:34:22,671 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,671 [model] Got input parameters: {'Omega_m': 0.2828969328262557, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5565734759874011, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,671 [classy] Got parameters {'Omega_m': 0.2828969328262557, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,671 [classy] Computing new state
 2023-07-02 10:34:22,671 [classy] Setting parameters: {'Omega_m': 0.2828969328262557, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,716 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.9776866336281}
 2023-07-02 10:34:22,717 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,718 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.058109
 2023-07-02 10:34:22,718 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5565734759874011, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,718 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,738 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.79764
 2023-07-02 10:34:22,738 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,738 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5084628442515837}
 2023-07-02 10:34:22,738 [prior] Evaluating prior at array([0.3064297 , 0.50846284])
 2023-07-02 10:34:22,739 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,739 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5084628442515837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,739 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,739 [classy] Re-using computed results
 2023-07-02 10:34:22,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
 2023-07-02 10:34:22,739 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,739 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5084628442515837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,739 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,758 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33163
 2023-07-02 10:34:22,758 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,758 [mcmc] New sample, #616:
   Omega_m:0.3064297, b1:0.5188153
 2023-07-02 10:34:22,758 [model] Posterior to be computed for parameters {'Omega_m': 0.2720418676786235, 'b1': 0.5636378570465901}
 2023-07-02 10:34:22,759 [prior] Evaluating prior at array([0.27204187, 0.56363786])
 2023-07-02 10:34:22,759 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,759 [model] Got input parameters: {'Omega_m': 0.2720418676786235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5636378570465901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,759 [classy] Got parameters {'Omega_m': 0.2720418676786235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,759 [classy] Computing new state
 2023-07-02 10:34:22,759 [classy] Setting parameters: {'Omega_m': 0.2720418676786235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.42639930439992}
 2023-07-02 10:34:22,805 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,807 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111572
 2023-07-02 10:34:22,807 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5636378570465901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,807 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,827 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.1409
 2023-07-02 10:34:22,827 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,827 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5085546523174836}
 2023-07-02 10:34:22,827 [prior] Evaluating prior at array([0.3064297 , 0.50855465])
 2023-07-02 10:34:22,827 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,827 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5085546523174836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,827 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,827 [classy] Re-using computed results
 2023-07-02 10:34:22,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
 2023-07-02 10:34:22,827 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5085546523174836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,827 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,847 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33523
 2023-07-02 10:34:22,847 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,847 [mcmc] New sample, #617:
   Omega_m:0.3064297, b1:0.5084628
 2023-07-02 10:34:22,847 [model] Posterior to be computed for parameters {'Omega_m': 0.30397454625323694, 'b1': 0.5124939341371525}
 2023-07-02 10:34:22,847 [prior] Evaluating prior at array([0.30397455, 0.51249393])
 2023-07-02 10:34:22,847 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,847 [model] Got input parameters: {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5124939341371525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,847 [classy] Got parameters {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,847 [classy] Computing new state
 2023-07-02 10:34:22,847 [classy] Setting parameters: {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2965890103057}
 2023-07-02 10:34:22,894 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0047385
 2023-07-02 10:34:22,896 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5124939341371525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,896 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,915 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02097
 2023-07-02 10:34:22,915 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,915 [mcmc] New sample, #618:
   Omega_m:0.3064297, b1:0.5085547
 2023-07-02 10:34:22,915 [model] Posterior to be computed for parameters {'Omega_m': 0.30397454625323694, 'b1': 0.5512513758955078}
 2023-07-02 10:34:22,915 [prior] Evaluating prior at array([0.30397455, 0.55125138])
 2023-07-02 10:34:22,915 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,915 [model] Got input parameters: {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5512513758955078, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,915 [classy] Got parameters {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,915 [classy] Re-using computed results
 2023-07-02 10:34:22,916 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2965890103057}
 2023-07-02 10:34:22,916 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:22,916 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5512513758955078, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,916 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:22,935 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.436916
 2023-07-02 10:34:22,935 [model] Computed derived parameters: {}
 2023-07-02 10:34:22,935 [mcmc] New sample, #619:
   Omega_m:0.3039745, b1:0.5124939
 2023-07-02 10:34:22,935 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.5524772295517166}
 2023-07-02 10:34:22,935 [prior] Evaluating prior at array([0.30321053, 0.55247723])
 2023-07-02 10:34:22,935 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:22,935 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5524772295517166, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,935 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:22,935 [classy] Computing new state
 2023-07-02 10:34:22,936 [classy] Setting parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:22,982 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
 2023-07-02 10:34:22,982 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:22,984 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00559996
 2023-07-02 10:34:22,984 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5524772295517166, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:22,984 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,003 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.514231
 2023-07-02 10:34:23,004 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,004 [mcmc] New sample, #620:
   Omega_m:0.3039745, b1:0.5512514
 2023-07-02 10:34:23,004 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.5723118045357374}
 2023-07-02 10:34:23,004 [prior] Evaluating prior at array([0.30321053, 0.5723118 ])
 2023-07-02 10:34:23,004 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,004 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5723118045357374, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,004 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,004 [classy] Re-using computed results
 2023-07-02 10:34:23,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
 2023-07-02 10:34:23,004 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,004 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5723118045357374, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,004 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,024 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.08048
 2023-07-02 10:34:23,024 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,024 [model] Posterior to be computed for parameters {'Omega_m': 0.29091300316472607, 'b1': 0.5722085187872962}
 2023-07-02 10:34:23,024 [prior] Evaluating prior at array([0.290913  , 0.57220852])
 2023-07-02 10:34:23,024 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,024 [model] Got input parameters: {'Omega_m': 0.29091300316472607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5722085187872962, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,024 [classy] Got parameters {'Omega_m': 0.29091300316472607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,024 [classy] Computing new state
 2023-07-02 10:34:23,024 [classy] Setting parameters: {'Omega_m': 0.29091300316472607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,070 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.93819892457324}
 2023-07-02 10:34:23,070 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,072 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0303433
 2023-07-02 10:34:23,072 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5722085187872962, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,072 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,092 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.88357
 2023-07-02 10:34:23,093 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,093 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.5696462930821214}
 2023-07-02 10:34:23,093 [prior] Evaluating prior at array([0.30321053, 0.56964629])
 2023-07-02 10:34:23,093 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,093 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5696462930821214, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,093 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,093 [classy] Re-using computed results
 2023-07-02 10:34:23,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
 2023-07-02 10:34:23,093 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5696462930821214, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,093 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,114 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.32874
 2023-07-02 10:34:23,114 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,114 [model] Posterior to be computed for parameters {'Omega_m': 0.2823036358121705, 'b1': 0.5860221808173293}
 2023-07-02 10:34:23,114 [prior] Evaluating prior at array([0.28230364, 0.58602218])
 2023-07-02 10:34:23,114 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,114 [model] Got input parameters: {'Omega_m': 0.2823036358121705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5860221808173293, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,115 [classy] Got parameters {'Omega_m': 0.2823036358121705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,115 [classy] Computing new state
 2023-07-02 10:34:23,115 [classy] Setting parameters: {'Omega_m': 0.2823036358121705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.0556307628839}
 2023-07-02 10:34:23,164 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,166 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0605493
 2023-07-02 10:34:23,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5860221808173293, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,166 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,185 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.91288
 2023-07-02 10:34:23,186 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,186 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.61633662283627}
 2023-07-02 10:34:23,186 [prior] Evaluating prior at array([0.30321053, 0.61633662])
 2023-07-02 10:34:23,186 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,186 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.61633662283627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,186 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,186 [classy] Re-using computed results
 2023-07-02 10:34:23,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
 2023-07-02 10:34:23,186 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.61633662283627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -24.0742
 2023-07-02 10:34:23,205 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,206 [model] Posterior to be computed for parameters {'Omega_m': 0.2827987976343764, 'b1': 0.5852276975780821}
 2023-07-02 10:34:23,206 [prior] Evaluating prior at array([0.2827988, 0.5852277])
 2023-07-02 10:34:23,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,206 [model] Got input parameters: {'Omega_m': 0.2827987976343764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5852276975780821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,206 [classy] Got parameters {'Omega_m': 0.2827987976343764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,206 [classy] Computing new state
 2023-07-02 10:34:23,206 [classy] Setting parameters: {'Omega_m': 0.2827987976343764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.99057018180818}
 2023-07-02 10:34:23,252 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,254 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.058509
 2023-07-02 10:34:23,254 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5852276975780821, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,254 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,273 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.70567
 2023-07-02 10:34:23,274 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,274 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.6015972343661647}
 2023-07-02 10:34:23,274 [prior] Evaluating prior at array([0.30321053, 0.60159723])
 2023-07-02 10:34:23,274 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,274 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6015972343661647, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,274 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,274 [classy] Re-using computed results
 2023-07-02 10:34:23,274 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
 2023-07-02 10:34:23,274 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,274 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6015972343661647, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,274 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,293 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.2939
 2023-07-02 10:34:23,294 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,294 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.5589675661012886}
 2023-07-02 10:34:23,294 [prior] Evaluating prior at array([0.29916543, 0.55896757])
 2023-07-02 10:34:23,294 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,294 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5589675661012886, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,294 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,294 [classy] Computing new state
 2023-07-02 10:34:23,294 [classy] Setting parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,340 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
 2023-07-02 10:34:23,340 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,342 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114507
 2023-07-02 10:34:23,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5589675661012886, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,342 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,361 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.05541
 2023-07-02 10:34:23,361 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,361 [mcmc] New sample, #621:
   Omega_m:0.3032105, b1:0.5524772
 2023-07-02 10:34:23,362 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.5218876467665031}
 2023-07-02 10:34:23,362 [prior] Evaluating prior at array([0.29916543, 0.52188765])
 2023-07-02 10:34:23,362 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,362 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5218876467665031, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,362 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,362 [classy] Re-using computed results
 2023-07-02 10:34:23,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
 2023-07-02 10:34:23,362 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,362 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5218876467665031, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,362 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,381 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24496
 2023-07-02 10:34:23,382 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,382 [mcmc] New sample, #622:
   Omega_m:0.2991654, b1:0.5589676
 2023-07-02 10:34:23,382 [model] Posterior to be computed for parameters {'Omega_m': 0.2762234136268267, 'b1': 0.5586979300347653}
 2023-07-02 10:34:23,382 [prior] Evaluating prior at array([0.27622341, 0.55869793])
 2023-07-02 10:34:23,382 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,382 [model] Got input parameters: {'Omega_m': 0.2762234136268267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5586979300347653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,382 [classy] Got parameters {'Omega_m': 0.2762234136268267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,382 [classy] Computing new state
 2023-07-02 10:34:23,382 [classy] Setting parameters: {'Omega_m': 0.2762234136268267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.86259655193544}
 2023-07-02 10:34:23,428 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0887334
 2023-07-02 10:34:23,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5586979300347653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,430 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,450 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.48428
 2023-07-02 10:34:23,450 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,451 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.4871447661295815}
 2023-07-02 10:34:23,451 [prior] Evaluating prior at array([0.29916543, 0.48714477])
 2023-07-02 10:34:23,451 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,451 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4871447661295815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,451 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,451 [classy] Re-using computed results
 2023-07-02 10:34:23,451 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
 2023-07-02 10:34:23,451 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,451 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4871447661295815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,451 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.09564
 2023-07-02 10:34:23,471 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,471 [model] Posterior to be computed for parameters {'Omega_m': 0.2769523586635247, 'b1': 0.5575283434713081}
 2023-07-02 10:34:23,471 [prior] Evaluating prior at array([0.27695236, 0.55752834])
 2023-07-02 10:34:23,471 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,471 [model] Got input parameters: {'Omega_m': 0.2769523586635247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5575283434713081, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,471 [classy] Got parameters {'Omega_m': 0.2769523586635247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,471 [classy] Computing new state
 2023-07-02 10:34:23,471 [classy] Setting parameters: {'Omega_m': 0.2769523586635247, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,518 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.7650575944623}
 2023-07-02 10:34:23,518 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,519 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0850445
 2023-07-02 10:34:23,519 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5575283434713081, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,520 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,539 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.07438
 2023-07-02 10:34:23,539 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,539 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.520730747909928}
 2023-07-02 10:34:23,539 [prior] Evaluating prior at array([0.29916543, 0.52073075])
 2023-07-02 10:34:23,539 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,539 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520730747909928, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,539 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,539 [classy] Re-using computed results
 2023-07-02 10:34:23,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
 2023-07-02 10:34:23,539 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520730747909928, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,539 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,559 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.19769
 2023-07-02 10:34:23,559 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,559 [mcmc] New sample, #623:
   Omega_m:0.2991654, b1:0.5218876
 2023-07-02 10:34:23,559 [model] Posterior to be computed for parameters {'Omega_m': 0.30475766795410936, 'b1': 0.5117580451102195}
 2023-07-02 10:34:23,559 [prior] Evaluating prior at array([0.30475767, 0.51175805])
 2023-07-02 10:34:23,559 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,559 [model] Got input parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117580451102195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,559 [classy] Got parameters {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,560 [classy] Computing new state
 2023-07-02 10:34:23,560 [classy] Setting parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20014596533642}
 2023-07-02 10:34:23,606 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,608 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00393468
 2023-07-02 10:34:23,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117580451102195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,608 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,627 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15016
 2023-07-02 10:34:23,627 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,627 [mcmc] New sample, #624:
   Omega_m:0.2991654, b1:0.5207307
 2023-07-02 10:34:23,628 [model] Posterior to be computed for parameters {'Omega_m': 0.30475766795410936, 'b1': 0.5317703700182342}
 2023-07-02 10:34:23,628 [prior] Evaluating prior at array([0.30475767, 0.53177037])
 2023-07-02 10:34:23,628 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,628 [model] Got input parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5317703700182342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,628 [classy] Got parameters {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,628 [classy] Re-using computed results
 2023-07-02 10:34:23,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20014596533642}
 2023-07-02 10:34:23,628 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5317703700182342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,628 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,648 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84275
 2023-07-02 10:34:23,648 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,648 [mcmc] New sample, #625:
   Omega_m:0.3047577, b1:0.511758
 2023-07-02 10:34:23,648 [model] Posterior to be computed for parameters {'Omega_m': 0.28966968137688587, 'b1': 0.5559789255086183}
 2023-07-02 10:34:23,648 [prior] Evaluating prior at array([0.28966968, 0.55597893])
 2023-07-02 10:34:23,648 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,648 [model] Got input parameters: {'Omega_m': 0.28966968137688587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5559789255086183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,648 [classy] Got parameters {'Omega_m': 0.28966968137688587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,648 [classy] Computing new state
 2023-07-02 10:34:23,648 [classy] Setting parameters: {'Omega_m': 0.28966968137688587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.09778805534918}
 2023-07-02 10:34:23,695 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0340269
 2023-07-02 10:34:23,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5559789255086183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,697 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,716 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.39721
 2023-07-02 10:34:23,716 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,716 [model] Posterior to be computed for parameters {'Omega_m': 0.30475766795410936, 'b1': 0.5115332617529503}
 2023-07-02 10:34:23,716 [prior] Evaluating prior at array([0.30475767, 0.51153326])
 2023-07-02 10:34:23,716 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,716 [model] Got input parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5115332617529503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,717 [classy] Got parameters {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,717 [classy] Re-using computed results
 2023-07-02 10:34:23,717 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20014596533642}
 2023-07-02 10:34:23,717 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,717 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5115332617529503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,717 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1415
 2023-07-02 10:34:23,736 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,736 [mcmc] New sample, #626:
   Omega_m:0.3047577, b1:0.5317704
 2023-07-02 10:34:23,736 [model] Posterior to be computed for parameters {'Omega_m': 0.32395193384246734, 'b1': 0.4807362134869512}
 2023-07-02 10:34:23,736 [prior] Evaluating prior at array([0.32395193, 0.48073621])
 2023-07-02 10:34:23,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,736 [model] Got input parameters: {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4807362134869512, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,736 [classy] Got parameters {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,736 [classy] Computing new state
 2023-07-02 10:34:23,737 [classy] Setting parameters: {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90229367627933}
 2023-07-02 10:34:23,782 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00804199
 2023-07-02 10:34:23,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4807362134869512, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,784 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,804 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48018
 2023-07-02 10:34:23,804 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,804 [mcmc] New sample, #627:
   Omega_m:0.3047577, b1:0.5115333
 2023-07-02 10:34:23,805 [model] Posterior to be computed for parameters {'Omega_m': 0.32395193384246734, 'b1': 0.48139359166374995}
 2023-07-02 10:34:23,805 [prior] Evaluating prior at array([0.32395193, 0.48139359])
 2023-07-02 10:34:23,805 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,805 [model] Got input parameters: {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48139359166374995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,805 [classy] Got parameters {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,805 [classy] Re-using computed results
 2023-07-02 10:34:23,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90229367627933}
 2023-07-02 10:34:23,805 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,805 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48139359166374995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,805 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,825 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.491
 2023-07-02 10:34:23,825 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,825 [mcmc] New sample, #628:
   Omega_m:0.3239519, b1:0.4807362
 2023-07-02 10:34:23,825 [model] Posterior to be computed for parameters {'Omega_m': 0.30412960243880965, 'b1': 0.5131983660965845}
 2023-07-02 10:34:23,825 [prior] Evaluating prior at array([0.3041296 , 0.51319837])
 2023-07-02 10:34:23,825 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,825 [model] Got input parameters: {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5131983660965845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,825 [classy] Got parameters {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,825 [classy] Computing new state
 2023-07-02 10:34:23,825 [classy] Setting parameters: {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.27747665659018}
 2023-07-02 10:34:23,871 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,873 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.004573
 2023-07-02 10:34:23,873 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5131983660965845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,873 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,892 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08018
 2023-07-02 10:34:23,893 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,893 [mcmc] New sample, #629:
   Omega_m:0.3239519, b1:0.4813936
 2023-07-02 10:34:23,893 [model] Posterior to be computed for parameters {'Omega_m': 0.30412960243880965, 'b1': 0.5080086781054344}
 2023-07-02 10:34:23,893 [prior] Evaluating prior at array([0.3041296 , 0.50800868])
 2023-07-02 10:34:23,893 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,893 [model] Got input parameters: {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080086781054344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,893 [classy] Got parameters {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,893 [classy] Re-using computed results
 2023-07-02 10:34:23,893 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.27747665659018}
 2023-07-02 10:34:23,893 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080086781054344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,893 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,913 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.82142
 2023-07-02 10:34:23,913 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,913 [mcmc] New sample, #630:
   Omega_m:0.3041296, b1:0.5131984
 2023-07-02 10:34:23,913 [model] Posterior to be computed for parameters {'Omega_m': 0.30248727299258243, 'b1': 0.5106437827517032}
 2023-07-02 10:34:23,913 [prior] Evaluating prior at array([0.30248727, 0.51064378])
 2023-07-02 10:34:23,913 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,913 [model] Got input parameters: {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5106437827517032, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,913 [classy] Got parameters {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,913 [classy] Computing new state
 2023-07-02 10:34:23,913 [classy] Setting parameters: {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:23,959 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4803543506021}
 2023-07-02 10:34:23,959 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:23,961 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00648617
 2023-07-02 10:34:23,961 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5106437827517032, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,961 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:23,980 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.56336
 2023-07-02 10:34:23,980 [model] Computed derived parameters: {}
 2023-07-02 10:34:23,980 [mcmc] New sample, #631:
   Omega_m:0.3041296, b1:0.5080087
 2023-07-02 10:34:23,980 [model] Posterior to be computed for parameters {'Omega_m': 0.30248727299258243, 'b1': 0.4791357691439814}
 2023-07-02 10:34:23,980 [prior] Evaluating prior at array([0.30248727, 0.47913577])
 2023-07-02 10:34:23,981 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:23,981 [model] Got input parameters: {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4791357691439814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,981 [classy] Got parameters {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:23,981 [classy] Re-using computed results
 2023-07-02 10:34:23,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4803543506021}
 2023-07-02 10:34:23,981 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:23,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4791357691439814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:23,981 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,000 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.94797
 2023-07-02 10:34:24,000 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,000 [model] Posterior to be computed for parameters {'Omega_m': 0.3288167908076349, 'b1': 0.46839827903267445}
 2023-07-02 10:34:24,000 [prior] Evaluating prior at array([0.32881679, 0.46839828])
 2023-07-02 10:34:24,000 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,000 [model] Got input parameters: {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46839827903267445, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,001 [classy] Got parameters {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,001 [classy] Computing new state
 2023-07-02 10:34:24,001 [classy] Setting parameters: {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.33921777466418}
 2023-07-02 10:34:24,047 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,049 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159189
 2023-07-02 10:34:24,049 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46839827903267445, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,049 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,069 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81256
 2023-07-02 10:34:24,069 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,069 [mcmc] New sample, #632:
   Omega_m:0.3024873, b1:0.5106438
 2023-07-02 10:34:24,069 [model] Posterior to be computed for parameters {'Omega_m': 0.3288167908076349, 'b1': 0.5402921511833714}
 2023-07-02 10:34:24,069 [prior] Evaluating prior at array([0.32881679, 0.54029215])
 2023-07-02 10:34:24,069 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,069 [model] Got input parameters: {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5402921511833714, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,069 [classy] Got parameters {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,069 [classy] Re-using computed results
 2023-07-02 10:34:24,069 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.33921777466418}
 2023-07-02 10:34:24,069 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,069 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5402921511833714, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,069 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,089 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.3676
 2023-07-02 10:34:24,089 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,089 [model] Posterior to be computed for parameters {'Omega_m': 0.3207607547953617, 'b1': 0.48132412529038865}
 2023-07-02 10:34:24,089 [prior] Evaluating prior at array([0.32076075, 0.48132413])
 2023-07-02 10:34:24,089 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,089 [model] Got input parameters: {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48132412529038865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,089 [classy] Got parameters {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,089 [classy] Computing new state
 2023-07-02 10:34:24,089 [classy] Setting parameters: {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.27577440451998}
 2023-07-02 10:34:24,137 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00431783
 2023-07-02 10:34:24,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48132412529038865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,139 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,159 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5591
 2023-07-02 10:34:24,159 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,159 [mcmc] New sample, #633:
   Omega_m:0.3288168, b1:0.4683983
 2023-07-02 10:34:24,159 [model] Posterior to be computed for parameters {'Omega_m': 0.3207607547953617, 'b1': 0.5238641458877586}
 2023-07-02 10:34:24,160 [prior] Evaluating prior at array([0.32076075, 0.52386415])
 2023-07-02 10:34:24,160 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,160 [model] Got input parameters: {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5238641458877586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,160 [classy] Got parameters {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,160 [classy] Re-using computed results
 2023-07-02 10:34:24,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.27577440451998}
 2023-07-02 10:34:24,160 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5238641458877586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,160 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,179 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.479895
 2023-07-02 10:34:24,180 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,180 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.4596949902766368}
 2023-07-02 10:34:24,180 [prior] Evaluating prior at array([0.33424112, 0.45969499])
 2023-07-02 10:34:24,180 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,180 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4596949902766368, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,180 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,180 [classy] Computing new state
 2023-07-02 10:34:24,180 [classy] Setting parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
 2023-07-02 10:34:24,227 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,228 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0277299
 2023-07-02 10:34:24,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4596949902766368, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,228 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,248 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.953271
 2023-07-02 10:34:24,248 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,248 [mcmc] New sample, #634:
   Omega_m:0.3207608, b1:0.4813241
 2023-07-02 10:34:24,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.5180125286952466}
 2023-07-02 10:34:24,248 [prior] Evaluating prior at array([0.33424112, 0.51801253])
 2023-07-02 10:34:24,248 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,248 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5180125286952466, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,248 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,248 [classy] Re-using computed results
 2023-07-02 10:34:24,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
 2023-07-02 10:34:24,248 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,248 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5180125286952466, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,248 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,268 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.93352
 2023-07-02 10:34:24,268 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,268 [model] Posterior to be computed for parameters {'Omega_m': 0.34313262453008814, 'b1': 0.44542863670913946}
 2023-07-02 10:34:24,268 [prior] Evaluating prior at array([0.34313262, 0.44542864])
 2023-07-02 10:34:24,268 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,268 [model] Got input parameters: {'Omega_m': 0.34313262453008814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44542863670913946, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,268 [classy] Got parameters {'Omega_m': 0.34313262453008814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,268 [classy] Computing new state
 2023-07-02 10:34:24,268 [classy] Setting parameters: {'Omega_m': 0.34313262453008814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,314 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.72493596161004}
 2023-07-02 10:34:24,315 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,316 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0536898
 2023-07-02 10:34:24,316 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44542863670913946, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,316 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,336 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.01658
 2023-07-02 10:34:24,336 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,336 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.4815162766483814}
 2023-07-02 10:34:24,336 [prior] Evaluating prior at array([0.33424112, 0.48151628])
 2023-07-02 10:34:24,336 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,336 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4815162766483814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,336 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,336 [classy] Re-using computed results
 2023-07-02 10:34:24,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
 2023-07-02 10:34:24,336 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,336 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4815162766483814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,336 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,356 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.327881
 2023-07-02 10:34:24,356 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,356 [model] Posterior to be computed for parameters {'Omega_m': 0.34763522329684704, 'b1': 0.43820425249205885}
 2023-07-02 10:34:24,356 [prior] Evaluating prior at array([0.34763522, 0.43820425])
 2023-07-02 10:34:24,356 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,356 [model] Got input parameters: {'Omega_m': 0.34763522329684704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43820425249205885, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,356 [classy] Got parameters {'Omega_m': 0.34763522329684704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,357 [classy] Computing new state
 2023-07-02 10:34:24,357 [classy] Setting parameters: {'Omega_m': 0.34763522329684704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.22988539667287}
 2023-07-02 10:34:24,402 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0698216
 2023-07-02 10:34:24,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43820425249205885, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,404 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,424 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.25743
 2023-07-02 10:34:24,424 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,424 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.4588897392813515}
 2023-07-02 10:34:24,425 [prior] Evaluating prior at array([0.33424112, 0.45888974])
 2023-07-02 10:34:24,425 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,425 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4588897392813515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,425 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,425 [classy] Re-using computed results
 2023-07-02 10:34:24,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
 2023-07-02 10:34:24,425 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4588897392813515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,425 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.926198
 2023-07-02 10:34:24,444 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,444 [mcmc] New sample, #635:
   Omega_m:0.3342411, b1:0.459695
 2023-07-02 10:34:24,444 [model] Posterior to be computed for parameters {'Omega_m': 0.36686816203618766, 'b1': 0.4065399029463184}
 2023-07-02 10:34:24,444 [prior] Evaluating prior at array([0.36686816, 0.4065399 ])
 2023-07-02 10:34:24,444 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,444 [model] Got input parameters: {'Omega_m': 0.36686816203618766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4065399029463184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,444 [classy] Got parameters {'Omega_m': 0.36686816203618766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,445 [classy] Computing new state
 2023-07-02 10:34:24,445 [classy] Setting parameters: {'Omega_m': 0.36686816203618766, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.17949725417077}
 2023-07-02 10:34:24,491 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.159662
 2023-07-02 10:34:24,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4065399029463184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,492 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,512 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.12262
 2023-07-02 10:34:24,512 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.44476619380700344}
 2023-07-02 10:34:24,512 [prior] Evaluating prior at array([0.33424112, 0.44476619])
 2023-07-02 10:34:24,513 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,513 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44476619380700344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,513 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,513 [classy] Re-using computed results
 2023-07-02 10:34:24,513 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
 2023-07-02 10:34:24,513 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44476619380700344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,513 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,532 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.1076
 2023-07-02 10:34:24,532 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,532 [mcmc] New sample, #636:
   Omega_m:0.3342411, b1:0.4588897
 2023-07-02 10:34:24,532 [model] Posterior to be computed for parameters {'Omega_m': 0.31676147068122745, 'b1': 0.47281214864646903}
 2023-07-02 10:34:24,532 [prior] Evaluating prior at array([0.31676147, 0.47281215])
 2023-07-02 10:34:24,532 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,532 [model] Got input parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47281214864646903, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,533 [classy] Got parameters {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,533 [classy] Computing new state
 2023-07-02 10:34:24,533 [classy] Setting parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.74853437447192}
 2023-07-02 10:34:24,579 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00131253
 2023-07-02 10:34:24,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47281214864646903, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,581 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,600 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35209
 2023-07-02 10:34:24,600 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,600 [mcmc] New sample, #637:
   Omega_m:0.3342411, b1:0.4447662
 2023-07-02 10:34:24,600 [model] Posterior to be computed for parameters {'Omega_m': 0.31676147068122745, 'b1': 0.4823902058030781}
 2023-07-02 10:34:24,600 [prior] Evaluating prior at array([0.31676147, 0.48239021])
 2023-07-02 10:34:24,600 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,600 [model] Got input parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4823902058030781, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,600 [classy] Got parameters {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,600 [classy] Re-using computed results
 2023-07-02 10:34:24,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.74853437447192}
 2023-07-02 10:34:24,600 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4823902058030781, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,600 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,620 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33331
 2023-07-02 10:34:24,620 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,620 [mcmc] New sample, #638:
   Omega_m:0.3167615, b1:0.4728121
 2023-07-02 10:34:24,620 [model] Posterior to be computed for parameters {'Omega_m': 0.30823459303396417, 'b1': 0.496071513751423}
 2023-07-02 10:34:24,621 [prior] Evaluating prior at array([0.30823459, 0.49607151])
 2023-07-02 10:34:24,621 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,621 [model] Got input parameters: {'Omega_m': 0.30823459303396417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.496071513751423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,621 [classy] Got parameters {'Omega_m': 0.30823459303396417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,621 [classy] Computing new state
 2023-07-02 10:34:24,621 [classy] Setting parameters: {'Omega_m': 0.30823459303396417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77456122260148}
 2023-07-02 10:34:24,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00132158
 2023-07-02 10:34:24,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.496071513751423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,669 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,688 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.92395
 2023-07-02 10:34:24,689 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,689 [model] Posterior to be computed for parameters {'Omega_m': 0.31676147068122745, 'b1': 0.46354884532833285}
 2023-07-02 10:34:24,689 [prior] Evaluating prior at array([0.31676147, 0.46354885])
 2023-07-02 10:34:24,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,689 [model] Got input parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46354884532833285, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,689 [classy] Got parameters {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,689 [classy] Re-using computed results
 2023-07-02 10:34:24,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.74853437447192}
 2023-07-02 10:34:24,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46354884532833285, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0343967
 2023-07-02 10:34:24,708 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,708 [model] Posterior to be computed for parameters {'Omega_m': 0.33367174672391486, 'b1': 0.4552578012345925}
 2023-07-02 10:34:24,708 [prior] Evaluating prior at array([0.33367175, 0.4552578 ])
 2023-07-02 10:34:24,709 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,709 [model] Got input parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4552578012345925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,709 [classy] Got parameters {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,709 [classy] Computing new state
 2023-07-02 10:34:24,709 [classy] Setting parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7847650730614}
 2023-07-02 10:34:24,755 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0263435
 2023-07-02 10:34:24,756 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4552578012345925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,756 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,776 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.807995
 2023-07-02 10:34:24,776 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,776 [mcmc] New sample, #639:
   Omega_m:0.3167615, b1:0.4823902
 2023-07-02 10:34:24,776 [model] Posterior to be computed for parameters {'Omega_m': 0.33367174672391486, 'b1': 0.4005117986214789}
 2023-07-02 10:34:24,776 [prior] Evaluating prior at array([0.33367175, 0.4005118 ])
 2023-07-02 10:34:24,776 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,776 [model] Got input parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4005117986214789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,776 [classy] Got parameters {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,776 [classy] Re-using computed results
 2023-07-02 10:34:24,776 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7847650730614}
 2023-07-02 10:34:24,776 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4005117986214789, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,777 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,796 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.0083
 2023-07-02 10:34:24,796 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,796 [model] Posterior to be computed for parameters {'Omega_m': 0.35352167088856196, 'b1': 0.42340875443432663}
 2023-07-02 10:34:24,796 [prior] Evaluating prior at array([0.35352167, 0.42340875])
 2023-07-02 10:34:24,796 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,796 [model] Got input parameters: {'Omega_m': 0.35352167088856196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42340875443432663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,796 [classy] Got parameters {'Omega_m': 0.35352167088856196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,796 [classy] Computing new state
 2023-07-02 10:34:24,796 [classy] Setting parameters: {'Omega_m': 0.35352167088856196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.59146439464664}
 2023-07-02 10:34:24,842 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,844 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.093804
 2023-07-02 10:34:24,844 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42340875443432663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,844 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,864 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.24282
 2023-07-02 10:34:24,864 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,864 [model] Posterior to be computed for parameters {'Omega_m': 0.33367174672391486, 'b1': 0.46806260222737}
 2023-07-02 10:34:24,864 [prior] Evaluating prior at array([0.33367175, 0.4680626 ])
 2023-07-02 10:34:24,865 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,865 [model] Got input parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46806260222737, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,865 [classy] Got parameters {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,865 [classy] Re-using computed results
 2023-07-02 10:34:24,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7847650730614}
 2023-07-02 10:34:24,865 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46806260222737, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,865 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,884 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14446
 2023-07-02 10:34:24,884 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,884 [mcmc] New sample, #640:
   Omega_m:0.3336717, b1:0.4552578
 2023-07-02 10:34:24,884 [mcmc] Learn + convergence test @ 640 samples accepted.
 2023-07-02 10:34:24,884 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:24,889 [mcmc]  - Acceptance rate: 0.475
 2023-07-02 10:34:24,889 [mcmc]  - Condition number = 18.1812
 2023-07-02 10:34:24,889 [mcmc]  - Eigenvalues = array([0.00466148, 0.08475108])
 2023-07-02 10:34:24,890 [mcmc]  - Convergence of means: R-1 = 0.084751 after 512 accepted steps
 2023-07-02 10:34:24,890 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:24,890 [mcmc] array([[ 0.00010358, -0.00017195],
       [-0.00017195,  0.00046429]])
 2023-07-02 10:34:24,900 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:24,900 [model] Posterior to be computed for parameters {'Omega_m': 0.30453218163579315, 'b1': 0.5164357133108873}
 2023-07-02 10:34:24,900 [prior] Evaluating prior at array([0.30453218, 0.51643571])
 2023-07-02 10:34:24,900 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,900 [model] Got input parameters: {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5164357133108873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,900 [classy] Got parameters {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,900 [classy] Computing new state
 2023-07-02 10:34:24,900 [classy] Setting parameters: {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:24,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22789359814456}
 2023-07-02 10:34:24,948 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:24,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00415795
 2023-07-02 10:34:24,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5164357133108873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,950 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,971 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23585
 2023-07-02 10:34:24,971 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,971 [mcmc] New sample, #641:
   Omega_m:0.3336717, b1:0.4680626
 2023-07-02 10:34:24,971 [model] Posterior to be computed for parameters {'Omega_m': 0.30453218163579315, 'b1': 0.5372895902961363}
 2023-07-02 10:34:24,971 [prior] Evaluating prior at array([0.30453218, 0.53728959])
 2023-07-02 10:34:24,971 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,971 [model] Got input parameters: {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5372895902961363, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,971 [classy] Got parameters {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,971 [classy] Re-using computed results
 2023-07-02 10:34:24,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22789359814456}
 2023-07-02 10:34:24,971 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:24,971 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5372895902961363, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,971 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:24,991 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38521
 2023-07-02 10:34:24,991 [model] Computed derived parameters: {}
 2023-07-02 10:34:24,991 [mcmc] New sample, #642:
   Omega_m:0.3045322, b1:0.5164357
 2023-07-02 10:34:24,991 [model] Posterior to be computed for parameters {'Omega_m': 0.3000674928633739, 'b1': 0.5447011932246099}
 2023-07-02 10:34:24,991 [prior] Evaluating prior at array([0.30006749, 0.54470119])
 2023-07-02 10:34:24,991 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:24,991 [model] Got input parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5447011932246099, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:24,991 [classy] Got parameters {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:24,991 [classy] Computing new state
 2023-07-02 10:34:24,991 [classy] Setting parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78104038734946}
 2023-07-02 10:34:25,038 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00995593
 2023-07-02 10:34:25,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5447011932246099, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,059 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.753538
 2023-07-02 10:34:25,059 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,059 [mcmc] New sample, #643:
   Omega_m:0.3045322, b1:0.5372896
 2023-07-02 10:34:25,059 [model] Posterior to be computed for parameters {'Omega_m': 0.3000674928633739, 'b1': 0.5557023943511958}
 2023-07-02 10:34:25,059 [prior] Evaluating prior at array([0.30006749, 0.55570239])
 2023-07-02 10:34:25,059 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,059 [model] Got input parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5557023943511958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,060 [classy] Got parameters {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,060 [classy] Re-using computed results
 2023-07-02 10:34:25,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78104038734946}
 2023-07-02 10:34:25,060 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5557023943511958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,060 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,079 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.621411
 2023-07-02 10:34:25,079 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,079 [model] Posterior to be computed for parameters {'Omega_m': 0.2831730848475549, 'b1': 0.5727467413708522}
 2023-07-02 10:34:25,080 [prior] Evaluating prior at array([0.28317308, 0.57274674])
 2023-07-02 10:34:25,080 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,080 [model] Got input parameters: {'Omega_m': 0.2831730848475549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5727467413708522, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,080 [classy] Got parameters {'Omega_m': 0.2831730848475549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,080 [classy] Computing new state
 2023-07-02 10:34:25,080 [classy] Setting parameters: {'Omega_m': 0.2831730848475549, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.94145238875436}
 2023-07-02 10:34:25,127 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0569915
 2023-07-02 10:34:25,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5727467413708522, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,128 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,149 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.23534
 2023-07-02 10:34:25,149 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,149 [model] Posterior to be computed for parameters {'Omega_m': 0.3000674928633739, 'b1': 0.5136822893523919}
 2023-07-02 10:34:25,149 [prior] Evaluating prior at array([0.30006749, 0.51368229])
 2023-07-02 10:34:25,149 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,149 [model] Got input parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5136822893523919, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,149 [classy] Got parameters {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,149 [classy] Re-using computed results
 2023-07-02 10:34:25,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78104038734946}
 2023-07-02 10:34:25,149 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5136822893523919, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,149 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05876
 2023-07-02 10:34:25,169 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,169 [mcmc] New sample, #644:
   Omega_m:0.3000675, b1:0.5447012
 2023-07-02 10:34:25,169 [model] Posterior to be computed for parameters {'Omega_m': 0.33629683107478214, 'b1': 0.45353980622050877}
 2023-07-02 10:34:25,169 [prior] Evaluating prior at array([0.33629683, 0.45353981])
 2023-07-02 10:34:25,169 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,169 [model] Got input parameters: {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45353980622050877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,169 [classy] Got parameters {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,169 [classy] Computing new state
 2023-07-02 10:34:25,169 [classy] Setting parameters: {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48799897594725}
 2023-07-02 10:34:25,216 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,217 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0330161
 2023-07-02 10:34:25,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45353980622050877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,218 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,237 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.452087
 2023-07-02 10:34:25,237 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,237 [mcmc] New sample, #645:
   Omega_m:0.3000675, b1:0.5136823
 2023-07-02 10:34:25,238 [model] Posterior to be computed for parameters {'Omega_m': 0.33629683107478214, 'b1': 0.4849462018302281}
 2023-07-02 10:34:25,238 [prior] Evaluating prior at array([0.33629683, 0.4849462 ])
 2023-07-02 10:34:25,238 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,238 [model] Got input parameters: {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4849462018302281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,238 [classy] Got parameters {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,238 [classy] Re-using computed results
 2023-07-02 10:34:25,238 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48799897594725}
 2023-07-02 10:34:25,238 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4849462018302281, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,238 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.874281
 2023-07-02 10:34:25,257 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,257 [model] Posterior to be computed for parameters {'Omega_m': 0.33958092609964635, 'b1': 0.4480880469726901}
 2023-07-02 10:34:25,257 [prior] Evaluating prior at array([0.33958093, 0.44808805])
 2023-07-02 10:34:25,257 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,257 [model] Got input parameters: {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4480880469726901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,258 [classy] Got parameters {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,258 [classy] Computing new state
 2023-07-02 10:34:25,258 [classy] Setting parameters: {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.11966615646188}
 2023-07-02 10:34:25,304 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0423618
 2023-07-02 10:34:25,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4480880469726901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,306 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,326 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.253556
 2023-07-02 10:34:25,326 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,326 [mcmc] New sample, #646:
   Omega_m:0.3362968, b1:0.4535398
 2023-07-02 10:34:25,326 [model] Posterior to be computed for parameters {'Omega_m': 0.33958092609964635, 'b1': 0.4468493555511388}
 2023-07-02 10:34:25,326 [prior] Evaluating prior at array([0.33958093, 0.44684936])
 2023-07-02 10:34:25,326 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,326 [model] Got input parameters: {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4468493555511388, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,326 [classy] Got parameters {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,326 [classy] Re-using computed results
 2023-07-02 10:34:25,326 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.11966615646188}
 2023-07-02 10:34:25,327 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,327 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4468493555511388, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,327 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,346 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.309947
 2023-07-02 10:34:25,346 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,346 [mcmc] New sample, #647:
   Omega_m:0.3395809, b1:0.448088
 2023-07-02 10:34:25,346 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.4889061851246316}
 2023-07-02 10:34:25,346 [prior] Evaluating prior at array([0.31424624, 0.48890619])
 2023-07-02 10:34:25,346 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,346 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4889061851246316, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,346 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,346 [classy] Computing new state
 2023-07-02 10:34:25,346 [classy] Setting parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
 2023-07-02 10:34:25,393 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,395 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000392036
 2023-07-02 10:34:25,395 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4889061851246316, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,395 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,414 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48522
 2023-07-02 10:34:25,414 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,414 [mcmc] New sample, #648:
   Omega_m:0.3395809, b1:0.4468494
 2023-07-02 10:34:25,414 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.5171685871882612}
 2023-07-02 10:34:25,414 [prior] Evaluating prior at array([0.31424624, 0.51716859])
 2023-07-02 10:34:25,414 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,415 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5171685871882612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,415 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,415 [classy] Re-using computed results
 2023-07-02 10:34:25,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
 2023-07-02 10:34:25,415 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5171685871882612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,415 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,435 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26841
 2023-07-02 10:34:25,435 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,435 [mcmc] New sample, #649:
   Omega_m:0.3142462, b1:0.4889062
 2023-07-02 10:34:25,435 [model] Posterior to be computed for parameters {'Omega_m': 0.2952522510530034, 'b1': 0.548699538205581}
 2023-07-02 10:34:25,435 [prior] Evaluating prior at array([0.29525225, 0.54869954])
 2023-07-02 10:34:25,435 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,435 [model] Got input parameters: {'Omega_m': 0.2952522510530034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.548699538205581, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,435 [classy] Got parameters {'Omega_m': 0.2952522510530034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,435 [classy] Computing new state
 2023-07-02 10:34:25,435 [classy] Setting parameters: {'Omega_m': 0.2952522510530034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.38581860890665}
 2023-07-02 10:34:25,482 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0192222
 2023-07-02 10:34:25,484 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.548699538205581, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,484 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,503 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0781293
 2023-07-02 10:34:25,503 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,503 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.5018672050831509}
 2023-07-02 10:34:25,503 [prior] Evaluating prior at array([0.31424624, 0.50186721])
 2023-07-02 10:34:25,503 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,503 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5018672050831509, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,503 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,503 [classy] Re-using computed results
 2023-07-02 10:34:25,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
 2023-07-02 10:34:25,503 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5018672050831509, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,503 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,523 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92163
 2023-07-02 10:34:25,523 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,523 [mcmc] New sample, #650:
   Omega_m:0.3142462, b1:0.5171686
 2023-07-02 10:34:25,523 [model] Posterior to be computed for parameters {'Omega_m': 0.34880705003835855, 'b1': 0.44449455604536725}
 2023-07-02 10:34:25,523 [prior] Evaluating prior at array([0.34880705, 0.44449456])
 2023-07-02 10:34:25,523 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,523 [model] Got input parameters: {'Omega_m': 0.34880705003835855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44449455604536725, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,523 [classy] Got parameters {'Omega_m': 0.34880705003835855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,523 [classy] Computing new state
 2023-07-02 10:34:25,523 [classy] Setting parameters: {'Omega_m': 0.34880705003835855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,569 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.10200856158238}
 2023-07-02 10:34:25,569 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,571 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0743379
 2023-07-02 10:34:25,571 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44449455604536725, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,571 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,591 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.65885
 2023-07-02 10:34:25,591 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,591 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.5456354677866205}
 2023-07-02 10:34:25,591 [prior] Evaluating prior at array([0.31424624, 0.54563547])
 2023-07-02 10:34:25,591 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,591 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5456354677866205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,591 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,591 [classy] Re-using computed results
 2023-07-02 10:34:25,591 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
 2023-07-02 10:34:25,591 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5456354677866205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,591 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,610 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.50731
 2023-07-02 10:34:25,610 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,611 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.5123224612568781}
 2023-07-02 10:34:25,611 [prior] Evaluating prior at array([0.30794808, 0.51232246])
 2023-07-02 10:34:25,611 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,611 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123224612568781, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,611 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,611 [classy] Computing new state
 2023-07-02 10:34:25,611 [classy] Setting parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
 2023-07-02 10:34:25,658 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,660 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00147851
 2023-07-02 10:34:25,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123224612568781, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,660 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,681 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62074
 2023-07-02 10:34:25,681 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,681 [mcmc] New sample, #651:
   Omega_m:0.3142462, b1:0.5018672
 2023-07-02 10:34:25,681 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.4671608381228353}
 2023-07-02 10:34:25,681 [prior] Evaluating prior at array([0.30794808, 0.46716084])
 2023-07-02 10:34:25,681 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,681 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4671608381228353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,681 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,681 [classy] Re-using computed results
 2023-07-02 10:34:25,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
 2023-07-02 10:34:25,681 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4671608381228353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,681 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,701 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.78494
 2023-07-02 10:34:25,701 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,701 [model] Posterior to be computed for parameters {'Omega_m': 0.30382114559235485, 'b1': 0.51917336976061}
 2023-07-02 10:34:25,701 [prior] Evaluating prior at array([0.30382115, 0.51917337])
 2023-07-02 10:34:25,701 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,701 [model] Got input parameters: {'Omega_m': 0.30382114559235485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.51917336976061, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,701 [classy] Got parameters {'Omega_m': 0.30382114559235485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,701 [classy] Computing new state
 2023-07-02 10:34:25,701 [classy] Setting parameters: {'Omega_m': 0.30382114559235485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,749 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3155071779159}
 2023-07-02 10:34:25,749 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,751 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00490534
 2023-07-02 10:34:25,751 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.51917336976061, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,751 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,771 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15839
 2023-07-02 10:34:25,771 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,771 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.5458057948874686}
 2023-07-02 10:34:25,771 [prior] Evaluating prior at array([0.30794808, 0.54580579])
 2023-07-02 10:34:25,771 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,771 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5458057948874686, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,771 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,771 [classy] Re-using computed results
 2023-07-02 10:34:25,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
 2023-07-02 10:34:25,771 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,771 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5458057948874686, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,771 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,791 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.326092
 2023-07-02 10:34:25,791 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,791 [model] Posterior to be computed for parameters {'Omega_m': 0.30566116849497127, 'b1': 0.5161188412528814}
 2023-07-02 10:34:25,791 [prior] Evaluating prior at array([0.30566117, 0.51611884])
 2023-07-02 10:34:25,791 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,791 [model] Got input parameters: {'Omega_m': 0.30566116849497127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5161188412528814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,791 [classy] Got parameters {'Omega_m': 0.30566116849497127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,791 [classy] Computing new state
 2023-07-02 10:34:25,792 [classy] Setting parameters: {'Omega_m': 0.30566116849497127, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.08914655669415}
 2023-07-02 10:34:25,838 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00310624
 2023-07-02 10:34:25,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5161188412528814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,840 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39137
 2023-07-02 10:34:25,861 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,861 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.4644212829912632}
 2023-07-02 10:34:25,861 [prior] Evaluating prior at array([0.30794808, 0.46442128])
 2023-07-02 10:34:25,861 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,861 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4644212829912632, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,861 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,861 [classy] Re-using computed results
 2023-07-02 10:34:25,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
 2023-07-02 10:34:25,861 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,861 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4644212829912632, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,861 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,881 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.43147
 2023-07-02 10:34:25,881 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3081335792428361, 'b1': 0.5120145178222171}
 2023-07-02 10:34:25,882 [prior] Evaluating prior at array([0.30813358, 0.51201452])
 2023-07-02 10:34:25,882 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,882 [model] Got input parameters: {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5120145178222171, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,882 [classy] Got parameters {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,882 [classy] Computing new state
 2023-07-02 10:34:25,882 [classy] Setting parameters: {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:25,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78686425001317}
 2023-07-02 10:34:25,928 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:25,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00137571
 2023-07-02 10:34:25,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5120145178222171, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,930 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,949 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63647
 2023-07-02 10:34:25,949 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,949 [mcmc] New sample, #652:
   Omega_m:0.3079481, b1:0.5123225
 2023-07-02 10:34:25,950 [model] Posterior to be computed for parameters {'Omega_m': 0.3081335792428361, 'b1': 0.4964335927346454}
 2023-07-02 10:34:25,950 [prior] Evaluating prior at array([0.30813358, 0.49643359])
 2023-07-02 10:34:25,950 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,950 [model] Got input parameters: {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4964335927346454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,950 [classy] Got parameters {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,950 [classy] Re-using computed results
 2023-07-02 10:34:25,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78686425001317}
 2023-07-02 10:34:25,950 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:25,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4964335927346454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,950 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:25,969 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.93107
 2023-07-02 10:34:25,969 [model] Computed derived parameters: {}
 2023-07-02 10:34:25,969 [model] Posterior to be computed for parameters {'Omega_m': 0.3159191734807206, 'b1': 0.4990900485042484}
 2023-07-02 10:34:25,969 [prior] Evaluating prior at array([0.31591917, 0.49909005])
 2023-07-02 10:34:25,970 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:25,970 [model] Got input parameters: {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4990900485042484, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:25,970 [classy] Got parameters {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:25,970 [classy] Computing new state
 2023-07-02 10:34:25,970 [classy] Setting parameters: {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84877774018676}
 2023-07-02 10:34:26,016 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000919939
 2023-07-02 10:34:26,018 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4990900485042484, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,018 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,038 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92331
 2023-07-02 10:34:26,038 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,038 [mcmc] New sample, #653:
   Omega_m:0.3081336, b1:0.5120145
 2023-07-02 10:34:26,039 [model] Posterior to be computed for parameters {'Omega_m': 0.3159191734807206, 'b1': 0.40318878978431283}
 2023-07-02 10:34:26,039 [prior] Evaluating prior at array([0.31591917, 0.40318879])
 2023-07-02 10:34:26,039 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,039 [model] Got input parameters: {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40318878978431283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,039 [classy] Got parameters {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,039 [classy] Re-using computed results
 2023-07-02 10:34:26,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84877774018676}
 2023-07-02 10:34:26,039 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40318878978431283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,039 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,058 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.4012
 2023-07-02 10:34:26,058 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,059 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.4886237255738662}
 2023-07-02 10:34:26,059 [prior] Evaluating prior at array([0.322224  , 0.48862373])
 2023-07-02 10:34:26,059 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,059 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4886237255738662, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,059 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,059 [classy] Computing new state
 2023-07-02 10:34:26,059 [classy] Setting parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,105 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,107 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00588131
 2023-07-02 10:34:26,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4886237255738662, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,107 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,127 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65162
 2023-07-02 10:34:26,128 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,128 [mcmc] New sample, #654:
   Omega_m:0.3159192, b1:0.49909
 2023-07-02 10:34:26,128 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.459444787556578}
 2023-07-02 10:34:26,128 [prior] Evaluating prior at array([0.322224  , 0.45944479])
 2023-07-02 10:34:26,128 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,128 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.459444787556578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,128 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,128 [classy] Re-using computed results
 2023-07-02 10:34:26,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,128 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.459444787556578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,128 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,158 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.618233
 2023-07-02 10:34:26,158 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,158 [model] Posterior to be computed for parameters {'Omega_m': 0.3536381417562883, 'b1': 0.43647470620823503}
 2023-07-02 10:34:26,158 [prior] Evaluating prior at array([0.35363814, 0.43647471])
 2023-07-02 10:34:26,158 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,158 [model] Got input parameters: {'Omega_m': 0.3536381417562883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43647470620823503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,158 [classy] Got parameters {'Omega_m': 0.3536381417562883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,158 [classy] Computing new state
 2023-07-02 10:34:26,158 [classy] Setting parameters: {'Omega_m': 0.3536381417562883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,204 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57893199995527}
 2023-07-02 10:34:26,204 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,206 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0943107
 2023-07-02 10:34:26,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43647470620823503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,225 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.22908
 2023-07-02 10:34:26,225 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,226 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.5267836238332567}
 2023-07-02 10:34:26,226 [prior] Evaluating prior at array([0.322224  , 0.52678362])
 2023-07-02 10:34:26,226 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,226 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5267836238332567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,226 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,226 [classy] Re-using computed results
 2023-07-02 10:34:26,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,226 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5267836238332567, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,226 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,246 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.7589
 2023-07-02 10:34:26,246 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,246 [model] Posterior to be computed for parameters {'Omega_m': 0.34812448864411255, 'b1': 0.44562764152709394}
 2023-07-02 10:34:26,246 [prior] Evaluating prior at array([0.34812449, 0.44562764])
 2023-07-02 10:34:26,246 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,246 [model] Got input parameters: {'Omega_m': 0.34812448864411255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44562764152709394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,246 [classy] Got parameters {'Omega_m': 0.34812448864411255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,246 [classy] Computing new state
 2023-07-02 10:34:26,246 [classy] Setting parameters: {'Omega_m': 0.34812448864411255, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.1764455031036}
 2023-07-02 10:34:26,292 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,294 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0716915
 2023-07-02 10:34:26,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44562764152709394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,294 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,313 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.45012
 2023-07-02 10:34:26,313 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,314 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.47337002743556816}
 2023-07-02 10:34:26,314 [prior] Evaluating prior at array([0.322224  , 0.47337003])
 2023-07-02 10:34:26,314 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,314 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47337002743556816, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,314 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,314 [classy] Re-using computed results
 2023-07-02 10:34:26,314 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,314 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47337002743556816, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,314 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,333 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14202
 2023-07-02 10:34:26,334 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,334 [mcmc] New sample, #655:
   Omega_m:0.322224, b1:0.4886237
 2023-07-02 10:34:26,334 [model] Posterior to be computed for parameters {'Omega_m': 0.3332632803916596, 'b1': 0.4550442799383361}
 2023-07-02 10:34:26,334 [prior] Evaluating prior at array([0.33326328, 0.45504428])
 2023-07-02 10:34:26,334 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,334 [model] Got input parameters: {'Omega_m': 0.3332632803916596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4550442799383361, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,334 [classy] Got parameters {'Omega_m': 0.3332632803916596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,334 [classy] Computing new state
 2023-07-02 10:34:26,334 [classy] Setting parameters: {'Omega_m': 0.3332632803916596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.83112799168265}
 2023-07-02 10:34:26,380 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,381 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0253701
 2023-07-02 10:34:26,381 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4550442799383361, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,382 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,401 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.822697
 2023-07-02 10:34:26,401 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,401 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.47985304491470115}
 2023-07-02 10:34:26,401 [prior] Evaluating prior at array([0.322224  , 0.47985304])
 2023-07-02 10:34:26,401 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,402 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47985304491470115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,402 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,402 [classy] Re-using computed results
 2023-07-02 10:34:26,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,402 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,402 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47985304491470115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,402 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,421 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50986
 2023-07-02 10:34:26,421 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,421 [mcmc] New sample, #656:
   Omega_m:0.322224, b1:0.47337
 2023-07-02 10:34:26,421 [model] Posterior to be computed for parameters {'Omega_m': 0.3759788387536629, 'b1': 0.39061736985365847}
 2023-07-02 10:34:26,421 [prior] Evaluating prior at array([0.37597884, 0.39061737])
 2023-07-02 10:34:26,421 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,421 [model] Got input parameters: {'Omega_m': 0.3759788387536629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39061736985365847, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,421 [classy] Got parameters {'Omega_m': 0.3759788387536629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,421 [classy] Computing new state
 2023-07-02 10:34:26,421 [classy] Setting parameters: {'Omega_m': 0.3759788387536629, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.24277616946878}
 2023-07-02 10:34:26,473 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,475 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.213186
 2023-07-02 10:34:26,475 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39061736985365847, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,476 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,505 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.1038
 2023-07-02 10:34:26,506 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,506 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.46853041511335153}
 2023-07-02 10:34:26,506 [prior] Evaluating prior at array([0.322224  , 0.46853042])
 2023-07-02 10:34:26,506 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,506 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46853041511335153, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,506 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,506 [classy] Re-using computed results
 2023-07-02 10:34:26,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,506 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46853041511335153, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,506 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72463
 2023-07-02 10:34:26,536 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,536 [mcmc] New sample, #657:
   Omega_m:0.322224, b1:0.479853
 2023-07-02 10:34:26,536 [model] Posterior to be computed for parameters {'Omega_m': 0.33298331747475146, 'b1': 0.4506694198263157}
 2023-07-02 10:34:26,536 [prior] Evaluating prior at array([0.33298332, 0.45066942])
 2023-07-02 10:34:26,536 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,536 [model] Got input parameters: {'Omega_m': 0.33298331747475146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4506694198263157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,536 [classy] Got parameters {'Omega_m': 0.33298331747475146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,536 [classy] Computing new state
 2023-07-02 10:34:26,536 [classy] Setting parameters: {'Omega_m': 0.33298331747475146, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,585 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8629400222411}
 2023-07-02 10:34:26,586 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,587 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247128
 2023-07-02 10:34:26,588 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4506694198263157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,588 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,608 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.49024
 2023-07-02 10:34:26,608 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,608 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.477830742568947}
 2023-07-02 10:34:26,608 [prior] Evaluating prior at array([0.322224  , 0.47783074])
 2023-07-02 10:34:26,608 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,608 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.477830742568947, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,608 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,608 [classy] Re-using computed results
 2023-07-02 10:34:26,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,608 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.477830742568947, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,608 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,630 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41885
 2023-07-02 10:34:26,630 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,630 [mcmc] New sample, #658:
   Omega_m:0.322224, b1:0.4685304
 2023-07-02 10:34:26,630 [model] Posterior to be computed for parameters {'Omega_m': 0.411455357690119, 'b1': 0.32970230139489043}
 2023-07-02 10:34:26,630 [prior] Evaluating prior at array([0.41145536, 0.3297023 ])
 2023-07-02 10:34:26,630 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,630 [model] Got input parameters: {'Omega_m': 0.411455357690119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.32970230139489043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,630 [classy] Got parameters {'Omega_m': 0.411455357690119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,630 [classy] Computing new state
 2023-07-02 10:34:26,630 [classy] Setting parameters: {'Omega_m': 0.411455357690119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.7882417086518}
 2023-07-02 10:34:26,678 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,680 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.479592
 2023-07-02 10:34:26,680 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.32970230139489043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,680 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.536
 2023-07-02 10:34:26,700 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,700 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.5310828142991628}
 2023-07-02 10:34:26,700 [prior] Evaluating prior at array([0.322224  , 0.53108281])
 2023-07-02 10:34:26,700 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,700 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5310828142991628, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,700 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,700 [classy] Re-using computed results
 2023-07-02 10:34:26,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
 2023-07-02 10:34:26,700 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,700 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5310828142991628, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,700 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,720 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.7945
 2023-07-02 10:34:26,720 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,720 [model] Posterior to be computed for parameters {'Omega_m': 0.3158117417123645, 'b1': 0.488475407518123}
 2023-07-02 10:34:26,720 [prior] Evaluating prior at array([0.31581174, 0.48847541])
 2023-07-02 10:34:26,720 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,720 [model] Got input parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.488475407518123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,720 [classy] Got parameters {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,720 [classy] Computing new state
 2023-07-02 10:34:26,720 [classy] Setting parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8615837788733}
 2023-07-02 10:34:26,767 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000875919
 2023-07-02 10:34:26,769 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.488475407518123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,769 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,788 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63584
 2023-07-02 10:34:26,788 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,788 [mcmc] New sample, #659:
   Omega_m:0.322224, b1:0.4778307
 2023-07-02 10:34:26,789 [model] Posterior to be computed for parameters {'Omega_m': 0.3158117417123645, 'b1': 0.46507094795764364}
 2023-07-02 10:34:26,789 [prior] Evaluating prior at array([0.31581174, 0.46507095])
 2023-07-02 10:34:26,789 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,789 [model] Got input parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46507094795764364, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,789 [classy] Got parameters {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,789 [classy] Re-using computed results
 2023-07-02 10:34:26,789 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8615837788733}
 2023-07-02 10:34:26,789 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46507094795764364, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,789 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,808 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0550902
 2023-07-02 10:34:26,809 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,809 [model] Posterior to be computed for parameters {'Omega_m': 0.33629002383698603, 'b1': 0.4544804521020681}
 2023-07-02 10:34:26,809 [prior] Evaluating prior at array([0.33629002, 0.45448045])
 2023-07-02 10:34:26,809 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,809 [model] Got input parameters: {'Omega_m': 0.33629002383698603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4544804521020681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,809 [classy] Got parameters {'Omega_m': 0.33629002383698603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,809 [classy] Computing new state
 2023-07-02 10:34:26,809 [classy] Setting parameters: {'Omega_m': 0.33629002383698603, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48876665234016}
 2023-07-02 10:34:26,856 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,858 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0329978
 2023-07-02 10:34:26,858 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4544804521020681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,858 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,877 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.492623
 2023-07-02 10:34:26,877 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,877 [model] Posterior to be computed for parameters {'Omega_m': 0.3158117417123645, 'b1': 0.48849094684824146}
 2023-07-02 10:34:26,877 [prior] Evaluating prior at array([0.31581174, 0.48849095])
 2023-07-02 10:34:26,878 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,878 [model] Got input parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48849094684824146, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,878 [classy] Got parameters {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,878 [classy] Re-using computed results
 2023-07-02 10:34:26,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8615837788733}
 2023-07-02 10:34:26,878 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48849094684824146, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,878 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,897 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6367
 2023-07-02 10:34:26,898 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,898 [mcmc] New sample, #660:
   Omega_m:0.3158117, b1:0.4884754
 2023-07-02 10:34:26,898 [model] Posterior to be computed for parameters {'Omega_m': 0.3204177102300361, 'b1': 0.4808448125947368}
 2023-07-02 10:34:26,898 [prior] Evaluating prior at array([0.32041771, 0.48084481])
 2023-07-02 10:34:26,898 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,898 [model] Got input parameters: {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4808448125947368, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,898 [classy] Got parameters {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,898 [classy] Computing new state
 2023-07-02 10:34:26,898 [classy] Setting parameters: {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:26,945 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.31611911198027}
 2023-07-02 10:34:26,945 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:26,947 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00398695
 2023-07-02 10:34:26,947 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4808448125947368, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,947 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,966 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52558
 2023-07-02 10:34:26,966 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,966 [mcmc] New sample, #661:
   Omega_m:0.3158117, b1:0.4884909
 2023-07-02 10:34:26,967 [model] Posterior to be computed for parameters {'Omega_m': 0.3204177102300361, 'b1': 0.43676935405998435}
 2023-07-02 10:34:26,967 [prior] Evaluating prior at array([0.32041771, 0.43676935])
 2023-07-02 10:34:26,967 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,967 [model] Got input parameters: {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43676935405998435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,967 [classy] Got parameters {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,967 [classy] Re-using computed results
 2023-07-02 10:34:26,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.31611911198027}
 2023-07-02 10:34:26,967 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:26,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43676935405998435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,967 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:26,986 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.63541
 2023-07-02 10:34:26,986 [model] Computed derived parameters: {}
 2023-07-02 10:34:26,986 [model] Posterior to be computed for parameters {'Omega_m': 0.31743703255982736, 'b1': 0.48579288411224697}
 2023-07-02 10:34:26,986 [prior] Evaluating prior at array([0.31743703, 0.48579288])
 2023-07-02 10:34:26,987 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:26,987 [model] Got input parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48579288411224697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:26,987 [classy] Got parameters {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:26,987 [classy] Computing new state
 2023-07-02 10:34:26,987 [classy] Setting parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6683066025225}
 2023-07-02 10:34:27,037 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00168832
 2023-07-02 10:34:27,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48579288411224697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,039 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,059 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62411
 2023-07-02 10:34:27,059 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,059 [mcmc] New sample, #662:
   Omega_m:0.3204177, b1:0.4808448
 2023-07-02 10:34:27,059 [model] Posterior to be computed for parameters {'Omega_m': 0.31743703255982736, 'b1': 0.5048650255043015}
 2023-07-02 10:34:27,059 [prior] Evaluating prior at array([0.31743703, 0.50486503])
 2023-07-02 10:34:27,059 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,059 [model] Got input parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5048650255043015, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,059 [classy] Got parameters {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,059 [classy] Re-using computed results
 2023-07-02 10:34:27,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6683066025225}
 2023-07-02 10:34:27,060 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5048650255043015, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,060 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,079 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6807
 2023-07-02 10:34:27,079 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,079 [mcmc] New sample, #663:
   Omega_m:0.317437, b1:0.4857929
 2023-07-02 10:34:27,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3392104508316875, 'b1': 0.46872008039110497}
 2023-07-02 10:34:27,079 [prior] Evaluating prior at array([0.33921045, 0.46872008])
 2023-07-02 10:34:27,079 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,079 [model] Got input parameters: {'Omega_m': 0.3392104508316875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46872008039110497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,079 [classy] Got parameters {'Omega_m': 0.3392104508316875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,079 [classy] Computing new state
 2023-07-02 10:34:27,079 [classy] Setting parameters: {'Omega_m': 0.3392104508316875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.161056504803}
 2023-07-02 10:34:27,130 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,132 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0412527
 2023-07-02 10:34:27,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46872008039110497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,133 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.418649
 2023-07-02 10:34:27,156 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,156 [model] Posterior to be computed for parameters {'Omega_m': 0.31743703255982736, 'b1': 0.509268578774452}
 2023-07-02 10:34:27,156 [prior] Evaluating prior at array([0.31743703, 0.50926858])
 2023-07-02 10:34:27,156 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,156 [model] Got input parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.509268578774452, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,157 [classy] Got parameters {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,157 [classy] Re-using computed results
 2023-07-02 10:34:27,157 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6683066025225}
 2023-07-02 10:34:27,157 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,157 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.509268578774452, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,157 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,178 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41098
 2023-07-02 10:34:27,178 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,179 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.4948413456017014}
 2023-07-02 10:34:27,179 [prior] Evaluating prior at array([0.32347522, 0.49484135])
 2023-07-02 10:34:27,179 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,179 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4948413456017014, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,179 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,179 [classy] Computing new state
 2023-07-02 10:34:27,179 [classy] Setting parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,227 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
 2023-07-02 10:34:27,227 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,229 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00741208
 2023-07-02 10:34:27,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4948413456017014, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,230 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,252 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28682
 2023-07-02 10:34:27,252 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,252 [mcmc] New sample, #664:
   Omega_m:0.317437, b1:0.504865
 2023-07-02 10:34:27,252 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.4777915370986712}
 2023-07-02 10:34:27,252 [prior] Evaluating prior at array([0.32347522, 0.47779154])
 2023-07-02 10:34:27,252 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,252 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4777915370986712, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,252 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,252 [classy] Re-using computed results
 2023-07-02 10:34:27,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
 2023-07-02 10:34:27,252 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,252 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4777915370986712, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,252 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,272 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41519
 2023-07-02 10:34:27,272 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,272 [mcmc] New sample, #665:
   Omega_m:0.3234752, b1:0.4948413
 2023-07-02 10:34:27,272 [model] Posterior to be computed for parameters {'Omega_m': 0.3613987522957856, 'b1': 0.414836600272471}
 2023-07-02 10:34:27,272 [prior] Evaluating prior at array([0.36139875, 0.4148366 ])
 2023-07-02 10:34:27,272 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,272 [model] Got input parameters: {'Omega_m': 0.3613987522957856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.414836600272471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,273 [classy] Got parameters {'Omega_m': 0.3613987522957856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,273 [classy] Computing new state
 2023-07-02 10:34:27,273 [classy] Setting parameters: {'Omega_m': 0.3613987522957856, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,319 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.75225975293353}
 2023-07-02 10:34:27,319 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,321 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.130811
 2023-07-02 10:34:27,321 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.414836600272471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,321 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,341 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.94536
 2023-07-02 10:34:27,341 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,341 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.4541539673057772}
 2023-07-02 10:34:27,341 [prior] Evaluating prior at array([0.32347522, 0.45415397])
 2023-07-02 10:34:27,341 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,341 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4541539673057772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,341 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,341 [classy] Re-using computed results
 2023-07-02 10:34:27,341 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
 2023-07-02 10:34:27,341 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4541539673057772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,342 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,361 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0531484
 2023-07-02 10:34:27,361 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,362 [model] Posterior to be computed for parameters {'Omega_m': 0.300987281724381, 'b1': 0.5151226123605656}
 2023-07-02 10:34:27,362 [prior] Evaluating prior at array([0.30098728, 0.51512261])
 2023-07-02 10:34:27,362 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,362 [model] Got input parameters: {'Omega_m': 0.300987281724381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5151226123605656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,362 [classy] Got parameters {'Omega_m': 0.300987281724381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,362 [classy] Computing new state
 2023-07-02 10:34:27,362 [classy] Setting parameters: {'Omega_m': 0.300987281724381, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.66649284965064}
 2023-07-02 10:34:27,408 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,410 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00854486
 2023-07-02 10:34:27,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5151226123605656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,410 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42299
 2023-07-02 10:34:27,430 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,430 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.5085610802448892}
 2023-07-02 10:34:27,430 [prior] Evaluating prior at array([0.32347522, 0.50856108])
 2023-07-02 10:34:27,430 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,430 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5085610802448892, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,430 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,430 [classy] Re-using computed results
 2023-07-02 10:34:27,430 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
 2023-07-02 10:34:27,430 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5085610802448892, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,430 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,451 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.00579
 2023-07-02 10:34:27,451 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,451 [model] Posterior to be computed for parameters {'Omega_m': 0.30782635576805834, 'b1': 0.5037694131133311}
 2023-07-02 10:34:27,451 [prior] Evaluating prior at array([0.30782636, 0.50376941])
 2023-07-02 10:34:27,451 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,451 [model] Got input parameters: {'Omega_m': 0.30782635576805834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5037694131133311, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,451 [classy] Got parameters {'Omega_m': 0.30782635576805834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,451 [classy] Computing new state
 2023-07-02 10:34:27,451 [classy] Setting parameters: {'Omega_m': 0.30782635576805834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,498 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82431291899152}
 2023-07-02 10:34:27,498 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,500 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00154834
 2023-07-02 10:34:27,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5037694131133311, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,500 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,519 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36746
 2023-07-02 10:34:27,519 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,519 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.5191033793095934}
 2023-07-02 10:34:27,519 [prior] Evaluating prior at array([0.32347522, 0.51910338])
 2023-07-02 10:34:27,519 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,520 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191033793095934, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,520 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,520 [classy] Re-using computed results
 2023-07-02 10:34:27,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
 2023-07-02 10:34:27,520 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,520 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191033793095934, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,520 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,539 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.721708
 2023-07-02 10:34:27,539 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,539 [model] Posterior to be computed for parameters {'Omega_m': 0.32401597620154776, 'b1': 0.4768938470140827}
 2023-07-02 10:34:27,539 [prior] Evaluating prior at array([0.32401598, 0.47689385])
 2023-07-02 10:34:27,540 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,540 [model] Got input parameters: {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4768938470140827, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,540 [classy] Got parameters {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,540 [classy] Computing new state
 2023-07-02 10:34:27,540 [classy] Setting parameters: {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89483143145048}
 2023-07-02 10:34:27,586 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,588 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00812858
 2023-07-02 10:34:27,588 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4768938470140827, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,588 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,608 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36904
 2023-07-02 10:34:27,608 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,608 [mcmc] New sample, #666:
   Omega_m:0.3234752, b1:0.4777915
 2023-07-02 10:34:27,608 [model] Posterior to be computed for parameters {'Omega_m': 0.32401597620154776, 'b1': 0.4501961613248355}
 2023-07-02 10:34:27,608 [prior] Evaluating prior at array([0.32401598, 0.45019616])
 2023-07-02 10:34:27,608 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,609 [model] Got input parameters: {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4501961613248355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,609 [classy] Got parameters {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,609 [classy] Re-using computed results
 2023-07-02 10:34:27,609 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89483143145048}
 2023-07-02 10:34:27,609 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,609 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4501961613248355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,609 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,628 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.495073
 2023-07-02 10:34:27,628 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,628 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.4669032195355536}
 2023-07-02 10:34:27,628 [prior] Evaluating prior at array([0.33003425, 0.46690322])
 2023-07-02 10:34:27,628 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,628 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4669032195355536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,628 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,628 [classy] Computing new state
 2023-07-02 10:34:27,628 [classy] Setting parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
 2023-07-02 10:34:27,676 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0182963
 2023-07-02 10:34:27,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4669032195355536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,678 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,697 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65958
 2023-07-02 10:34:27,697 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,697 [mcmc] New sample, #667:
   Omega_m:0.324016, b1:0.4768938
 2023-07-02 10:34:27,697 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.4937271729091959}
 2023-07-02 10:34:27,697 [prior] Evaluating prior at array([0.33003425, 0.49372717])
 2023-07-02 10:34:27,697 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,697 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4937271729091959, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,697 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,697 [classy] Re-using computed results
 2023-07-02 10:34:27,697 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
 2023-07-02 10:34:27,697 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4937271729091959, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,697 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,717 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.575068
 2023-07-02 10:34:27,717 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,717 [mcmc] New sample, #668:
   Omega_m:0.3300342, b1:0.4669032
 2023-07-02 10:34:27,717 [model] Posterior to be computed for parameters {'Omega_m': 0.3555628740856584, 'b1': 0.451348398474087}
 2023-07-02 10:34:27,718 [prior] Evaluating prior at array([0.35556287, 0.4513484 ])
 2023-07-02 10:34:27,718 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,718 [model] Got input parameters: {'Omega_m': 0.3555628740856584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.451348398474087, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,718 [classy] Got parameters {'Omega_m': 0.3555628740856584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,718 [classy] Computing new state
 2023-07-02 10:34:27,718 [classy] Setting parameters: {'Omega_m': 0.3555628740856584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.3723564571013}
 2023-07-02 10:34:27,764 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102864
 2023-07-02 10:34:27,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.451348398474087, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46719
 2023-07-02 10:34:27,786 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,786 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.5133901763103446}
 2023-07-02 10:34:27,786 [prior] Evaluating prior at array([0.33003425, 0.51339018])
 2023-07-02 10:34:27,786 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,786 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133901763103446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,786 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,786 [classy] Re-using computed results
 2023-07-02 10:34:27,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
 2023-07-02 10:34:27,786 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133901763103446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,786 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,808 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.85844
 2023-07-02 10:34:27,808 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,809 [model] Posterior to be computed for parameters {'Omega_m': 0.2945255713712757, 'b1': 0.5526733226969497}
 2023-07-02 10:34:27,809 [prior] Evaluating prior at array([0.29452557, 0.55267332])
 2023-07-02 10:34:27,809 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,809 [model] Got input parameters: {'Omega_m': 0.2945255713712757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5526733226969497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,809 [classy] Got parameters {'Omega_m': 0.2945255713712757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,809 [classy] Computing new state
 2023-07-02 10:34:27,810 [classy] Setting parameters: {'Omega_m': 0.2945255713712757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.47782903336713}
 2023-07-02 10:34:27,860 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,862 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0208988
 2023-07-02 10:34:27,862 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5526733226969497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,862 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,882 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.307783
 2023-07-02 10:34:27,882 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.49239712107443523}
 2023-07-02 10:34:27,882 [prior] Evaluating prior at array([0.33003425, 0.49239712])
 2023-07-02 10:34:27,882 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,882 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49239712107443523, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,882 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,882 [classy] Re-using computed results
 2023-07-02 10:34:27,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
 2023-07-02 10:34:27,882 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,882 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49239712107443523, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,882 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,902 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.7247
 2023-07-02 10:34:27,902 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,902 [mcmc] New sample, #669:
   Omega_m:0.3300342, b1:0.4937272
 2023-07-02 10:34:27,902 [model] Posterior to be computed for parameters {'Omega_m': 0.3502426894010373, 'b1': 0.45885011485397653}
 2023-07-02 10:34:27,902 [prior] Evaluating prior at array([0.35024269, 0.45885011])
 2023-07-02 10:34:27,902 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,902 [model] Got input parameters: {'Omega_m': 0.3502426894010373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45885011485397653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,902 [classy] Got parameters {'Omega_m': 0.3502426894010373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,902 [classy] Computing new state
 2023-07-02 10:34:27,902 [classy] Setting parameters: {'Omega_m': 0.3502426894010373, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:27,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9458781846698}
 2023-07-02 10:34:27,949 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:27,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.080047
 2023-07-02 10:34:27,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45885011485397653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,950 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,970 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.42367
 2023-07-02 10:34:27,970 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,971 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.488145821476959}
 2023-07-02 10:34:27,971 [prior] Evaluating prior at array([0.33003425, 0.48814582])
 2023-07-02 10:34:27,971 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,971 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.488145821476959, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,971 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,971 [classy] Re-using computed results
 2023-07-02 10:34:27,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
 2023-07-02 10:34:27,971 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:27,971 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.488145821476959, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,971 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:27,990 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.13448
 2023-07-02 10:34:27,990 [model] Computed derived parameters: {}
 2023-07-02 10:34:27,990 [mcmc] New sample, #670:
   Omega_m:0.3300342, b1:0.4923971
 2023-07-02 10:34:27,991 [model] Posterior to be computed for parameters {'Omega_m': 0.3161238809807235, 'b1': 0.5112377151426849}
 2023-07-02 10:34:27,991 [prior] Evaluating prior at array([0.31612388, 0.51123772])
 2023-07-02 10:34:27,991 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:27,991 [model] Got input parameters: {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112377151426849, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:27,991 [classy] Got parameters {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:27,991 [classy] Computing new state
 2023-07-02 10:34:27,991 [classy] Setting parameters: {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.82439463601958}
 2023-07-02 10:34:28,038 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00100756
 2023-07-02 10:34:28,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112377151426849, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,060 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46477
 2023-07-02 10:34:28,060 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,060 [mcmc] New sample, #671:
   Omega_m:0.3300342, b1:0.4881458
 2023-07-02 10:34:28,061 [model] Posterior to be computed for parameters {'Omega_m': 0.3161238809807235, 'b1': 0.4948521415773958}
 2023-07-02 10:34:28,061 [prior] Evaluating prior at array([0.31612388, 0.49485214])
 2023-07-02 10:34:28,061 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,061 [model] Got input parameters: {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4948521415773958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,061 [classy] Got parameters {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,061 [classy] Re-using computed results
 2023-07-02 10:34:28,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.82439463601958}
 2023-07-02 10:34:28,061 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,061 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4948521415773958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,061 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,081 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88975
 2023-07-02 10:34:28,081 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,081 [mcmc] New sample, #672:
   Omega_m:0.3161239, b1:0.5112377
 2023-07-02 10:34:28,081 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5080317584896779}
 2023-07-02 10:34:28,081 [prior] Evaluating prior at array([0.30818459, 0.50803176])
 2023-07-02 10:34:28,081 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,081 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080317584896779, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,081 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,081 [classy] Computing new state
 2023-07-02 10:34:28,081 [classy] Setting parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,131 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00134821
 2023-07-02 10:34:28,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080317584896779, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,133 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,154 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5837
 2023-07-02 10:34:28,154 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,154 [mcmc] New sample, #673:
   Omega_m:0.3161239, b1:0.4948521
 2023-07-02 10:34:28,154 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.4605028802481791}
 2023-07-02 10:34:28,154 [prior] Evaluating prior at array([0.30818459, 0.46050288])
 2023-07-02 10:34:28,154 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,154 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4605028802481791, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,154 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,154 [classy] Re-using computed results
 2023-07-02 10:34:28,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,154 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,154 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4605028802481791, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,154 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,175 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.28655
 2023-07-02 10:34:28,175 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,175 [model] Posterior to be computed for parameters {'Omega_m': 0.2909433465217033, 'b1': 0.5366530671178064}
 2023-07-02 10:34:28,175 [prior] Evaluating prior at array([0.29094335, 0.53665307])
 2023-07-02 10:34:28,175 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,175 [model] Got input parameters: {'Omega_m': 0.2909433465217033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366530671178064, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,175 [classy] Got parameters {'Omega_m': 0.2909433465217033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,175 [classy] Computing new state
 2023-07-02 10:34:28,175 [classy] Setting parameters: {'Omega_m': 0.2909433465217033, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.93431215213093}
 2023-07-02 10:34:28,222 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,224 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0302562
 2023-07-02 10:34:28,224 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366530671178064, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,224 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.87462
 2023-07-02 10:34:28,243 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,244 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5122751487607266}
 2023-07-02 10:34:28,244 [prior] Evaluating prior at array([0.30818459, 0.51227515])
 2023-07-02 10:34:28,244 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,244 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122751487607266, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,244 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,244 [classy] Re-using computed results
 2023-07-02 10:34:28,244 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,244 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,244 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122751487607266, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,244 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,264 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64187
 2023-07-02 10:34:28,264 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,264 [mcmc] New sample, #674:
   Omega_m:0.3081846, b1:0.5080318
 2023-07-02 10:34:28,264 [model] Posterior to be computed for parameters {'Omega_m': 0.29329634312139774, 'b1': 0.5369903673167505}
 2023-07-02 10:34:28,264 [prior] Evaluating prior at array([0.29329634, 0.53699037])
 2023-07-02 10:34:28,264 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,264 [model] Got input parameters: {'Omega_m': 0.29329634312139774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5369903673167505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,264 [classy] Got parameters {'Omega_m': 0.29329634312139774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,264 [classy] Computing new state
 2023-07-02 10:34:28,264 [classy] Setting parameters: {'Omega_m': 0.29329634312139774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.63392355470125}
 2023-07-02 10:34:28,310 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,312 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0239042
 2023-07-02 10:34:28,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5369903673167505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,312 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0483115
 2023-07-02 10:34:28,332 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,332 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5263175419786233}
 2023-07-02 10:34:28,332 [prior] Evaluating prior at array([0.30818459, 0.52631754])
 2023-07-02 10:34:28,333 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,333 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5263175419786233, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,333 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,333 [classy] Re-using computed results
 2023-07-02 10:34:28,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,333 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,333 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5263175419786233, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,333 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,352 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14083
 2023-07-02 10:34:28,352 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,352 [model] Posterior to be computed for parameters {'Omega_m': 0.29853242946857, 'b1': 0.5282982064780871}
 2023-07-02 10:34:28,352 [prior] Evaluating prior at array([0.29853243, 0.52829821])
 2023-07-02 10:34:28,352 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,352 [model] Got input parameters: {'Omega_m': 0.29853242946857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282982064780871, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,353 [classy] Got parameters {'Omega_m': 0.29853242946857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,353 [classy] Computing new state
 2023-07-02 10:34:28,353 [classy] Setting parameters: {'Omega_m': 0.29853242946857, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.97291662000035}
 2023-07-02 10:34:28,399 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0125655
 2023-07-02 10:34:28,401 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282982064780871, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,401 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,421 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24304
 2023-07-02 10:34:28,421 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,421 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5082847508536987}
 2023-07-02 10:34:28,421 [prior] Evaluating prior at array([0.30818459, 0.50828475])
 2023-07-02 10:34:28,421 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,421 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5082847508536987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,421 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,421 [classy] Re-using computed results
 2023-07-02 10:34:28,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,421 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,421 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5082847508536987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,421 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,441 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58985
 2023-07-02 10:34:28,441 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,441 [mcmc] New sample, #675:
   Omega_m:0.3081846, b1:0.5122751
 2023-07-02 10:34:28,441 [model] Posterior to be computed for parameters {'Omega_m': 0.3295320030870295, 'b1': 0.4728469918549347}
 2023-07-02 10:34:28,441 [prior] Evaluating prior at array([0.329532  , 0.47284699])
 2023-07-02 10:34:28,441 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,441 [model] Got input parameters: {'Omega_m': 0.3295320030870295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4728469918549347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,441 [classy] Got parameters {'Omega_m': 0.3295320030870295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,441 [classy] Computing new state
 2023-07-02 10:34:28,441 [classy] Setting parameters: {'Omega_m': 0.3295320030870295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.25706610657542}
 2023-07-02 10:34:28,488 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,489 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0172962
 2023-07-02 10:34:28,490 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4728469918549347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,490 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,509 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.83495
 2023-07-02 10:34:28,509 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,509 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5191353964663232}
 2023-07-02 10:34:28,509 [prior] Evaluating prior at array([0.30818459, 0.5191354 ])
 2023-07-02 10:34:28,509 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,509 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191353964663232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,509 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,509 [classy] Re-using computed results
 2023-07-02 10:34:28,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,509 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191353964663232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,529 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53164
 2023-07-02 10:34:28,529 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,529 [mcmc] New sample, #676:
   Omega_m:0.3081846, b1:0.5082848
 2023-07-02 10:34:28,530 [model] Posterior to be computed for parameters {'Omega_m': 0.328691348921757, 'b1': 0.4850931647239397}
 2023-07-02 10:34:28,530 [prior] Evaluating prior at array([0.32869135, 0.48509316])
 2023-07-02 10:34:28,530 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,530 [model] Got input parameters: {'Omega_m': 0.328691348921757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4850931647239397, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,530 [classy] Got parameters {'Omega_m': 0.328691348921757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,530 [classy] Computing new state
 2023-07-02 10:34:28,530 [classy] Setting parameters: {'Omega_m': 0.328691348921757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,576 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35364232550143}
 2023-07-02 10:34:28,577 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,578 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156831
 2023-07-02 10:34:28,578 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4850931647239397, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,578 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,598 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70637
 2023-07-02 10:34:28,598 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,598 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.4928617499551069}
 2023-07-02 10:34:28,598 [prior] Evaluating prior at array([0.30818459, 0.49286175])
 2023-07-02 10:34:28,598 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,598 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4928617499551069, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,598 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,598 [classy] Re-using computed results
 2023-07-02 10:34:28,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
 2023-07-02 10:34:28,598 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4928617499551069, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,598 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,618 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60666
 2023-07-02 10:34:28,618 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,618 [mcmc] New sample, #677:
   Omega_m:0.3081846, b1:0.5191354
 2023-07-02 10:34:28,619 [model] Posterior to be computed for parameters {'Omega_m': 0.3115782114424989, 'b1': 0.48722816802504}
 2023-07-02 10:34:28,619 [prior] Evaluating prior at array([0.31157821, 0.48722817])
 2023-07-02 10:34:28,619 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,619 [model] Got input parameters: {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48722816802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,619 [classy] Got parameters {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,619 [classy] Computing new state
 2023-07-02 10:34:28,619 [classy] Setting parameters: {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,665 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.36925905071544}
 2023-07-02 10:34:28,665 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,667 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000252795
 2023-07-02 10:34:28,667 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48722816802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,667 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,687 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.86713
 2023-07-02 10:34:28,687 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,687 [mcmc] New sample, #678:
   Omega_m:0.3081846, b1:0.4928617
 2023-07-02 10:34:28,688 [model] Posterior to be computed for parameters {'Omega_m': 0.3115782114424989, 'b1': 0.4592189537722995}
 2023-07-02 10:34:28,688 [prior] Evaluating prior at array([0.31157821, 0.45921895])
 2023-07-02 10:34:28,688 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,688 [model] Got input parameters: {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4592189537722995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,688 [classy] Got parameters {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,688 [classy] Re-using computed results
 2023-07-02 10:34:28,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.36925905071544}
 2023-07-02 10:34:28,688 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4592189537722995, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,688 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,707 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.88959
 2023-07-02 10:34:28,707 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,707 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.46445803145130765}
 2023-07-02 10:34:28,707 [prior] Evaluating prior at array([0.32529475, 0.46445803])
 2023-07-02 10:34:28,708 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,708 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46445803145130765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,708 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,708 [classy] Computing new state
 2023-07-02 10:34:28,708 [classy] Setting parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
 2023-07-02 10:34:28,754 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00995369
 2023-07-02 10:34:28,756 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46445803145130765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,756 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,776 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58429
 2023-07-02 10:34:28,776 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,776 [mcmc] New sample, #679:
   Omega_m:0.3115782, b1:0.4872282
 2023-07-02 10:34:28,776 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.4654409403304877}
 2023-07-02 10:34:28,776 [prior] Evaluating prior at array([0.32529475, 0.46544094])
 2023-07-02 10:34:28,776 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,776 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4654409403304877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,776 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,777 [classy] Re-using computed results
 2023-07-02 10:34:28,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
 2023-07-02 10:34:28,777 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4654409403304877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,777 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,796 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67151
 2023-07-02 10:34:28,796 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,796 [mcmc] New sample, #680:
   Omega_m:0.3252948, b1:0.464458
 2023-07-02 10:34:28,796 [model] Posterior to be computed for parameters {'Omega_m': 0.35821203583268013, 'b1': 0.41079663503957375}
 2023-07-02 10:34:28,796 [prior] Evaluating prior at array([0.35821204, 0.41079664])
 2023-07-02 10:34:28,796 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,796 [model] Got input parameters: {'Omega_m': 0.35821203583268013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41079663503957375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,796 [classy] Got parameters {'Omega_m': 0.35821203583268013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,796 [classy] Computing new state
 2023-07-02 10:34:28,797 [classy] Setting parameters: {'Omega_m': 0.35821203583268013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.08970233560763}
 2023-07-02 10:34:28,843 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.11518
 2023-07-02 10:34:28,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41079663503957375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,845 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.11112
 2023-07-02 10:34:28,865 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,865 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.4736693811831151}
 2023-07-02 10:34:28,865 [prior] Evaluating prior at array([0.32529475, 0.47366938])
 2023-07-02 10:34:28,865 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,865 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4736693811831151, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,865 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,865 [classy] Re-using computed results
 2023-07-02 10:34:28,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
 2023-07-02 10:34:28,865 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4736693811831151, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,865 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20394
 2023-07-02 10:34:28,885 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,885 [mcmc] New sample, #681:
   Omega_m:0.3252948, b1:0.4654409
 2023-07-02 10:34:28,885 [model] Posterior to be computed for parameters {'Omega_m': 0.27926486118989297, 'b1': 0.5500812682950901}
 2023-07-02 10:34:28,885 [prior] Evaluating prior at array([0.27926486, 0.55008127])
 2023-07-02 10:34:28,886 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,886 [model] Got input parameters: {'Omega_m': 0.27926486118989297, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5500812682950901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,886 [classy] Got parameters {'Omega_m': 0.27926486118989297, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,886 [classy] Computing new state
 2023-07-02 10:34:28,886 [classy] Setting parameters: {'Omega_m': 0.27926486118989297, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:28,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.4570632109594}
 2023-07-02 10:34:28,932 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:28,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.073905
 2023-07-02 10:34:28,934 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5500812682950901, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,934 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,953 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.08541
 2023-07-02 10:34:28,953 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,953 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.46599749560486586}
 2023-07-02 10:34:28,953 [prior] Evaluating prior at array([0.32529475, 0.4659975 ])
 2023-07-02 10:34:28,953 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,954 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46599749560486586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,954 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,954 [classy] Re-using computed results
 2023-07-02 10:34:28,954 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
 2023-07-02 10:34:28,954 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:28,954 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46599749560486586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,954 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:28,973 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.71868
 2023-07-02 10:34:28,973 [model] Computed derived parameters: {}
 2023-07-02 10:34:28,973 [mcmc] New sample, #682:
   Omega_m:0.3252948, b1:0.4736694
 2023-07-02 10:34:28,973 [model] Posterior to be computed for parameters {'Omega_m': 0.37360684724760046, 'b1': 0.3857970462729653}
 2023-07-02 10:34:28,974 [prior] Evaluating prior at array([0.37360685, 0.38579705])
 2023-07-02 10:34:28,974 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:28,974 [model] Got input parameters: {'Omega_m': 0.37360684724760046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3857970462729653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:28,974 [classy] Got parameters {'Omega_m': 0.37360684724760046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:28,974 [classy] Computing new state
 2023-07-02 10:34:28,974 [classy] Setting parameters: {'Omega_m': 0.37360684724760046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.48459710060587}
 2023-07-02 10:34:29,020 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,022 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.198613
 2023-07-02 10:34:29,022 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3857970462729653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,022 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,042 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.2688
 2023-07-02 10:34:29,042 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,042 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.45974265645886486}
 2023-07-02 10:34:29,042 [prior] Evaluating prior at array([0.32529475, 0.45974266])
 2023-07-02 10:34:29,042 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,042 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45974265645886486, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,042 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,042 [classy] Re-using computed results
 2023-07-02 10:34:29,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
 2023-07-02 10:34:29,042 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45974265645886486, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,042 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,062 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09677
 2023-07-02 10:34:29,062 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,062 [model] Posterior to be computed for parameters {'Omega_m': 0.35038457977314286, 'b1': 0.4243471523145616}
 2023-07-02 10:34:29,062 [prior] Evaluating prior at array([0.35038458, 0.42434715])
 2023-07-02 10:34:29,062 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,062 [model] Got input parameters: {'Omega_m': 0.35038457977314286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4243471523145616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,062 [classy] Got parameters {'Omega_m': 0.35038457977314286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,062 [classy] Computing new state
 2023-07-02 10:34:29,062 [classy] Setting parameters: {'Omega_m': 0.35038457977314286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,108 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9304799511133}
 2023-07-02 10:34:29,108 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,110 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0806217
 2023-07-02 10:34:29,110 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4243471523145616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,110 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,133 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.46939
 2023-07-02 10:34:29,134 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,134 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.49052242499793525}
 2023-07-02 10:34:29,134 [prior] Evaluating prior at array([0.32529475, 0.49052242])
 2023-07-02 10:34:29,134 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,134 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49052242499793525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,134 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,134 [classy] Re-using computed results
 2023-07-02 10:34:29,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
 2023-07-02 10:34:29,134 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49052242499793525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,134 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,158 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.16176
 2023-07-02 10:34:29,158 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,158 [mcmc] New sample, #683:
   Omega_m:0.3252948, b1:0.4659975
 2023-07-02 10:34:29,158 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.48353683259199703}
 2023-07-02 10:34:29,158 [prior] Evaluating prior at array([0.32950282, 0.48353683])
 2023-07-02 10:34:29,158 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,158 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48353683259199703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,158 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,158 [classy] Computing new state
 2023-07-02 10:34:29,158 [classy] Setting parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
 2023-07-02 10:34:29,206 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0172389
 2023-07-02 10:34:29,207 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48353683259199703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,207 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,227 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.5947
 2023-07-02 10:34:29,227 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,227 [mcmc] New sample, #684:
   Omega_m:0.3252948, b1:0.4905224
 2023-07-02 10:34:29,228 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.46601786264738176}
 2023-07-02 10:34:29,228 [prior] Evaluating prior at array([0.32950282, 0.46601786])
 2023-07-02 10:34:29,228 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,228 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46601786264738176, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,228 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,228 [classy] Re-using computed results
 2023-07-02 10:34:29,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
 2023-07-02 10:34:29,228 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46601786264738176, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,228 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,248 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66803
 2023-07-02 10:34:29,248 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,248 [mcmc] New sample, #685:
   Omega_m:0.3295028, b1:0.4835368
 2023-07-02 10:34:29,248 [model] Posterior to be computed for parameters {'Omega_m': 0.38527693751726805, 'b1': 0.37343008195738486}
 2023-07-02 10:34:29,248 [prior] Evaluating prior at array([0.38527694, 0.37343008])
 2023-07-02 10:34:29,248 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,248 [model] Got input parameters: {'Omega_m': 0.38527693751726805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37343008195738486, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,248 [classy] Got parameters {'Omega_m': 0.38527693751726805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,248 [classy] Computing new state
 2023-07-02 10:34:29,248 [classy] Setting parameters: {'Omega_m': 0.38527693751726805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.30850046681243}
 2023-07-02 10:34:29,295 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.274456
 2023-07-02 10:34:29,297 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37343008195738486, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,297 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,316 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.5471
 2023-07-02 10:34:29,316 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,316 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.5306528399301558}
 2023-07-02 10:34:29,317 [prior] Evaluating prior at array([0.32950282, 0.53065284])
 2023-07-02 10:34:29,317 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,317 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5306528399301558, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,317 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,317 [classy] Re-using computed results
 2023-07-02 10:34:29,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
 2023-07-02 10:34:29,317 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5306528399301558, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,317 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,337 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.41924
 2023-07-02 10:34:29,337 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,337 [model] Posterior to be computed for parameters {'Omega_m': 0.2944792283675266, 'b1': 0.5241587444321636}
 2023-07-02 10:34:29,337 [prior] Evaluating prior at array([0.29447923, 0.52415874])
 2023-07-02 10:34:29,337 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,337 [model] Got input parameters: {'Omega_m': 0.2944792283675266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241587444321636, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,337 [classy] Got parameters {'Omega_m': 0.2944792283675266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,337 [classy] Computing new state
 2023-07-02 10:34:29,337 [classy] Setting parameters: {'Omega_m': 0.2944792283675266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4837030668277}
 2023-07-02 10:34:29,384 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0210083
 2023-07-02 10:34:29,386 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241587444321636, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,386 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,405 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.175151
 2023-07-02 10:34:29,405 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,405 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.40508761705818375}
 2023-07-02 10:34:29,405 [prior] Evaluating prior at array([0.32950282, 0.40508762])
 2023-07-02 10:34:29,405 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,406 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40508761705818375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,406 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,406 [classy] Re-using computed results
 2023-07-02 10:34:29,406 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
 2023-07-02 10:34:29,406 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,406 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40508761705818375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,406 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,425 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2641
 2023-07-02 10:34:29,425 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,425 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.4826445680775367}
 2023-07-02 10:34:29,425 [prior] Evaluating prior at array([0.31948703, 0.48264457])
 2023-07-02 10:34:29,425 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,425 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4826445680775367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,426 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,426 [classy] Computing new state
 2023-07-02 10:34:29,426 [classy] Setting parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
 2023-07-02 10:34:29,472 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,474 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00315786
 2023-07-02 10:34:29,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4826445680775367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,474 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,494 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57983
 2023-07-02 10:34:29,494 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,494 [mcmc] New sample, #686:
   Omega_m:0.3295028, b1:0.4660179
 2023-07-02 10:34:29,494 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.4391179894855841}
 2023-07-02 10:34:29,495 [prior] Evaluating prior at array([0.31948703, 0.43911799])
 2023-07-02 10:34:29,495 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,495 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4391179894855841, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,495 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,495 [classy] Re-using computed results
 2023-07-02 10:34:29,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
 2023-07-02 10:34:29,495 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,495 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4391179894855841, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,495 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,514 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.40503
 2023-07-02 10:34:29,514 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,515 [model] Posterior to be computed for parameters {'Omega_m': 0.3407379655303091, 'b1': 0.4473669658111894}
 2023-07-02 10:34:29,515 [prior] Evaluating prior at array([0.34073797, 0.44736697])
 2023-07-02 10:34:29,515 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,515 [model] Got input parameters: {'Omega_m': 0.3407379655303091, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4473669658111894, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,515 [classy] Got parameters {'Omega_m': 0.3407379655303091, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,515 [classy] Computing new state
 2023-07-02 10:34:29,515 [classy] Setting parameters: {'Omega_m': 0.3407379655303091, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.99066356827603}
 2023-07-02 10:34:29,562 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,563 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0459144
 2023-07-02 10:34:29,563 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4473669658111894, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,563 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,584 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.477776
 2023-07-02 10:34:29,584 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,584 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5017006218552754}
 2023-07-02 10:34:29,584 [prior] Evaluating prior at array([0.31948703, 0.50170062])
 2023-07-02 10:34:29,584 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,584 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5017006218552754, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,584 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,584 [classy] Re-using computed results
 2023-07-02 10:34:29,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
 2023-07-02 10:34:29,584 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5017006218552754, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,584 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,604 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57836
 2023-07-02 10:34:29,604 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,604 [mcmc] New sample, #687:
   Omega_m:0.319487, b1:0.4826446
 2023-07-02 10:34:29,604 [model] Posterior to be computed for parameters {'Omega_m': 0.276657160856017, 'b1': 0.5728003067398022}
 2023-07-02 10:34:29,604 [prior] Evaluating prior at array([0.27665716, 0.57280031])
 2023-07-02 10:34:29,604 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,604 [model] Got input parameters: {'Omega_m': 0.276657160856017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5728003067398022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,604 [classy] Got parameters {'Omega_m': 0.276657160856017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,604 [classy] Computing new state
 2023-07-02 10:34:29,604 [classy] Setting parameters: {'Omega_m': 0.276657160856017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.80453124860398}
 2023-07-02 10:34:29,652 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0865281
 2023-07-02 10:34:29,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5728003067398022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,653 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,673 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.90742
 2023-07-02 10:34:29,673 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,673 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5540754427149882}
 2023-07-02 10:34:29,673 [prior] Evaluating prior at array([0.31948703, 0.55407544])
 2023-07-02 10:34:29,673 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,673 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5540754427149882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,673 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,673 [classy] Re-using computed results
 2023-07-02 10:34:29,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
 2023-07-02 10:34:29,673 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5540754427149882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,673 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,694 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.19845
 2023-07-02 10:34:29,694 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,694 [model] Posterior to be computed for parameters {'Omega_m': 0.3491482447057602, 'b1': 0.45246154255359217}
 2023-07-02 10:34:29,694 [prior] Evaluating prior at array([0.34914824, 0.45246154])
 2023-07-02 10:34:29,694 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,694 [model] Got input parameters: {'Omega_m': 0.3491482447057602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45246154255359217, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,694 [classy] Got parameters {'Omega_m': 0.3491482447057602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,694 [classy] Computing new state
 2023-07-02 10:34:29,694 [classy] Setting parameters: {'Omega_m': 0.3491482447057602, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.06485011048932}
 2023-07-02 10:34:29,741 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,743 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0756772
 2023-07-02 10:34:29,743 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45246154255359217, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,743 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,762 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22454
 2023-07-02 10:34:29,762 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,762 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5133977457386354}
 2023-07-02 10:34:29,762 [prior] Evaluating prior at array([0.31948703, 0.51339775])
 2023-07-02 10:34:29,763 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,763 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133977457386354, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,763 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,763 [classy] Re-using computed results
 2023-07-02 10:34:29,763 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
 2023-07-02 10:34:29,763 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,763 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133977457386354, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,763 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,782 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58265
 2023-07-02 10:34:29,782 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,782 [mcmc] New sample, #688:
   Omega_m:0.319487, b1:0.5017006
 2023-07-02 10:34:29,782 [model] Posterior to be computed for parameters {'Omega_m': 0.29929061942482466, 'b1': 0.5469247763216256}
 2023-07-02 10:34:29,782 [prior] Evaluating prior at array([0.29929062, 0.54692478])
 2023-07-02 10:34:29,782 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,782 [model] Got input parameters: {'Omega_m': 0.29929061942482466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5469247763216256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,782 [classy] Got parameters {'Omega_m': 0.29929061942482466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,782 [classy] Computing new state
 2023-07-02 10:34:29,782 [classy] Setting parameters: {'Omega_m': 0.29929061942482466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.87803966877365}
 2023-07-02 10:34:29,829 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,831 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0112367
 2023-07-02 10:34:29,831 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5469247763216256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,831 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,851 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.526662
 2023-07-02 10:34:29,851 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,851 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5091465664976124}
 2023-07-02 10:34:29,851 [prior] Evaluating prior at array([0.31948703, 0.50914657])
 2023-07-02 10:34:29,851 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,852 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5091465664976124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,852 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,852 [classy] Re-using computed results
 2023-07-02 10:34:29,852 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
 2023-07-02 10:34:29,852 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,852 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5091465664976124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,852 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,871 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03438
 2023-07-02 10:34:29,871 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,871 [mcmc] New sample, #689:
   Omega_m:0.319487, b1:0.5133977
 2023-07-02 10:34:29,871 [model] Posterior to be computed for parameters {'Omega_m': 0.31878494751373443, 'b1': 0.5103120537531161}
 2023-07-02 10:34:29,871 [prior] Evaluating prior at array([0.31878495, 0.51031205])
 2023-07-02 10:34:29,871 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,871 [model] Got input parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5103120537531161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,871 [classy] Got parameters {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,871 [classy] Computing new state
 2023-07-02 10:34:29,871 [classy] Setting parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:29,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50867872041206}
 2023-07-02 10:34:29,918 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:29,920 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00259909
 2023-07-02 10:34:29,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5103120537531161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,920 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,941 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07543
 2023-07-02 10:34:29,941 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,941 [mcmc] New sample, #690:
   Omega_m:0.319487, b1:0.5091466
 2023-07-02 10:34:29,941 [model] Posterior to be computed for parameters {'Omega_m': 0.31878494751373443, 'b1': 0.5270728788759755}
 2023-07-02 10:34:29,941 [prior] Evaluating prior at array([0.31878495, 0.52707288])
 2023-07-02 10:34:29,942 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,942 [model] Got input parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5270728788759755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,942 [classy] Got parameters {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,942 [classy] Re-using computed results
 2023-07-02 10:34:29,942 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50867872041206}
 2023-07-02 10:34:29,942 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:29,942 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5270728788759755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,942 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:29,962 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.302792
 2023-07-02 10:34:29,962 [model] Computed derived parameters: {}
 2023-07-02 10:34:29,963 [model] Posterior to be computed for parameters {'Omega_m': 0.2940226396523268, 'b1': 0.5514187025737741}
 2023-07-02 10:34:29,963 [prior] Evaluating prior at array([0.29402264, 0.5514187 ])
 2023-07-02 10:34:29,963 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:29,963 [model] Got input parameters: {'Omega_m': 0.2940226396523268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5514187025737741, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:29,963 [classy] Got parameters {'Omega_m': 0.2940226396523268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:29,963 [classy] Computing new state
 2023-07-02 10:34:29,963 [classy] Setting parameters: {'Omega_m': 0.2940226396523268, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.54162804456496}
 2023-07-02 10:34:30,011 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221028
 2023-07-02 10:34:30,013 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5514187025737741, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,013 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,034 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.278024
 2023-07-02 10:34:30,034 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,034 [model] Posterior to be computed for parameters {'Omega_m': 0.31878494751373443, 'b1': 0.526091577755176}
 2023-07-02 10:34:30,034 [prior] Evaluating prior at array([0.31878495, 0.52609158])
 2023-07-02 10:34:30,034 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,034 [model] Got input parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.526091577755176, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,034 [classy] Got parameters {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,034 [classy] Re-using computed results
 2023-07-02 10:34:30,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50867872041206}
 2023-07-02 10:34:30,034 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,035 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.526091577755176, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,035 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,055 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.11809
 2023-07-02 10:34:30,055 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,056 [mcmc] New sample, #691:
   Omega_m:0.3187849, b1:0.5103121
 2023-07-02 10:34:30,056 [model] Posterior to be computed for parameters {'Omega_m': 0.30541203767619823, 'b1': 0.5482912657438171}
 2023-07-02 10:34:30,056 [prior] Evaluating prior at array([0.30541204, 0.54829127])
 2023-07-02 10:34:30,056 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,056 [model] Got input parameters: {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5482912657438171, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,056 [classy] Got parameters {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,056 [classy] Computing new state
 2023-07-02 10:34:30,056 [classy] Setting parameters: {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,103 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11972246776716}
 2023-07-02 10:34:30,103 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,105 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0033241
 2023-07-02 10:34:30,106 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5482912657438171, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,106 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,127 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.199584
 2023-07-02 10:34:30,127 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,127 [mcmc] New sample, #692:
   Omega_m:0.3187849, b1:0.5260916
 2023-07-02 10:34:30,127 [model] Posterior to be computed for parameters {'Omega_m': 0.30541203767619823, 'b1': 0.5314879685334746}
 2023-07-02 10:34:30,127 [prior] Evaluating prior at array([0.30541204, 0.53148797])
 2023-07-02 10:34:30,127 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,127 [model] Got input parameters: {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5314879685334746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,127 [classy] Got parameters {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,127 [classy] Re-using computed results
 2023-07-02 10:34:30,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11972246776716}
 2023-07-02 10:34:30,127 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,127 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5314879685334746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,127 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,148 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.85618
 2023-07-02 10:34:30,148 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,148 [mcmc] New sample, #693:
   Omega_m:0.305412, b1:0.5482913
 2023-07-02 10:34:30,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3134644612837745, 'b1': 0.5181205493395757}
 2023-07-02 10:34:30,148 [prior] Evaluating prior at array([0.31346446, 0.51812055])
 2023-07-02 10:34:30,148 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,149 [model] Got input parameters: {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5181205493395757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,149 [classy] Got parameters {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,149 [classy] Computing new state
 2023-07-02 10:34:30,149 [classy] Setting parameters: {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,195 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1423074138287}
 2023-07-02 10:34:30,195 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,197 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000261202
 2023-07-02 10:34:30,197 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5181205493395757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,197 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,216 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29625
 2023-07-02 10:34:30,217 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,217 [mcmc] New sample, #694:
   Omega_m:0.305412, b1:0.531488
 2023-07-02 10:34:30,217 [model] Posterior to be computed for parameters {'Omega_m': 0.3134644612837745, 'b1': 0.48878169896355106}
 2023-07-02 10:34:30,217 [prior] Evaluating prior at array([0.31346446, 0.4887817 ])
 2023-07-02 10:34:30,217 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,217 [model] Got input parameters: {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48878169896355106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,217 [classy] Got parameters {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,217 [classy] Re-using computed results
 2023-07-02 10:34:30,217 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1423074138287}
 2023-07-02 10:34:30,217 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,217 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48878169896355106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,217 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,236 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36308
 2023-07-02 10:34:30,236 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,236 [mcmc] New sample, #695:
   Omega_m:0.3134645, b1:0.5181205
 2023-07-02 10:34:30,236 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.4715384372549299}
 2023-07-02 10:34:30,236 [prior] Evaluating prior at array([0.32385166, 0.47153844])
 2023-07-02 10:34:30,237 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,237 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4715384372549299, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,237 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,237 [classy] Computing new state
 2023-07-02 10:34:30,237 [classy] Setting parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
 2023-07-02 10:34:30,283 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,285 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00790736
 2023-07-02 10:34:30,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4715384372549299, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,285 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,305 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08407
 2023-07-02 10:34:30,305 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,305 [mcmc] New sample, #696:
   Omega_m:0.3134645, b1:0.4887817
 2023-07-02 10:34:30,305 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.4869690251521813}
 2023-07-02 10:34:30,305 [prior] Evaluating prior at array([0.32385166, 0.48696903])
 2023-07-02 10:34:30,306 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,306 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4869690251521813, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,306 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,306 [classy] Re-using computed results
 2023-07-02 10:34:30,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
 2023-07-02 10:34:30,306 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4869690251521813, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,306 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,325 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50064
 2023-07-02 10:34:30,325 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,325 [mcmc] New sample, #697:
   Omega_m:0.3238517, b1:0.4715384
 2023-07-02 10:34:30,325 [model] Posterior to be computed for parameters {'Omega_m': 0.3387069686341388, 'b1': 0.46230848327303303}
 2023-07-02 10:34:30,325 [prior] Evaluating prior at array([0.33870697, 0.46230848])
 2023-07-02 10:34:30,325 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,325 [model] Got input parameters: {'Omega_m': 0.3387069686341388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46230848327303303, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,325 [classy] Got parameters {'Omega_m': 0.3387069686341388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,325 [classy] Computing new state
 2023-07-02 10:34:30,325 [classy] Setting parameters: {'Omega_m': 0.3387069686341388, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,372 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.2173698211626}
 2023-07-02 10:34:30,372 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,374 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0397677
 2023-07-02 10:34:30,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46230848327303303, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,374 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,394 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.046335
 2023-07-02 10:34:30,394 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,394 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.48199050699630613}
 2023-07-02 10:34:30,394 [prior] Evaluating prior at array([0.32385166, 0.48199051])
 2023-07-02 10:34:30,394 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,394 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48199050699630613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,394 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,394 [classy] Re-using computed results
 2023-07-02 10:34:30,394 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
 2023-07-02 10:34:30,394 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48199050699630613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,394 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,414 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50592
 2023-07-02 10:34:30,414 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,414 [mcmc] New sample, #698:
   Omega_m:0.3238517, b1:0.486969
 2023-07-02 10:34:30,414 [model] Posterior to be computed for parameters {'Omega_m': 0.34328280323589966, 'b1': 0.44973385464600296}
 2023-07-02 10:34:30,414 [prior] Evaluating prior at array([0.3432828 , 0.44973385])
 2023-07-02 10:34:30,414 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,414 [model] Got input parameters: {'Omega_m': 0.34328280323589966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44973385464600296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,414 [classy] Got parameters {'Omega_m': 0.34328280323589966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,414 [classy] Computing new state
 2023-07-02 10:34:30,414 [classy] Setting parameters: {'Omega_m': 0.34328280323589966, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.70832803029055}
 2023-07-02 10:34:30,461 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0541963
 2023-07-02 10:34:30,463 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44973385464600296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,463 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,482 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.01269
 2023-07-02 10:34:30,482 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,482 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.443187446490782}
 2023-07-02 10:34:30,482 [prior] Evaluating prior at array([0.32385166, 0.44318745])
 2023-07-02 10:34:30,482 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,483 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.443187446490782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,483 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,483 [classy] Re-using computed results
 2023-07-02 10:34:30,483 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
 2023-07-02 10:34:30,483 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,483 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.443187446490782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,483 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,502 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.88375
 2023-07-02 10:34:30,502 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,503 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.5100086464043815}
 2023-07-02 10:34:30,503 [prior] Evaluating prior at array([0.30697376, 0.51000865])
 2023-07-02 10:34:30,503 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,503 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5100086464043815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,503 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,503 [classy] Computing new state
 2023-07-02 10:34:30,503 [classy] Setting parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
 2023-07-02 10:34:30,549 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,551 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00209019
 2023-07-02 10:34:30,551 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5100086464043815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,551 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,570 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46936
 2023-07-02 10:34:30,570 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,570 [mcmc] New sample, #699:
   Omega_m:0.3238517, b1:0.4819905
 2023-07-02 10:34:30,570 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.4490814472476656}
 2023-07-02 10:34:30,570 [prior] Evaluating prior at array([0.30697376, 0.44908145])
 2023-07-02 10:34:30,571 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,571 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4490814472476656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,571 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,571 [classy] Re-using computed results
 2023-07-02 10:34:30,571 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
 2023-07-02 10:34:30,571 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,571 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4490814472476656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,571 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,590 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.31653
 2023-07-02 10:34:30,590 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,590 [model] Posterior to be computed for parameters {'Omega_m': 0.301226682593108, 'b1': 0.5195490831658292}
 2023-07-02 10:34:30,590 [prior] Evaluating prior at array([0.30122668, 0.51954908])
 2023-07-02 10:34:30,590 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,590 [model] Got input parameters: {'Omega_m': 0.301226682593108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195490831658292, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,590 [classy] Got parameters {'Omega_m': 0.301226682593108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,590 [classy] Computing new state
 2023-07-02 10:34:30,590 [classy] Setting parameters: {'Omega_m': 0.301226682593108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.63673349710393}
 2023-07-02 10:34:30,636 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,638 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00819628
 2023-07-02 10:34:30,638 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195490831658292, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,638 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,659 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67466
 2023-07-02 10:34:30,659 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,659 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.5503702809012158}
 2023-07-02 10:34:30,659 [prior] Evaluating prior at array([0.30697376, 0.55037028])
 2023-07-02 10:34:30,659 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,659 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5503702809012158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,659 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,660 [classy] Re-using computed results
 2023-07-02 10:34:30,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
 2023-07-02 10:34:30,660 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5503702809012158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,660 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,679 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.947542
 2023-07-02 10:34:30,679 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,679 [model] Posterior to be computed for parameters {'Omega_m': 0.2804158159210142, 'b1': 0.5540961452866644}
 2023-07-02 10:34:30,679 [prior] Evaluating prior at array([0.28041582, 0.55409615])
 2023-07-02 10:34:30,679 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,679 [model] Got input parameters: {'Omega_m': 0.2804158159210142, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5540961452866644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,679 [classy] Got parameters {'Omega_m': 0.2804158159210142, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,679 [classy] Computing new state
 2023-07-02 10:34:30,679 [classy] Setting parameters: {'Omega_m': 0.2804158159210142, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,725 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3045795354919}
 2023-07-02 10:34:30,726 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0686766
 2023-07-02 10:34:30,728 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5540961452866644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,728 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.14494
 2023-07-02 10:34:30,747 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,747 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.5218428830068252}
 2023-07-02 10:34:30,748 [prior] Evaluating prior at array([0.30697376, 0.52184288])
 2023-07-02 10:34:30,748 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,748 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5218428830068252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,748 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,748 [classy] Re-using computed results
 2023-07-02 10:34:30,748 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
 2023-07-02 10:34:30,748 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,748 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5218428830068252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,748 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,768 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40471
 2023-07-02 10:34:30,768 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,768 [mcmc] New sample, #700:
   Omega_m:0.3069738, b1:0.5100086
 2023-07-02 10:34:30,768 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.5154490633661637}
 2023-07-02 10:34:30,768 [prior] Evaluating prior at array([0.31082535, 0.51544906])
 2023-07-02 10:34:30,768 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,768 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5154490633661637, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,768 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,768 [classy] Computing new state
 2023-07-02 10:34:30,768 [classy] Setting parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
 2023-07-02 10:34:30,814 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,816 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000371782
 2023-07-02 10:34:30,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5154490633661637, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,816 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,836 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66454
 2023-07-02 10:34:30,836 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,836 [mcmc] New sample, #701:
   Omega_m:0.3069738, b1:0.5218429
 2023-07-02 10:34:30,836 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.5174390616925092}
 2023-07-02 10:34:30,836 [prior] Evaluating prior at array([0.31082535, 0.51743906])
 2023-07-02 10:34:30,836 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,836 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5174390616925092, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,836 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,836 [classy] Re-using computed results
 2023-07-02 10:34:30,836 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
 2023-07-02 10:34:30,836 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5174390616925092, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,836 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,856 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57237
 2023-07-02 10:34:30,856 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,856 [mcmc] New sample, #702:
   Omega_m:0.3108253, b1:0.5154491
 2023-07-02 10:34:30,856 [model] Posterior to be computed for parameters {'Omega_m': 0.2977809443202852, 'b1': 0.5390934130834051}
 2023-07-02 10:34:30,856 [prior] Evaluating prior at array([0.29778094, 0.53909341])
 2023-07-02 10:34:30,857 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,857 [model] Got input parameters: {'Omega_m': 0.2977809443202852, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5390934130834051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,857 [classy] Got parameters {'Omega_m': 0.2977809443202852, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,857 [classy] Computing new state
 2023-07-02 10:34:30,857 [classy] Setting parameters: {'Omega_m': 0.2977809443202852, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,903 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.06716352627132}
 2023-07-02 10:34:30,904 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0139598
 2023-07-02 10:34:30,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5390934130834051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,906 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.943617
 2023-07-02 10:34:30,925 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,925 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.4836044424209451}
 2023-07-02 10:34:30,925 [prior] Evaluating prior at array([0.31082535, 0.48360444])
 2023-07-02 10:34:30,926 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,926 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4836044424209451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,926 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,926 [classy] Re-using computed results
 2023-07-02 10:34:30,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
 2023-07-02 10:34:30,926 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:30,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4836044424209451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,926 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:30,945 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.26721
 2023-07-02 10:34:30,945 [model] Computed derived parameters: {}
 2023-07-02 10:34:30,945 [model] Posterior to be computed for parameters {'Omega_m': 0.3450286171604994, 'b1': 0.46065995260361836}
 2023-07-02 10:34:30,945 [prior] Evaluating prior at array([0.34502862, 0.46065995])
 2023-07-02 10:34:30,945 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:30,945 [model] Got input parameters: {'Omega_m': 0.3450286171604994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46065995260361836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,945 [classy] Got parameters {'Omega_m': 0.3450286171604994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:30,945 [classy] Computing new state
 2023-07-02 10:34:30,946 [classy] Setting parameters: {'Omega_m': 0.3450286171604994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:30,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.51574446370918}
 2023-07-02 10:34:30,992 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:30,994 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0602451
 2023-07-02 10:34:30,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46065995260361836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:30,994 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,014 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.08448
 2023-07-02 10:34:31,014 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,014 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.5056007606352946}
 2023-07-02 10:34:31,014 [prior] Evaluating prior at array([0.31082535, 0.50560076])
 2023-07-02 10:34:31,014 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,014 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5056007606352946, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,014 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,014 [classy] Re-using computed results
 2023-07-02 10:34:31,014 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
 2023-07-02 10:34:31,014 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,014 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5056007606352946, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,014 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,033 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80304
 2023-07-02 10:34:31,034 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,034 [mcmc] New sample, #703:
   Omega_m:0.3108253, b1:0.5174391
 2023-07-02 10:34:31,034 [model] Posterior to be computed for parameters {'Omega_m': 0.3166007337264668, 'b1': 0.4960133360847669}
 2023-07-02 10:34:31,034 [prior] Evaluating prior at array([0.31660073, 0.49601334])
 2023-07-02 10:34:31,034 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,034 [model] Got input parameters: {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4960133360847669, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,034 [classy] Got parameters {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,034 [classy] Computing new state
 2023-07-02 10:34:31,034 [classy] Setting parameters: {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,081 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.76764731418749}
 2023-07-02 10:34:31,081 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,082 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00123107
 2023-07-02 10:34:31,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4960133360847669, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,083 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91014
 2023-07-02 10:34:31,102 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,102 [mcmc] New sample, #704:
   Omega_m:0.3108253, b1:0.5056008
 2023-07-02 10:34:31,102 [model] Posterior to be computed for parameters {'Omega_m': 0.3166007337264668, 'b1': 0.4852188652516624}
 2023-07-02 10:34:31,102 [prior] Evaluating prior at array([0.31660073, 0.48521887])
 2023-07-02 10:34:31,103 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,103 [model] Got input parameters: {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4852188652516624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,103 [classy] Got parameters {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,103 [classy] Re-using computed results
 2023-07-02 10:34:31,103 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.76764731418749}
 2023-07-02 10:34:31,103 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4852188652516624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,103 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,125 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51715
 2023-07-02 10:34:31,125 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.510097298105304}
 2023-07-02 10:34:31,125 [prior] Evaluating prior at array([0.30811667, 0.5100973 ])
 2023-07-02 10:34:31,125 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,125 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510097298105304, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,126 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,126 [classy] Computing new state
 2023-07-02 10:34:31,126 [classy] Setting parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,173 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,173 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,175 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00138491
 2023-07-02 10:34:31,175 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510097298105304, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,175 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,195 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61658
 2023-07-02 10:34:31,195 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,195 [mcmc] New sample, #705:
   Omega_m:0.3166007, b1:0.4960133
 2023-07-02 10:34:31,195 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5643555912252121}
 2023-07-02 10:34:31,195 [prior] Evaluating prior at array([0.30811667, 0.56435559])
 2023-07-02 10:34:31,195 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,195 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5643555912252121, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,195 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,195 [classy] Re-using computed results
 2023-07-02 10:34:31,195 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,195 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,195 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5643555912252121, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,195 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,216 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.83999
 2023-07-02 10:34:31,216 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,216 [model] Posterior to be computed for parameters {'Omega_m': 0.2967318065721468, 'b1': 0.5289967322830177}
 2023-07-02 10:34:31,216 [prior] Evaluating prior at array([0.29673181, 0.52899673])
 2023-07-02 10:34:31,216 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,216 [model] Got input parameters: {'Omega_m': 0.2967318065721468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5289967322830177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,216 [classy] Got parameters {'Omega_m': 0.2967318065721468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,216 [classy] Computing new state
 2023-07-02 10:34:31,216 [classy] Setting parameters: {'Omega_m': 0.2967318065721468, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19908483675007}
 2023-07-02 10:34:31,264 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0160358
 2023-07-02 10:34:31,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5289967322830177, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,266 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,285 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.802417
 2023-07-02 10:34:31,285 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,285 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.50873016494565}
 2023-07-02 10:34:31,285 [prior] Evaluating prior at array([0.30811667, 0.50873016])
 2023-07-02 10:34:31,286 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,286 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.50873016494565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,286 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,286 [classy] Re-using computed results
 2023-07-02 10:34:31,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,286 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.50873016494565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,286 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,305 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59156
 2023-07-02 10:34:31,305 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,305 [mcmc] New sample, #706:
   Omega_m:0.3081167, b1:0.5100973
 2023-07-02 10:34:31,305 [model] Posterior to be computed for parameters {'Omega_m': 0.2996548351894904, 'b1': 0.5227772278686981}
 2023-07-02 10:34:31,306 [prior] Evaluating prior at array([0.29965484, 0.52277723])
 2023-07-02 10:34:31,306 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,306 [model] Got input parameters: {'Omega_m': 0.2996548351894904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5227772278686981, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,306 [classy] Got parameters {'Omega_m': 0.2996548351894904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,306 [classy] Computing new state
 2023-07-02 10:34:31,306 [classy] Setting parameters: {'Omega_m': 0.2996548351894904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.83253722101625}
 2023-07-02 10:34:31,352 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,354 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0106261
 2023-07-02 10:34:31,354 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5227772278686981, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,354 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,374 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39989
 2023-07-02 10:34:31,374 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,374 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.48608872944192644}
 2023-07-02 10:34:31,374 [prior] Evaluating prior at array([0.30811667, 0.48608873])
 2023-07-02 10:34:31,374 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,374 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48608872944192644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,374 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,374 [classy] Re-using computed results
 2023-07-02 10:34:31,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,374 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48608872944192644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,374 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,394 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.77009
 2023-07-02 10:34:31,394 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,394 [model] Posterior to be computed for parameters {'Omega_m': 0.2925140041986516, 'b1': 0.5346313584881449}
 2023-07-02 10:34:31,394 [prior] Evaluating prior at array([0.292514  , 0.53463136])
 2023-07-02 10:34:31,394 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,394 [model] Got input parameters: {'Omega_m': 0.2925140041986516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5346313584881449, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,394 [classy] Got parameters {'Omega_m': 0.2925140041986516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,394 [classy] Computing new state
 2023-07-02 10:34:31,394 [classy] Setting parameters: {'Omega_m': 0.2925140041986516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,441 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.73356701170118}
 2023-07-02 10:34:31,441 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0259284
 2023-07-02 10:34:31,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5346313584881449, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,443 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,464 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.365306
 2023-07-02 10:34:31,464 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,465 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5528681085570034}
 2023-07-02 10:34:31,465 [prior] Evaluating prior at array([0.30811667, 0.55286811])
 2023-07-02 10:34:31,465 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,465 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5528681085570034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,465 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,465 [classy] Re-using computed results
 2023-07-02 10:34:31,465 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,465 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,465 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5528681085570034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,465 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,484 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.82607
 2023-07-02 10:34:31,485 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,485 [model] Posterior to be computed for parameters {'Omega_m': 0.28117503396746524, 'b1': 0.5534546067043463}
 2023-07-02 10:34:31,485 [prior] Evaluating prior at array([0.28117503, 0.55345461])
 2023-07-02 10:34:31,485 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,485 [model] Got input parameters: {'Omega_m': 0.28117503396746524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5534546067043463, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,485 [classy] Got parameters {'Omega_m': 0.28117503396746524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,485 [classy] Computing new state
 2023-07-02 10:34:31,485 [classy] Setting parameters: {'Omega_m': 0.28117503396746524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.20429028540894}
 2023-07-02 10:34:31,531 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,533 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0653415
 2023-07-02 10:34:31,533 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5534546067043463, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,533 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,553 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.74969
 2023-07-02 10:34:31,553 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,553 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.4836574007959134}
 2023-07-02 10:34:31,553 [prior] Evaluating prior at array([0.30811667, 0.4836574 ])
 2023-07-02 10:34:31,553 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,553 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4836574007959134, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,553 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,553 [classy] Re-using computed results
 2023-07-02 10:34:31,553 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,553 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,553 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4836574007959134, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,553 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,574 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.420905
 2023-07-02 10:34:31,574 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,574 [model] Posterior to be computed for parameters {'Omega_m': 0.2949364406444823, 'b1': 0.5306099948565134}
 2023-07-02 10:34:31,574 [prior] Evaluating prior at array([0.29493644, 0.53060999])
 2023-07-02 10:34:31,574 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,574 [model] Got input parameters: {'Omega_m': 0.2949364406444823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5306099948565134, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,574 [classy] Got parameters {'Omega_m': 0.2949364406444823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,574 [classy] Computing new state
 2023-07-02 10:34:31,574 [classy] Setting parameters: {'Omega_m': 0.2949364406444823, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,621 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.42578366646626}
 2023-07-02 10:34:31,621 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,623 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0199418
 2023-07-02 10:34:31,623 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5306099948565134, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,623 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,642 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.31542
 2023-07-02 10:34:31,642 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,642 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5105159297180544}
 2023-07-02 10:34:31,643 [prior] Evaluating prior at array([0.30811667, 0.51051593])
 2023-07-02 10:34:31,643 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,643 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5105159297180544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,643 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,643 [classy] Re-using computed results
 2023-07-02 10:34:31,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,643 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5105159297180544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,643 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,664 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62226
 2023-07-02 10:34:31,664 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,664 [mcmc] New sample, #707:
   Omega_m:0.3081167, b1:0.5087302
 2023-07-02 10:34:31,664 [model] Posterior to be computed for parameters {'Omega_m': 0.23479711361411262, 'b1': 0.63223000005531}
 2023-07-02 10:34:31,664 [prior] Evaluating prior at array([0.23479711, 0.63223   ])
 2023-07-02 10:34:31,665 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,665 [model] Got input parameters: {'Omega_m': 0.23479711361411262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.63223000005531, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,665 [classy] Got parameters {'Omega_m': 0.23479711361411262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,665 [classy] Computing new state
 2023-07-02 10:34:31,665 [classy] Setting parameters: {'Omega_m': 0.23479711361411262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.79696486450297}
 2023-07-02 10:34:31,712 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,713 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.456555
 2023-07-02 10:34:31,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.63223000005531, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,714 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,733 [fs_likelihood.fslikelihood] Computed log-likelihood = -48.1031
 2023-07-02 10:34:31,733 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,733 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.46404131797135123}
 2023-07-02 10:34:31,733 [prior] Evaluating prior at array([0.30811667, 0.46404132])
 2023-07-02 10:34:31,733 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,733 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46404131797135123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,733 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,733 [classy] Re-using computed results
 2023-07-02 10:34:31,733 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,733 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,733 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46404131797135123, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,733 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,753 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.43617
 2023-07-02 10:34:31,753 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,753 [model] Posterior to be computed for parameters {'Omega_m': 0.2368383403796161, 'b1': 0.6288414632403045}
 2023-07-02 10:34:31,753 [prior] Evaluating prior at array([0.23683834, 0.62884146])
 2023-07-02 10:34:31,753 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,753 [model] Got input parameters: {'Omega_m': 0.2368383403796161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6288414632403045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,753 [classy] Got parameters {'Omega_m': 0.2368383403796161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,753 [classy] Computing new state
 2023-07-02 10:34:31,753 [classy] Setting parameters: {'Omega_m': 0.2368383403796161, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,800 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.4851181864174}
 2023-07-02 10:34:31,800 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,802 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.430314
 2023-07-02 10:34:31,802 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6288414632403045, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,802 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,822 [fs_likelihood.fslikelihood] Computed log-likelihood = -45.157
 2023-07-02 10:34:31,822 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,822 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.46218718916270973}
 2023-07-02 10:34:31,822 [prior] Evaluating prior at array([0.30811667, 0.46218719])
 2023-07-02 10:34:31,822 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,822 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46218718916270973, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,822 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,823 [classy] Re-using computed results
 2023-07-02 10:34:31,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,823 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,823 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46218718916270973, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,823 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,842 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.89405
 2023-07-02 10:34:31,842 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,842 [model] Posterior to be computed for parameters {'Omega_m': 0.27419570889761025, 'b1': 0.5668263943247615}
 2023-07-02 10:34:31,842 [prior] Evaluating prior at array([0.27419571, 0.56682639])
 2023-07-02 10:34:31,842 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,842 [model] Got input parameters: {'Omega_m': 0.27419570889761025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5668263943247615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,843 [classy] Got parameters {'Omega_m': 0.27419570889761025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,843 [classy] Computing new state
 2023-07-02 10:34:31,843 [classy] Setting parameters: {'Omega_m': 0.27419570889761025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13508043764273}
 2023-07-02 10:34:31,890 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.099449
 2023-07-02 10:34:31,892 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5668263943247615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,892 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,912 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.43132
 2023-07-02 10:34:31,912 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,912 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5067768409787212}
 2023-07-02 10:34:31,912 [prior] Evaluating prior at array([0.30811667, 0.50677684])
 2023-07-02 10:34:31,912 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,912 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5067768409787212, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,912 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,912 [classy] Re-using computed results
 2023-07-02 10:34:31,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:31,912 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:31,912 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5067768409787212, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,912 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:31,932 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53868
 2023-07-02 10:34:31,932 [model] Computed derived parameters: {}
 2023-07-02 10:34:31,932 [mcmc] New sample, #708:
   Omega_m:0.3081167, b1:0.5105159
 2023-07-02 10:34:31,932 [model] Posterior to be computed for parameters {'Omega_m': 0.2904005307311574, 'b1': 0.5361865044145034}
 2023-07-02 10:34:31,932 [prior] Evaluating prior at array([0.29040053, 0.5361865 ])
 2023-07-02 10:34:31,932 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:31,933 [model] Got input parameters: {'Omega_m': 0.2904005307311574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5361865044145034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,933 [classy] Got parameters {'Omega_m': 0.2904005307311574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:31,933 [classy] Computing new state
 2023-07-02 10:34:31,933 [classy] Setting parameters: {'Omega_m': 0.2904005307311574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:31,979 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.00390611815547}
 2023-07-02 10:34:31,979 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:31,981 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0318344
 2023-07-02 10:34:31,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5361865044145034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:31,981 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,000 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10971
 2023-07-02 10:34:32,001 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,001 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5015402797432746}
 2023-07-02 10:34:32,001 [prior] Evaluating prior at array([0.30811667, 0.50154028])
 2023-07-02 10:34:32,001 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,001 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015402797432746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,001 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,001 [classy] Re-using computed results
 2023-07-02 10:34:32,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
 2023-07-02 10:34:32,001 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,001 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015402797432746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,001 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,031 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29824
 2023-07-02 10:34:32,031 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,031 [mcmc] New sample, #709:
   Omega_m:0.3081167, b1:0.5067768
 2023-07-02 10:34:32,031 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.49548677958578335}
 2023-07-02 10:34:32,031 [prior] Evaluating prior at array([0.31176325, 0.49548678])
 2023-07-02 10:34:32,031 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,031 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49548677958578335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,031 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,031 [classy] Computing new state
 2023-07-02 10:34:32,031 [classy] Setting parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,078 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,080 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000234284
 2023-07-02 10:34:32,080 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49548677958578335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,080 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,099 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55308
 2023-07-02 10:34:32,100 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,100 [mcmc] New sample, #710:
   Omega_m:0.3081167, b1:0.5015403
 2023-07-02 10:34:32,100 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5101236677176169}
 2023-07-02 10:34:32,100 [prior] Evaluating prior at array([0.31176325, 0.51012367])
 2023-07-02 10:34:32,100 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,100 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5101236677176169, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,100 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,100 [classy] Re-using computed results
 2023-07-02 10:34:32,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,100 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,100 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5101236677176169, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,100 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,120 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81868
 2023-07-02 10:34:32,120 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,120 [mcmc] New sample, #711:
   Omega_m:0.3117632, b1:0.4954868
 2023-07-02 10:34:32,120 [model] Posterior to be computed for parameters {'Omega_m': 0.32828814355318114, 'b1': 0.4826915307740906}
 2023-07-02 10:34:32,120 [prior] Evaluating prior at array([0.32828814, 0.48269153])
 2023-07-02 10:34:32,120 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,120 [model] Got input parameters: {'Omega_m': 0.32828814355318114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4826915307740906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,121 [classy] Got parameters {'Omega_m': 0.32828814355318114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,121 [classy] Computing new state
 2023-07-02 10:34:32,121 [classy] Setting parameters: {'Omega_m': 0.32828814355318114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4000417051186}
 2023-07-02 10:34:32,169 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,171 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0149366
 2023-07-02 10:34:32,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4826915307740906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,171 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,191 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90039
 2023-07-02 10:34:32,191 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,191 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5410847544256415}
 2023-07-02 10:34:32,191 [prior] Evaluating prior at array([0.31176325, 0.54108475])
 2023-07-02 10:34:32,191 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,191 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5410847544256415, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,191 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,191 [classy] Re-using computed results
 2023-07-02 10:34:32,191 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,191 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,191 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5410847544256415, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,191 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,211 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.521664
 2023-07-02 10:34:32,211 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,211 [model] Posterior to be computed for parameters {'Omega_m': 0.2982962487810565, 'b1': 0.5324795510492645}
 2023-07-02 10:34:32,211 [prior] Evaluating prior at array([0.29829625, 0.53247955])
 2023-07-02 10:34:32,211 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,211 [model] Got input parameters: {'Omega_m': 0.2982962487810565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5324795510492645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,211 [classy] Got parameters {'Omega_m': 0.2982962487810565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,211 [classy] Computing new state
 2023-07-02 10:34:32,211 [classy] Setting parameters: {'Omega_m': 0.2982962487810565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,258 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0025145746044}
 2023-07-02 10:34:32,258 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,260 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129954
 2023-07-02 10:34:32,260 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5324795510492645, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,260 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,280 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.195
 2023-07-02 10:34:32,280 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,281 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5059570422716518}
 2023-07-02 10:34:32,281 [prior] Evaluating prior at array([0.31176325, 0.50595704])
 2023-07-02 10:34:32,281 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,281 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5059570422716518, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,281 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,281 [classy] Re-using computed results
 2023-07-02 10:34:32,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,281 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,281 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5059570422716518, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,281 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,300 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85949
 2023-07-02 10:34:32,300 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,300 [mcmc] New sample, #712:
   Omega_m:0.3117632, b1:0.5101237
 2023-07-02 10:34:32,300 [model] Posterior to be computed for parameters {'Omega_m': 0.34717089550883595, 'b1': 0.4471786084581791}
 2023-07-02 10:34:32,300 [prior] Evaluating prior at array([0.3471709 , 0.44717861])
 2023-07-02 10:34:32,301 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,301 [model] Got input parameters: {'Omega_m': 0.34717089550883595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4471786084581791, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,301 [classy] Got parameters {'Omega_m': 0.34717089550883595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,301 [classy] Computing new state
 2023-07-02 10:34:32,301 [classy] Setting parameters: {'Omega_m': 0.34717089550883595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,347 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2806612747171}
 2023-07-02 10:34:32,347 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,349 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0680683
 2023-07-02 10:34:32,349 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4471786084581791, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,349 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,368 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.16323
 2023-07-02 10:34:32,369 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,369 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.4982521990034722}
 2023-07-02 10:34:32,369 [prior] Evaluating prior at array([0.31176325, 0.4982522 ])
 2023-07-02 10:34:32,369 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,369 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4982521990034722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,369 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,369 [classy] Re-using computed results
 2023-07-02 10:34:32,369 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,369 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,369 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4982521990034722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,369 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,389 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69019
 2023-07-02 10:34:32,389 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,389 [mcmc] New sample, #713:
   Omega_m:0.3117632, b1:0.505957
 2023-07-02 10:34:32,389 [model] Posterior to be computed for parameters {'Omega_m': 0.38789090490987443, 'b1': 0.37187654703929873}
 2023-07-02 10:34:32,389 [prior] Evaluating prior at array([0.3878909 , 0.37187655])
 2023-07-02 10:34:32,389 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,390 [model] Got input parameters: {'Omega_m': 0.38789090490987443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37187654703929873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,390 [classy] Got parameters {'Omega_m': 0.38789090490987443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,390 [classy] Computing new state
 2023-07-02 10:34:32,390 [classy] Setting parameters: {'Omega_m': 0.38789090490987443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.0496529909523}
 2023-07-02 10:34:32,436 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.292836
 2023-07-02 10:34:32,438 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37187654703929873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,438 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,457 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.8613
 2023-07-02 10:34:32,457 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,457 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.4685827753252232}
 2023-07-02 10:34:32,457 [prior] Evaluating prior at array([0.31176325, 0.46858278])
 2023-07-02 10:34:32,458 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,458 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4685827753252232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,458 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,458 [classy] Re-using computed results
 2023-07-02 10:34:32,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,458 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,458 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4685827753252232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,458 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,478 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.80685
 2023-07-02 10:34:32,478 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,479 [model] Posterior to be computed for parameters {'Omega_m': 0.3384639431268244, 'b1': 0.4539277343381398}
 2023-07-02 10:34:32,479 [prior] Evaluating prior at array([0.33846394, 0.45392773])
 2023-07-02 10:34:32,479 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,479 [model] Got input parameters: {'Omega_m': 0.3384639431268244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4539277343381398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,479 [classy] Got parameters {'Omega_m': 0.3384639431268244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,479 [classy] Computing new state
 2023-07-02 10:34:32,479 [classy] Setting parameters: {'Omega_m': 0.3384639431268244, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,525 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.24457964941573}
 2023-07-02 10:34:32,525 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,527 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0390601
 2023-07-02 10:34:32,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4539277343381398, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,527 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,546 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.125242
 2023-07-02 10:34:32,546 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,546 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.45529118162470056}
 2023-07-02 10:34:32,546 [prior] Evaluating prior at array([0.31176325, 0.45529118])
 2023-07-02 10:34:32,546 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,546 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45529118162470056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,547 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,547 [classy] Re-using computed results
 2023-07-02 10:34:32,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,547 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45529118162470056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,547 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.76332
 2023-07-02 10:34:32,566 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,566 [model] Posterior to be computed for parameters {'Omega_m': 0.26343683428272374, 'b1': 0.578476424732639}
 2023-07-02 10:34:32,566 [prior] Evaluating prior at array([0.26343683, 0.57847642])
 2023-07-02 10:34:32,566 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,566 [model] Got input parameters: {'Omega_m': 0.26343683428272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.578476424732639, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,566 [classy] Got parameters {'Omega_m': 0.26343683428272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,566 [classy] Computing new state
 2023-07-02 10:34:32,566 [classy] Setting parameters: {'Omega_m': 0.26343683428272374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.61020467698955}
 2023-07-02 10:34:32,612 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,614 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.167897
 2023-07-02 10:34:32,614 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.578476424732639, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,614 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,634 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.327
 2023-07-02 10:34:32,634 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,635 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5002750289201412}
 2023-07-02 10:34:32,635 [prior] Evaluating prior at array([0.31176325, 0.50027503])
 2023-07-02 10:34:32,635 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,635 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5002750289201412, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,635 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,635 [classy] Re-using computed results
 2023-07-02 10:34:32,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,635 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5002750289201412, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,635 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,654 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76509
 2023-07-02 10:34:32,654 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,654 [mcmc] New sample, #714:
   Omega_m:0.3117632, b1:0.4982522
 2023-07-02 10:34:32,654 [model] Posterior to be computed for parameters {'Omega_m': 0.3230832833558424, 'b1': 0.48148321587090254}
 2023-07-02 10:34:32,654 [prior] Evaluating prior at array([0.32308328, 0.48148322])
 2023-07-02 10:34:32,655 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,655 [model] Got input parameters: {'Omega_m': 0.3230832833558424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48148321587090254, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,655 [classy] Got parameters {'Omega_m': 0.3230832833558424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,655 [classy] Computing new state
 2023-07-02 10:34:32,655 [classy] Setting parameters: {'Omega_m': 0.3230832833558424, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.00363016026483}
 2023-07-02 10:34:32,701 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,703 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00691345
 2023-07-02 10:34:32,703 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48148321587090254, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,703 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,723 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54041
 2023-07-02 10:34:32,723 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,723 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5068111191219317}
 2023-07-02 10:34:32,723 [prior] Evaluating prior at array([0.31176325, 0.50681112])
 2023-07-02 10:34:32,723 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,723 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5068111191219317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,724 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,724 [classy] Re-using computed results
 2023-07-02 10:34:32,724 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,724 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5068111191219317, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,724 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,744 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85876
 2023-07-02 10:34:32,744 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,744 [mcmc] New sample, #715:
   Omega_m:0.3117632, b1:0.500275
 2023-07-02 10:34:32,744 [model] Posterior to be computed for parameters {'Omega_m': 0.3273167556003784, 'b1': 0.48099153395136496}
 2023-07-02 10:34:32,744 [prior] Evaluating prior at array([0.32731676, 0.48099153])
 2023-07-02 10:34:32,744 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,744 [model] Got input parameters: {'Omega_m': 0.3273167556003784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48099153395136496, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,744 [classy] Got parameters {'Omega_m': 0.3273167556003784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,744 [classy] Computing new state
 2023-07-02 10:34:32,744 [classy] Setting parameters: {'Omega_m': 0.3273167556003784, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.51203535192877}
 2023-07-02 10:34:32,791 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132114
 2023-07-02 10:34:32,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48099153395136496, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,792 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,812 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11713
 2023-07-02 10:34:32,812 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,812 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5308182268463638}
 2023-07-02 10:34:32,812 [prior] Evaluating prior at array([0.31176325, 0.53081823])
 2023-07-02 10:34:32,812 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,812 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308182268463638, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,812 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,812 [classy] Re-using computed results
 2023-07-02 10:34:32,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,812 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308182268463638, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,812 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,832 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.19381
 2023-07-02 10:34:32,832 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,832 [model] Posterior to be computed for parameters {'Omega_m': 0.28258260765916193, 'b1': 0.5552524194876783}
 2023-07-02 10:34:32,832 [prior] Evaluating prior at array([0.28258261, 0.55525242])
 2023-07-02 10:34:32,833 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,833 [model] Got input parameters: {'Omega_m': 0.28258260765916193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5552524194876783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,833 [classy] Got parameters {'Omega_m': 0.28258260765916193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,833 [classy] Computing new state
 2023-07-02 10:34:32,833 [classy] Setting parameters: {'Omega_m': 0.28258260765916193, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.01896385615075}
 2023-07-02 10:34:32,879 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0593951
 2023-07-02 10:34:32,881 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5552524194876783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,881 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,901 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.96658
 2023-07-02 10:34:32,901 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,901 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5219705513883467}
 2023-07-02 10:34:32,901 [prior] Evaluating prior at array([0.31176325, 0.52197055])
 2023-07-02 10:34:32,901 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,901 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5219705513883467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,901 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,901 [classy] Re-using computed results
 2023-07-02 10:34:32,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
 2023-07-02 10:34:32,901 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5219705513883467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,901 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,920 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18283
 2023-07-02 10:34:32,920 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,920 [mcmc] New sample, #716:
   Omega_m:0.3117632, b1:0.5068111
 2023-07-02 10:34:32,920 [model] Posterior to be computed for parameters {'Omega_m': 0.3139702786750449, 'b1': 0.5183067742722361}
 2023-07-02 10:34:32,920 [prior] Evaluating prior at array([0.31397028, 0.51830677])
 2023-07-02 10:34:32,921 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,921 [model] Got input parameters: {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183067742722361, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,921 [classy] Got parameters {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,921 [classy] Computing new state
 2023-07-02 10:34:32,921 [classy] Setting parameters: {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:32,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08165482317673}
 2023-07-02 10:34:32,967 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:32,969 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000337375
 2023-07-02 10:34:32,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183067742722361, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,969 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:32,989 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20979
 2023-07-02 10:34:32,989 [model] Computed derived parameters: {}
 2023-07-02 10:34:32,989 [mcmc] New sample, #717:
   Omega_m:0.3117632, b1:0.5219706
 2023-07-02 10:34:32,989 [model] Posterior to be computed for parameters {'Omega_m': 0.3139702786750449, 'b1': 0.5299038224053864}
 2023-07-02 10:34:32,989 [prior] Evaluating prior at array([0.31397028, 0.52990382])
 2023-07-02 10:34:32,989 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:32,989 [model] Got input parameters: {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5299038224053864, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,989 [classy] Got parameters {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:32,990 [classy] Re-using computed results
 2023-07-02 10:34:32,990 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08165482317673}
 2023-07-02 10:34:32,990 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:32,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5299038224053864, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:32,990 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,009 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.795885
 2023-07-02 10:34:33,009 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,009 [model] Posterior to be computed for parameters {'Omega_m': 0.3074855928282414, 'b1': 0.529071671684415}
 2023-07-02 10:34:33,009 [prior] Evaluating prior at array([0.30748559, 0.52907167])
 2023-07-02 10:34:33,009 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,009 [model] Got input parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.529071671684415, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,009 [classy] Got parameters {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,009 [classy] Computing new state
 2023-07-02 10:34:33,009 [classy] Setting parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8658817262105}
 2023-07-02 10:34:33,056 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,058 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00175379
 2023-07-02 10:34:33,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.529071671684415, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,058 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,078 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.96424
 2023-07-02 10:34:33,078 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,078 [mcmc] New sample, #718:
   Omega_m:0.3139703, b1:0.5183068
 2023-07-02 10:34:33,078 [model] Posterior to be computed for parameters {'Omega_m': 0.3074855928282414, 'b1': 0.5174440260227556}
 2023-07-02 10:34:33,078 [prior] Evaluating prior at array([0.30748559, 0.51744403])
 2023-07-02 10:34:33,078 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,078 [model] Got input parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5174440260227556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,078 [classy] Got parameters {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,079 [classy] Re-using computed results
 2023-07-02 10:34:33,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8658817262105}
 2023-07-02 10:34:33,079 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,079 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5174440260227556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,079 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,098 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54988
 2023-07-02 10:34:33,099 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,099 [mcmc] New sample, #719:
   Omega_m:0.3074856, b1:0.5290717
 2023-07-02 10:34:33,099 [model] Posterior to be computed for parameters {'Omega_m': 0.3398000390052746, 'b1': 0.46380045619606786}
 2023-07-02 10:34:33,099 [prior] Evaluating prior at array([0.33980004, 0.46380046])
 2023-07-02 10:34:33,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,099 [model] Got input parameters: {'Omega_m': 0.3398000390052746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46380045619606786, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,099 [classy] Got parameters {'Omega_m': 0.3398000390052746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,099 [classy] Computing new state
 2023-07-02 10:34:33,099 [classy] Setting parameters: {'Omega_m': 0.3398000390052746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,148 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.09520645961544}
 2023-07-02 10:34:33,148 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,150 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0430242
 2023-07-02 10:34:33,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46380045619606786, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,150 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,169 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.334803
 2023-07-02 10:34:33,169 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,169 [model] Posterior to be computed for parameters {'Omega_m': 0.3074855928282414, 'b1': 0.512666647486877}
 2023-07-02 10:34:33,169 [prior] Evaluating prior at array([0.30748559, 0.51266665])
 2023-07-02 10:34:33,170 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,170 [model] Got input parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.512666647486877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,170 [classy] Got parameters {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,170 [classy] Re-using computed results
 2023-07-02 10:34:33,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8658817262105}
 2023-07-02 10:34:33,170 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,170 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.512666647486877, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,170 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57713
 2023-07-02 10:34:33,190 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,190 [mcmc] New sample, #720:
   Omega_m:0.3074856, b1:0.517444
 2023-07-02 10:34:33,190 [mcmc] Learn + convergence test @ 720 samples accepted.
 2023-07-02 10:34:33,190 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:33,195 [mcmc]  - Acceptance rate: 0.478
 2023-07-02 10:34:33,196 [mcmc]  - Condition number = 14.3905
 2023-07-02 10:34:33,196 [mcmc]  - Eigenvalues = array([0.00280571, 0.04037571])
 2023-07-02 10:34:33,196 [mcmc]  - Convergence of means: R-1 = 0.040376 after 576 accepted steps
 2023-07-02 10:34:33,196 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:33,196 [mcmc] array([[ 0.00010025, -0.00017427],
       [-0.00017427,  0.0004754 ]])
 2023-07-02 10:34:33,206 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:33,206 [model] Posterior to be computed for parameters {'Omega_m': 0.3226206442669289, 'b1': 0.48635618190946245}
 2023-07-02 10:34:33,206 [prior] Evaluating prior at array([0.32262064, 0.48635618])
 2023-07-02 10:34:33,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,206 [model] Got input parameters: {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48635618190946245, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,206 [classy] Got parameters {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,206 [classy] Computing new state
 2023-07-02 10:34:33,207 [classy] Setting parameters: {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,254 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.05770076482432}
 2023-07-02 10:34:33,254 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,256 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00634728
 2023-07-02 10:34:33,256 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48635618190946245, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,256 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,276 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62595
 2023-07-02 10:34:33,276 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,276 [mcmc] New sample, #721:
   Omega_m:0.3074856, b1:0.5126666
 2023-07-02 10:34:33,276 [model] Posterior to be computed for parameters {'Omega_m': 0.3226206442669289, 'b1': 0.4580917743938249}
 2023-07-02 10:34:33,276 [prior] Evaluating prior at array([0.32262064, 0.45809177])
 2023-07-02 10:34:33,276 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,277 [model] Got input parameters: {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4580917743938249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,277 [classy] Got parameters {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,277 [classy] Re-using computed results
 2023-07-02 10:34:33,277 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.05770076482432}
 2023-07-02 10:34:33,277 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,277 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4580917743938249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,277 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,297 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.494035
 2023-07-02 10:34:33,297 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,297 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5246855112265184}
 2023-07-02 10:34:33,297 [prior] Evaluating prior at array([0.30057176, 0.52468551])
 2023-07-02 10:34:33,298 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,298 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5246855112265184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,298 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,298 [classy] Computing new state
 2023-07-02 10:34:33,298 [classy] Setting parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
 2023-07-02 10:34:33,345 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00916818
 2023-07-02 10:34:33,347 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5246855112265184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,347 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.63956
 2023-07-02 10:34:33,366 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,366 [mcmc] New sample, #722:
   Omega_m:0.3226206, b1:0.4863562
 2023-07-02 10:34:33,366 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5133629000237084}
 2023-07-02 10:34:33,366 [prior] Evaluating prior at array([0.30057176, 0.5133629 ])
 2023-07-02 10:34:33,366 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,366 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133629000237084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,366 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,366 [classy] Re-using computed results
 2023-07-02 10:34:33,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
 2023-07-02 10:34:33,367 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133629000237084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,367 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,386 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.1929
 2023-07-02 10:34:33,386 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,387 [mcmc] New sample, #723:
   Omega_m:0.3005718, b1:0.5246855
 2023-07-02 10:34:33,387 [model] Posterior to be computed for parameters {'Omega_m': 0.286652445967754, 'b1': 0.5375599550447375}
 2023-07-02 10:34:33,387 [prior] Evaluating prior at array([0.28665245, 0.53755996])
 2023-07-02 10:34:33,387 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,387 [model] Got input parameters: {'Omega_m': 0.286652445967754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375599550447375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,387 [classy] Got parameters {'Omega_m': 0.286652445967754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,387 [classy] Computing new state
 2023-07-02 10:34:33,387 [classy] Setting parameters: {'Omega_m': 0.286652445967754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.48753642130387}
 2023-07-02 10:34:33,433 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0439068
 2023-07-02 10:34:33,435 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375599550447375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,435 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,454 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.756
 2023-07-02 10:34:33,454 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,455 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5382970998964345}
 2023-07-02 10:34:33,455 [prior] Evaluating prior at array([0.30057176, 0.5382971 ])
 2023-07-02 10:34:33,455 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,455 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5382970998964345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,455 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,455 [classy] Re-using computed results
 2023-07-02 10:34:33,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
 2023-07-02 10:34:33,455 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,455 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5382970998964345, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,455 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,474 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2777
 2023-07-02 10:34:33,475 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,475 [mcmc] New sample, #724:
   Omega_m:0.3005718, b1:0.5133629
 2023-07-02 10:34:33,475 [model] Posterior to be computed for parameters {'Omega_m': 0.2605877872821915, 'b1': 0.6078044274270509}
 2023-07-02 10:34:33,475 [prior] Evaluating prior at array([0.26058779, 0.60780443])
 2023-07-02 10:34:33,475 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,475 [model] Got input parameters: {'Omega_m': 0.2605877872821915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6078044274270509, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,475 [classy] Got parameters {'Omega_m': 0.2605877872821915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,475 [classy] Computing new state
 2023-07-02 10:34:33,475 [classy] Setting parameters: {'Omega_m': 0.2605877872821915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,522 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.00930431794265}
 2023-07-02 10:34:33,522 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,524 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.189424
 2023-07-02 10:34:33,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6078044274270509, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,524 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,544 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.3492
 2023-07-02 10:34:33,544 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,544 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5531083626864187}
 2023-07-02 10:34:33,544 [prior] Evaluating prior at array([0.30057176, 0.55310836])
 2023-07-02 10:34:33,544 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,544 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5531083626864187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,544 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,544 [classy] Re-using computed results
 2023-07-02 10:34:33,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
 2023-07-02 10:34:33,544 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5531083626864187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,544 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,564 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.275504
 2023-07-02 10:34:33,564 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,564 [model] Posterior to be computed for parameters {'Omega_m': 0.31768967802768583, 'b1': 0.5085396619949156}
 2023-07-02 10:34:33,564 [prior] Evaluating prior at array([0.31768968, 0.50853966])
 2023-07-02 10:34:33,564 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,564 [model] Got input parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5085396619949156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,564 [classy] Got parameters {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,564 [classy] Computing new state
 2023-07-02 10:34:33,564 [classy] Setting parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6383380396427}
 2023-07-02 10:34:33,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00184278
 2023-07-02 10:34:33,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5085396619949156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,613 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,632 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42392
 2023-07-02 10:34:33,632 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,632 [mcmc] New sample, #725:
   Omega_m:0.3005718, b1:0.5382971
 2023-07-02 10:34:33,632 [model] Posterior to be computed for parameters {'Omega_m': 0.31768967802768583, 'b1': 0.5052693608425649}
 2023-07-02 10:34:33,632 [prior] Evaluating prior at array([0.31768968, 0.50526936])
 2023-07-02 10:34:33,632 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,632 [model] Got input parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5052693608425649, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,633 [classy] Got parameters {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,633 [classy] Re-using computed results
 2023-07-02 10:34:33,633 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6383380396427}
 2023-07-02 10:34:33,633 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5052693608425649, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,633 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,653 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62967
 2023-07-02 10:34:33,653 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,653 [mcmc] New sample, #726:
   Omega_m:0.3176897, b1:0.5085397
 2023-07-02 10:34:33,653 [model] Posterior to be computed for parameters {'Omega_m': 0.3349306489081108, 'b1': 0.4752980077415698}
 2023-07-02 10:34:33,653 [prior] Evaluating prior at array([0.33493065, 0.47529801])
 2023-07-02 10:34:33,653 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,653 [model] Got input parameters: {'Omega_m': 0.3349306489081108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4752980077415698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,653 [classy] Got parameters {'Omega_m': 0.3349306489081108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,653 [classy] Computing new state
 2023-07-02 10:34:33,653 [classy] Setting parameters: {'Omega_m': 0.3349306489081108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.64218396451753}
 2023-07-02 10:34:33,700 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.029454
 2023-07-02 10:34:33,702 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4752980077415698, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,702 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,721 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.572115
 2023-07-02 10:34:33,721 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,721 [model] Posterior to be computed for parameters {'Omega_m': 0.31768967802768583, 'b1': 0.4978938737703222}
 2023-07-02 10:34:33,721 [prior] Evaluating prior at array([0.31768968, 0.49789387])
 2023-07-02 10:34:33,722 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,722 [model] Got input parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4978938737703222, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,722 [classy] Got parameters {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,722 [classy] Re-using computed results
 2023-07-02 10:34:33,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6383380396427}
 2023-07-02 10:34:33,722 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,722 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4978938737703222, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,722 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,741 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87604
 2023-07-02 10:34:33,741 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,742 [mcmc] New sample, #727:
   Omega_m:0.3176897, b1:0.5052694
 2023-07-02 10:34:33,742 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.49372002270603094}
 2023-07-02 10:34:33,742 [prior] Evaluating prior at array([0.32009068, 0.49372002])
 2023-07-02 10:34:33,742 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,742 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49372002270603094, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,742 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,742 [classy] Computing new state
 2023-07-02 10:34:33,742 [classy] Setting parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,788 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
 2023-07-02 10:34:33,788 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,790 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00368414
 2023-07-02 10:34:33,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49372002270603094, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,790 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,810 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77604
 2023-07-02 10:34:33,810 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,810 [mcmc] New sample, #728:
   Omega_m:0.3176897, b1:0.4978939
 2023-07-02 10:34:33,810 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.5292142793968342}
 2023-07-02 10:34:33,810 [prior] Evaluating prior at array([0.32009068, 0.52921428])
 2023-07-02 10:34:33,810 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,810 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5292142793968342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,810 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,810 [classy] Re-using computed results
 2023-07-02 10:34:33,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
 2023-07-02 10:34:33,810 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5292142793968342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,810 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.2917
 2023-07-02 10:34:33,830 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,830 [model] Posterior to be computed for parameters {'Omega_m': 0.3451827299049178, 'b1': 0.45010051158953845}
 2023-07-02 10:34:33,830 [prior] Evaluating prior at array([0.34518273, 0.45010051])
 2023-07-02 10:34:33,830 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,830 [model] Got input parameters: {'Omega_m': 0.3451827299049178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45010051158953845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,830 [classy] Got parameters {'Omega_m': 0.3451827299049178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,830 [classy] Computing new state
 2023-07-02 10:34:33,830 [classy] Setting parameters: {'Omega_m': 0.3451827299049178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,876 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.49878836173818}
 2023-07-02 10:34:33,877 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,878 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0607932
 2023-07-02 10:34:33,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45010051158953845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,878 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,898 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.57891
 2023-07-02 10:34:33,898 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,898 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.5676139708129573}
 2023-07-02 10:34:33,899 [prior] Evaluating prior at array([0.32009068, 0.56761397])
 2023-07-02 10:34:33,899 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,899 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5676139708129573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,899 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,899 [classy] Re-using computed results
 2023-07-02 10:34:33,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
 2023-07-02 10:34:33,899 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,899 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5676139708129573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,899 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,918 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.3145
 2023-07-02 10:34:33,918 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,918 [model] Posterior to be computed for parameters {'Omega_m': 0.3483233719210537, 'b1': 0.44464088338865193}
 2023-07-02 10:34:33,918 [prior] Evaluating prior at array([0.34832337, 0.44464088])
 2023-07-02 10:34:33,919 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,919 [model] Got input parameters: {'Omega_m': 0.3483233719210537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44464088338865193, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,919 [classy] Got parameters {'Omega_m': 0.3483233719210537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,919 [classy] Computing new state
 2023-07-02 10:34:33,919 [classy] Setting parameters: {'Omega_m': 0.3483233719210537, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:33,965 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.15474376189673}
 2023-07-02 10:34:33,965 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:33,967 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0724579
 2023-07-02 10:34:33,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44464088338865193, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,967 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:33,987 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.49276
 2023-07-02 10:34:33,987 [model] Computed derived parameters: {}
 2023-07-02 10:34:33,987 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.5134282294216049}
 2023-07-02 10:34:33,987 [prior] Evaluating prior at array([0.32009068, 0.51342823])
 2023-07-02 10:34:33,987 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:33,987 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5134282294216049, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,987 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:33,988 [classy] Re-using computed results
 2023-07-02 10:34:33,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
 2023-07-02 10:34:33,988 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:33,988 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5134282294216049, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:33,988 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41455
 2023-07-02 10:34:34,008 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,008 [model] Posterior to be computed for parameters {'Omega_m': 0.3419989952203588, 'b1': 0.4556350512087163}
 2023-07-02 10:34:34,008 [prior] Evaluating prior at array([0.341999  , 0.45563505])
 2023-07-02 10:34:34,008 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,008 [model] Got input parameters: {'Omega_m': 0.3419989952203588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4556350512087163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,008 [classy] Got parameters {'Omega_m': 0.3419989952203588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,008 [classy] Computing new state
 2023-07-02 10:34:34,008 [classy] Setting parameters: {'Omega_m': 0.3419989952203588, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.85052036542538}
 2023-07-02 10:34:34,055 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0499382
 2023-07-02 10:34:34,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4556350512087163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,057 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,078 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.727489
 2023-07-02 10:34:34,078 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.54611710067799}
 2023-07-02 10:34:34,079 [prior] Evaluating prior at array([0.32009068, 0.5461171 ])
 2023-07-02 10:34:34,079 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,079 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.54611710067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,079 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,079 [classy] Re-using computed results
 2023-07-02 10:34:34,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
 2023-07-02 10:34:34,079 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,079 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.54611710067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,079 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,099 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.86491
 2023-07-02 10:34:34,099 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,099 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5150489986127667}
 2023-07-02 10:34:34,099 [prior] Evaluating prior at array([0.30782122, 0.515049  ])
 2023-07-02 10:34:34,099 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,099 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150489986127667, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,099 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,099 [classy] Computing new state
 2023-07-02 10:34:34,100 [classy] Setting parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,150 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00155131
 2023-07-02 10:34:34,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150489986127667, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,153 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,173 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60424
 2023-07-02 10:34:34,173 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,174 [mcmc] New sample, #729:
   Omega_m:0.3200907, b1:0.49372
 2023-07-02 10:34:34,174 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.4158374720263018}
 2023-07-02 10:34:34,174 [prior] Evaluating prior at array([0.30782122, 0.41583747])
 2023-07-02 10:34:34,174 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,174 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4158374720263018, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,174 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,174 [classy] Re-using computed results
 2023-07-02 10:34:34,174 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,174 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,174 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4158374720263018, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,174 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,194 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.4616
 2023-07-02 10:34:34,194 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,194 [model] Posterior to be computed for parameters {'Omega_m': 0.29658447493405954, 'b1': 0.5345827295531178}
 2023-07-02 10:34:34,195 [prior] Evaluating prior at array([0.29658447, 0.53458273])
 2023-07-02 10:34:34,195 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,195 [model] Got input parameters: {'Omega_m': 0.29658447493405954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5345827295531178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,195 [classy] Got parameters {'Omega_m': 0.29658447493405954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,195 [classy] Computing new state
 2023-07-02 10:34:34,195 [classy] Setting parameters: {'Omega_m': 0.29658447493405954, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.21764210412306}
 2023-07-02 10:34:34,251 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163395
 2023-07-02 10:34:34,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5345827295531178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,253 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,282 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.820035
 2023-07-02 10:34:34,282 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,282 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5552682468125634}
 2023-07-02 10:34:34,282 [prior] Evaluating prior at array([0.30782122, 0.55526825])
 2023-07-02 10:34:34,283 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,283 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5552682468125634, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,283 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,283 [classy] Re-using computed results
 2023-07-02 10:34:34,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,283 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,283 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5552682468125634, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,283 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,309 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.28399
 2023-07-02 10:34:34,309 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,309 [model] Posterior to be computed for parameters {'Omega_m': 0.34179027717776245, 'b1': 0.45599788240868705}
 2023-07-02 10:34:34,309 [prior] Evaluating prior at array([0.34179028, 0.45599788])
 2023-07-02 10:34:34,310 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,310 [model] Got input parameters: {'Omega_m': 0.34179027717776245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45599788240868705, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,310 [classy] Got parameters {'Omega_m': 0.34179027717776245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,310 [classy] Computing new state
 2023-07-02 10:34:34,310 [classy] Setting parameters: {'Omega_m': 0.34179027717776245, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8736851165023}
 2023-07-02 10:34:34,357 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0492612
 2023-07-02 10:34:34,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45599788240868705, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,359 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,379 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.674396
 2023-07-02 10:34:34,379 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,379 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5483848172324856}
 2023-07-02 10:34:34,379 [prior] Evaluating prior at array([0.30782122, 0.54838482])
 2023-07-02 10:34:34,379 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,379 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483848172324856, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,379 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,379 [classy] Re-using computed results
 2023-07-02 10:34:34,379 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,379 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483848172324856, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,379 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,399 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.783893
 2023-07-02 10:34:34,399 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,399 [model] Posterior to be computed for parameters {'Omega_m': 0.33768869219887154, 'b1': 0.4631279943106593}
 2023-07-02 10:34:34,399 [prior] Evaluating prior at array([0.33768869, 0.46312799])
 2023-07-02 10:34:34,399 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,399 [model] Got input parameters: {'Omega_m': 0.33768869219887154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4631279943106593, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,399 [classy] Got parameters {'Omega_m': 0.33768869219887154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,399 [classy] Computing new state
 2023-07-02 10:34:34,399 [classy] Setting parameters: {'Omega_m': 0.33768869219887154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.3314978558565}
 2023-07-02 10:34:34,450 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0368428
 2023-07-02 10:34:34,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4631279943106593, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,452 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,472 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.298356
 2023-07-02 10:34:34,472 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,472 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5538579541844277}
 2023-07-02 10:34:34,472 [prior] Evaluating prior at array([0.30782122, 0.55385795])
 2023-07-02 10:34:34,472 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,472 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5538579541844277, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,472 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,472 [classy] Re-using computed results
 2023-07-02 10:34:34,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,472 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5538579541844277, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,472 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,492 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.95349
 2023-07-02 10:34:34,492 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,492 [model] Posterior to be computed for parameters {'Omega_m': 0.3279371187006351, 'b1': 0.4800799313351448}
 2023-07-02 10:34:34,493 [prior] Evaluating prior at array([0.32793712, 0.48007993])
 2023-07-02 10:34:34,493 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,493 [model] Got input parameters: {'Omega_m': 0.3279371187006351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4800799313351448, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,493 [classy] Got parameters {'Omega_m': 0.3279371187006351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,493 [classy] Computing new state
 2023-07-02 10:34:34,493 [classy] Setting parameters: {'Omega_m': 0.3279371187006351, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.44047976212397}
 2023-07-02 10:34:34,539 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0143012
 2023-07-02 10:34:34,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4800799313351448, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,541 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,561 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03339
 2023-07-02 10:34:34,561 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,561 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.6231285020999274}
 2023-07-02 10:34:34,561 [prior] Evaluating prior at array([0.30782122, 0.6231285 ])
 2023-07-02 10:34:34,562 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,562 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6231285020999274, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,562 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,562 [classy] Re-using computed results
 2023-07-02 10:34:34,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,562 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,562 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6231285020999274, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,562 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,581 [fs_likelihood.fslikelihood] Computed log-likelihood = -33.3001
 2023-07-02 10:34:34,581 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,582 [model] Posterior to be computed for parameters {'Omega_m': 0.26332381457083465, 'b1': 0.5924023850140703}
 2023-07-02 10:34:34,582 [prior] Evaluating prior at array([0.26332381, 0.59240239])
 2023-07-02 10:34:34,582 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,582 [model] Got input parameters: {'Omega_m': 0.26332381457083465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5924023850140703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,582 [classy] Got parameters {'Omega_m': 0.26332381457083465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,582 [classy] Computing new state
 2023-07-02 10:34:34,582 [classy] Setting parameters: {'Omega_m': 0.26332381457083465, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.62596951588094}
 2023-07-02 10:34:34,628 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.168723
 2023-07-02 10:34:34,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5924023850140703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,630 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,649 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.862
 2023-07-02 10:34:34,649 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,650 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5351445489868382}
 2023-07-02 10:34:34,650 [prior] Evaluating prior at array([0.30782122, 0.53514455])
 2023-07-02 10:34:34,650 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,650 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5351445489868382, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,650 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,650 [classy] Re-using computed results
 2023-07-02 10:34:34,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,650 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,650 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5351445489868382, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,650 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,670 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.31631
 2023-07-02 10:34:34,670 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,670 [model] Posterior to be computed for parameters {'Omega_m': 0.2867833487250209, 'b1': 0.5516208080021705}
 2023-07-02 10:34:34,670 [prior] Evaluating prior at array([0.28678335, 0.55162081])
 2023-07-02 10:34:34,670 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,670 [model] Got input parameters: {'Omega_m': 0.2867833487250209, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5516208080021705, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,670 [classy] Got parameters {'Omega_m': 0.2867833487250209, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,670 [classy] Computing new state
 2023-07-02 10:34:34,670 [classy] Setting parameters: {'Omega_m': 0.2867833487250209, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.47055417026638}
 2023-07-02 10:34:34,718 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,720 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0434502
 2023-07-02 10:34:34,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5516208080021705, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,720 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,739 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.18516
 2023-07-02 10:34:34,739 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,739 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5166446013770936}
 2023-07-02 10:34:34,739 [prior] Evaluating prior at array([0.30782122, 0.5166446 ])
 2023-07-02 10:34:34,739 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,739 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166446013770936, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,739 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,739 [classy] Re-using computed results
 2023-07-02 10:34:34,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,740 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166446013770936, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,740 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,759 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58313
 2023-07-02 10:34:34,759 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,760 [mcmc] New sample, #730:
   Omega_m:0.3078212, b1:0.515049
 2023-07-02 10:34:34,760 [model] Posterior to be computed for parameters {'Omega_m': 0.25137402758935745, 'b1': 0.6147712544109722}
 2023-07-02 10:34:34,760 [prior] Evaluating prior at array([0.25137403, 0.61477125])
 2023-07-02 10:34:34,760 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,760 [model] Got input parameters: {'Omega_m': 0.25137402758935745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6147712544109722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,760 [classy] Got parameters {'Omega_m': 0.25137402758935745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,760 [classy] Computing new state
 2023-07-02 10:34:34,760 [classy] Setting parameters: {'Omega_m': 0.25137402758935745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,806 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.32549280324454}
 2023-07-02 10:34:34,806 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,808 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.269427
 2023-07-02 10:34:34,808 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6147712544109722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,808 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,828 [fs_likelihood.fslikelihood] Computed log-likelihood = -26.9467
 2023-07-02 10:34:34,828 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,828 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5582116231789337}
 2023-07-02 10:34:34,828 [prior] Evaluating prior at array([0.30782122, 0.55821162])
 2023-07-02 10:34:34,828 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,828 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5582116231789337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,828 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,828 [classy] Re-using computed results
 2023-07-02 10:34:34,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,828 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,828 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5582116231789337, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,828 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,847 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.01255
 2023-07-02 10:34:34,847 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,847 [model] Posterior to be computed for parameters {'Omega_m': 0.3034111739944942, 'b1': 0.5243109375243346}
 2023-07-02 10:34:34,848 [prior] Evaluating prior at array([0.30341117, 0.52431094])
 2023-07-02 10:34:34,848 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,848 [model] Got input parameters: {'Omega_m': 0.3034111739944942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5243109375243346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,848 [classy] Got parameters {'Omega_m': 0.3034111739944942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,848 [classy] Computing new state
 2023-07-02 10:34:34,848 [classy] Setting parameters: {'Omega_m': 0.3034111739944942, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.36610639144422}
 2023-07-02 10:34:34,894 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00536633
 2023-07-02 10:34:34,896 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5243109375243346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,896 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,917 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08404
 2023-07-02 10:34:34,917 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,917 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5277396481046734}
 2023-07-02 10:34:34,917 [prior] Evaluating prior at array([0.30782122, 0.52773965])
 2023-07-02 10:34:34,917 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,917 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5277396481046734, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,917 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,917 [classy] Re-using computed results
 2023-07-02 10:34:34,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:34,917 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:34,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5277396481046734, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,917 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:34,937 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05206
 2023-07-02 10:34:34,937 [model] Computed derived parameters: {}
 2023-07-02 10:34:34,937 [mcmc] New sample, #731:
   Omega_m:0.3078212, b1:0.5166446
 2023-07-02 10:34:34,937 [model] Posterior to be computed for parameters {'Omega_m': 0.30366365165102466, 'b1': 0.5349670822291416}
 2023-07-02 10:34:34,937 [prior] Evaluating prior at array([0.30366365, 0.53496708])
 2023-07-02 10:34:34,937 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:34,937 [model] Got input parameters: {'Omega_m': 0.30366365165102466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5349670822291416, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,937 [classy] Got parameters {'Omega_m': 0.30366365165102466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:34,937 [classy] Computing new state
 2023-07-02 10:34:34,937 [classy] Setting parameters: {'Omega_m': 0.30366365165102466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:34,984 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.334937745333}
 2023-07-02 10:34:34,984 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:34,986 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00507982
 2023-07-02 10:34:34,986 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5349670822291416, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:34,986 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,005 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61014
 2023-07-02 10:34:35,005 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,005 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5654594376991975}
 2023-07-02 10:34:35,005 [prior] Evaluating prior at array([0.30782122, 0.56545944])
 2023-07-02 10:34:35,005 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,005 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5654594376991975, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,005 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,005 [classy] Re-using computed results
 2023-07-02 10:34:35,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,005 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,005 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5654594376991975, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,005 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,026 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.0326
 2023-07-02 10:34:35,026 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3340034526797648, 'b1': 0.48222498922562435}
 2023-07-02 10:34:35,026 [prior] Evaluating prior at array([0.33400345, 0.48222499])
 2023-07-02 10:34:35,026 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,026 [model] Got input parameters: {'Omega_m': 0.3340034526797648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48222498922562435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,026 [classy] Got parameters {'Omega_m': 0.3340034526797648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,026 [classy] Computing new state
 2023-07-02 10:34:35,026 [classy] Setting parameters: {'Omega_m': 0.3340034526797648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.74714886034815}
 2023-07-02 10:34:35,073 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0271471
 2023-07-02 10:34:35,075 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48222498922562435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,075 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,095 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.347465
 2023-07-02 10:34:35,095 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,095 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5484608684177067}
 2023-07-02 10:34:35,095 [prior] Evaluating prior at array([0.30782122, 0.54846087])
 2023-07-02 10:34:35,095 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,095 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5484608684177067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,095 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,095 [classy] Re-using computed results
 2023-07-02 10:34:35,095 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,095 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,095 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5484608684177067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,095 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,115 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.798922
 2023-07-02 10:34:35,115 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,116 [model] Posterior to be computed for parameters {'Omega_m': 0.2602533506523905, 'b1': 0.6104306665292432}
 2023-07-02 10:34:35,116 [prior] Evaluating prior at array([0.26025335, 0.61043067])
 2023-07-02 10:34:35,116 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,116 [model] Got input parameters: {'Omega_m': 0.2602533506523905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6104306665292432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,116 [classy] Got parameters {'Omega_m': 0.2602533506523905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,116 [classy] Computing new state
 2023-07-02 10:34:35,116 [classy] Setting parameters: {'Omega_m': 0.2602533506523905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.05638878019178}
 2023-07-02 10:34:35,164 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,166 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.192048
 2023-07-02 10:34:35,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6104306665292432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,166 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,185 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.7447
 2023-07-02 10:34:35,185 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,186 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5768476062596689}
 2023-07-02 10:34:35,186 [prior] Evaluating prior at array([0.30782122, 0.57684761])
 2023-07-02 10:34:35,186 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,186 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5768476062596689, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,186 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,186 [classy] Re-using computed results
 2023-07-02 10:34:35,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,186 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5768476062596689, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.86921
 2023-07-02 10:34:35,205 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,206 [model] Posterior to be computed for parameters {'Omega_m': 0.28793212553530145, 'b1': 0.562314447252952}
 2023-07-02 10:34:35,206 [prior] Evaluating prior at array([0.28793213, 0.56231445])
 2023-07-02 10:34:35,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,206 [model] Got input parameters: {'Omega_m': 0.28793212553530145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.562314447252952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,206 [classy] Got parameters {'Omega_m': 0.28793212553530145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,206 [classy] Computing new state
 2023-07-02 10:34:35,206 [classy] Setting parameters: {'Omega_m': 0.28793212553530145, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.32180444893572}
 2023-07-02 10:34:35,253 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,255 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0395525
 2023-07-02 10:34:35,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.562314447252952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,255 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,275 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1959
 2023-07-02 10:34:35,275 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,275 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.486805209231203}
 2023-07-02 10:34:35,275 [prior] Evaluating prior at array([0.30782122, 0.48680521])
 2023-07-02 10:34:35,276 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,276 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.486805209231203, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,276 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,276 [classy] Re-using computed results
 2023-07-02 10:34:35,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,276 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,276 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.486805209231203, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,276 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,296 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.7702
 2023-07-02 10:34:35,296 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,296 [model] Posterior to be computed for parameters {'Omega_m': 0.26251651366528567, 'b1': 0.6064964299798615}
 2023-07-02 10:34:35,296 [prior] Evaluating prior at array([0.26251651, 0.60649643])
 2023-07-02 10:34:35,296 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,296 [model] Got input parameters: {'Omega_m': 0.26251651366528567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6064964299798615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,296 [classy] Got parameters {'Omega_m': 0.26251651366528567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,296 [classy] Computing new state
 2023-07-02 10:34:35,296 [classy] Setting parameters: {'Omega_m': 0.26251651366528567, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.738728640241}
 2023-07-02 10:34:35,343 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17469
 2023-07-02 10:34:35,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6064964299798615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,345 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,365 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.8456
 2023-07-02 10:34:35,365 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,365 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5851839027485815}
 2023-07-02 10:34:35,365 [prior] Evaluating prior at array([0.30782122, 0.5851839 ])
 2023-07-02 10:34:35,365 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,365 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5851839027485815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,365 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,365 [classy] Re-using computed results
 2023-07-02 10:34:35,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,365 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5851839027485815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,365 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,385 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.2038
 2023-07-02 10:34:35,385 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,385 [model] Posterior to be computed for parameters {'Omega_m': 0.3396853863429277, 'b1': 0.4723476313148563}
 2023-07-02 10:34:35,385 [prior] Evaluating prior at array([0.33968539, 0.47234763])
 2023-07-02 10:34:35,385 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,385 [model] Got input parameters: {'Omega_m': 0.3396853863429277, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4723476313148563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,385 [classy] Got parameters {'Omega_m': 0.3396853863429277, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,385 [classy] Computing new state
 2023-07-02 10:34:35,385 [classy] Setting parameters: {'Omega_m': 0.3396853863429277, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.10800296388737}
 2023-07-02 10:34:35,436 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.042677
 2023-07-02 10:34:35,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4723476313148563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,439 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.894634
 2023-07-02 10:34:35,459 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,460 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5019667928152267}
 2023-07-02 10:34:35,460 [prior] Evaluating prior at array([0.30782122, 0.50196679])
 2023-07-02 10:34:35,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,460 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5019667928152267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,460 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,460 [classy] Re-using computed results
 2023-07-02 10:34:35,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,460 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5019667928152267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,480 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26664
 2023-07-02 10:34:35,480 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,480 [mcmc] New sample, #732:
   Omega_m:0.3078212, b1:0.5277396
 2023-07-02 10:34:35,480 [model] Posterior to be computed for parameters {'Omega_m': 0.2899500680203179, 'b1': 0.5330336417920566}
 2023-07-02 10:34:35,481 [prior] Evaluating prior at array([0.28995007, 0.53303364])
 2023-07-02 10:34:35,481 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,481 [model] Got input parameters: {'Omega_m': 0.2899500680203179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330336417920566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,481 [classy] Got parameters {'Omega_m': 0.2899500680203179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,481 [classy] Computing new state
 2023-07-02 10:34:35,481 [classy] Setting parameters: {'Omega_m': 0.2899500680203179, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.06174566377476}
 2023-07-02 10:34:35,528 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0331765
 2023-07-02 10:34:35,530 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330336417920566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,530 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,549 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.47888
 2023-07-02 10:34:35,549 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,549 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.4999325702979241}
 2023-07-02 10:34:35,549 [prior] Evaluating prior at array([0.30782122, 0.49993257])
 2023-07-02 10:34:35,549 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,549 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4999325702979241, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,549 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,549 [classy] Re-using computed results
 2023-07-02 10:34:35,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
 2023-07-02 10:34:35,549 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,549 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4999325702979241, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,550 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,569 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13372
 2023-07-02 10:34:35,569 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,569 [mcmc] New sample, #733:
   Omega_m:0.3078212, b1:0.5019668
 2023-07-02 10:34:35,569 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5116809196630896}
 2023-07-02 10:34:35,570 [prior] Evaluating prior at array([0.301063  , 0.51168092])
 2023-07-02 10:34:35,570 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,570 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5116809196630896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,570 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,570 [classy] Computing new state
 2023-07-02 10:34:35,570 [classy] Setting parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,616 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
 2023-07-02 10:34:35,616 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,618 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00843375
 2023-07-02 10:34:35,618 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5116809196630896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,618 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,638 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22365
 2023-07-02 10:34:35,638 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,638 [mcmc] New sample, #734:
   Omega_m:0.3078212, b1:0.4999326
 2023-07-02 10:34:35,638 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5255361549856249}
 2023-07-02 10:34:35,638 [prior] Evaluating prior at array([0.301063  , 0.52553615])
 2023-07-02 10:34:35,638 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,638 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5255361549856249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,638 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,638 [classy] Re-using computed results
 2023-07-02 10:34:35,638 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
 2023-07-02 10:34:35,638 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,638 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5255361549856249, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,638 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,657 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.73562
 2023-07-02 10:34:35,657 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,657 [mcmc] New sample, #735:
   Omega_m:0.301063, b1:0.5116809
 2023-07-02 10:34:35,657 [model] Posterior to be computed for parameters {'Omega_m': 0.3357509743678803, 'b1': 0.46523529058299495}
 2023-07-02 10:34:35,657 [prior] Evaluating prior at array([0.33575097, 0.46523529])
 2023-07-02 10:34:35,658 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,658 [model] Got input parameters: {'Omega_m': 0.3357509743678803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46523529058299495, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,658 [classy] Got parameters {'Omega_m': 0.3357509743678803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,658 [classy] Computing new state
 2023-07-02 10:34:35,658 [classy] Setting parameters: {'Omega_m': 0.3357509743678803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.54953384713232}
 2023-07-02 10:34:35,705 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0315698
 2023-07-02 10:34:35,707 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46523529058299495, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,707 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,727 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.731395
 2023-07-02 10:34:35,727 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,727 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5737459942729837}
 2023-07-02 10:34:35,727 [prior] Evaluating prior at array([0.301063  , 0.57374599])
 2023-07-02 10:34:35,728 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,728 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5737459942729837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,728 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,728 [classy] Re-using computed results
 2023-07-02 10:34:35,728 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
 2023-07-02 10:34:35,728 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,728 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5737459942729837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,728 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.71096
 2023-07-02 10:34:35,747 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,747 [model] Posterior to be computed for parameters {'Omega_m': 0.2737227705773714, 'b1': 0.5730638584124655}
 2023-07-02 10:34:35,747 [prior] Evaluating prior at array([0.27372277, 0.57306386])
 2023-07-02 10:34:35,747 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,747 [model] Got input parameters: {'Omega_m': 0.2737227705773714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5730638584124655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,748 [classy] Got parameters {'Omega_m': 0.2737227705773714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,748 [classy] Computing new state
 2023-07-02 10:34:35,748 [classy] Setting parameters: {'Omega_m': 0.2737227705773714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.19888024071236}
 2023-07-02 10:34:35,794 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,796 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102045
 2023-07-02 10:34:35,796 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5730638584124655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,796 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,815 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.58485
 2023-07-02 10:34:35,815 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,815 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5635160162531283}
 2023-07-02 10:34:35,815 [prior] Evaluating prior at array([0.301063  , 0.56351602])
 2023-07-02 10:34:35,816 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,816 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5635160162531283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,816 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,816 [classy] Re-using computed results
 2023-07-02 10:34:35,816 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
 2023-07-02 10:34:35,816 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5635160162531283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,816 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,836 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.22001
 2023-07-02 10:34:35,836 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,836 [model] Posterior to be computed for parameters {'Omega_m': 0.27454084515778016, 'b1': 0.571641734201339}
 2023-07-02 10:34:35,836 [prior] Evaluating prior at array([0.27454085, 0.57164173])
 2023-07-02 10:34:35,836 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,836 [model] Got input parameters: {'Omega_m': 0.27454084515778016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.571641734201339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,836 [classy] Got parameters {'Omega_m': 0.27454084515778016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,836 [classy] Computing new state
 2023-07-02 10:34:35,836 [classy] Setting parameters: {'Omega_m': 0.27454084515778016, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,883 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.08857893330432}
 2023-07-02 10:34:35,883 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,885 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0975775
 2023-07-02 10:34:35,885 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.571641734201339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,885 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,904 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.0976
 2023-07-02 10:34:35,904 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,904 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5165518387326689}
 2023-07-02 10:34:35,904 [prior] Evaluating prior at array([0.301063  , 0.51655184])
 2023-07-02 10:34:35,905 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,905 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5165518387326689, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,905 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,905 [classy] Re-using computed results
 2023-07-02 10:34:35,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
 2023-07-02 10:34:35,905 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,905 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5165518387326689, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,905 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.5173
 2023-07-02 10:34:35,925 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,925 [mcmc] New sample, #736:
   Omega_m:0.301063, b1:0.5255362
 2023-07-02 10:34:35,925 [model] Posterior to be computed for parameters {'Omega_m': 0.29877966224659547, 'b1': 0.5205211513333666}
 2023-07-02 10:34:35,925 [prior] Evaluating prior at array([0.29877966, 0.52052115])
 2023-07-02 10:34:35,926 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,926 [model] Got input parameters: {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205211513333666, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,926 [classy] Got parameters {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,926 [classy] Computing new state
 2023-07-02 10:34:35,926 [classy] Setting parameters: {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:35,972 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9419550418081}
 2023-07-02 10:34:35,972 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:35,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0121236
 2023-07-02 10:34:35,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205211513333666, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,974 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:35,994 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07787
 2023-07-02 10:34:35,994 [model] Computed derived parameters: {}
 2023-07-02 10:34:35,994 [mcmc] New sample, #737:
   Omega_m:0.301063, b1:0.5165518
 2023-07-02 10:34:35,994 [model] Posterior to be computed for parameters {'Omega_m': 0.29877966224659547, 'b1': 0.4666415873877423}
 2023-07-02 10:34:35,994 [prior] Evaluating prior at array([0.29877966, 0.46664159])
 2023-07-02 10:34:35,994 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:35,994 [model] Got input parameters: {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4666415873877423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,994 [classy] Got parameters {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:35,994 [classy] Re-using computed results
 2023-07-02 10:34:35,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9419550418081}
 2023-07-02 10:34:35,994 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:35,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4666415873877423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:35,994 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,013 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.62356
 2023-07-02 10:34:36,013 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,013 [model] Posterior to be computed for parameters {'Omega_m': 0.32892436169525674, 'b1': 0.4681182189483354}
 2023-07-02 10:34:36,014 [prior] Evaluating prior at array([0.32892436, 0.46811822])
 2023-07-02 10:34:36,014 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,014 [model] Got input parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4681182189483354, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,014 [classy] Got parameters {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,014 [classy] Computing new state
 2023-07-02 10:34:36,014 [classy] Setting parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32685184225735}
 2023-07-02 10:34:36,060 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0161225
 2023-07-02 10:34:36,062 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4681182189483354, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,062 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79419
 2023-07-02 10:34:36,083 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,083 [mcmc] New sample, #738:
   Omega_m:0.2987797, b1:0.5205212
 2023-07-02 10:34:36,083 [model] Posterior to be computed for parameters {'Omega_m': 0.32892436169525674, 'b1': 0.50606052806406}
 2023-07-02 10:34:36,083 [prior] Evaluating prior at array([0.32892436, 0.50606053])
 2023-07-02 10:34:36,083 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,083 [model] Got input parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.50606052806406, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,083 [classy] Got parameters {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,083 [classy] Re-using computed results
 2023-07-02 10:34:36,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32685184225735}
 2023-07-02 10:34:36,083 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.50606052806406, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,083 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,103 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.773872
 2023-07-02 10:34:36,103 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,103 [model] Posterior to be computed for parameters {'Omega_m': 0.29716199835611096, 'b1': 0.523333265337659}
 2023-07-02 10:34:36,103 [prior] Evaluating prior at array([0.297162  , 0.52333327])
 2023-07-02 10:34:36,103 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,103 [model] Got input parameters: {'Omega_m': 0.29716199835611096, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523333265337659, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,103 [classy] Got parameters {'Omega_m': 0.29716199835611096, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,103 [classy] Computing new state
 2023-07-02 10:34:36,103 [classy] Setting parameters: {'Omega_m': 0.29716199835611096, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.14493797952687}
 2023-07-02 10:34:36,153 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0151661
 2023-07-02 10:34:36,155 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523333265337659, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,155 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,174 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.723322
 2023-07-02 10:34:36,174 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,175 [model] Posterior to be computed for parameters {'Omega_m': 0.32892436169525674, 'b1': 0.4676315279242922}
 2023-07-02 10:34:36,175 [prior] Evaluating prior at array([0.32892436, 0.46763153])
 2023-07-02 10:34:36,175 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,175 [model] Got input parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4676315279242922, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,175 [classy] Got parameters {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,175 [classy] Re-using computed results
 2023-07-02 10:34:36,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32685184225735}
 2023-07-02 10:34:36,175 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,175 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4676315279242922, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,175 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,195 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7752
 2023-07-02 10:34:36,195 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,195 [mcmc] New sample, #739:
   Omega_m:0.3289244, b1:0.4681182
 2023-07-02 10:34:36,195 [model] Posterior to be computed for parameters {'Omega_m': 0.31640776265317944, 'b1': 0.4893901291141824}
 2023-07-02 10:34:36,195 [prior] Evaluating prior at array([0.31640776, 0.48939013])
 2023-07-02 10:34:36,195 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,195 [model] Got input parameters: {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4893901291141824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,195 [classy] Got parameters {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,195 [classy] Computing new state
 2023-07-02 10:34:36,195 [classy] Setting parameters: {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7906012332484}
 2023-07-02 10:34:36,241 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,243 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00113737
 2023-07-02 10:34:36,243 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4893901291141824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,243 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,263 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72948
 2023-07-02 10:34:36,263 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,263 [mcmc] New sample, #740:
   Omega_m:0.3289244, b1:0.4676315
 2023-07-02 10:34:36,263 [model] Posterior to be computed for parameters {'Omega_m': 0.31640776265317944, 'b1': 0.4796693642285248}
 2023-07-02 10:34:36,263 [prior] Evaluating prior at array([0.31640776, 0.47966936])
 2023-07-02 10:34:36,263 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,263 [model] Got input parameters: {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4796693642285248, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,263 [classy] Got parameters {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,263 [classy] Re-using computed results
 2023-07-02 10:34:36,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7906012332484}
 2023-07-02 10:34:36,263 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,263 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4796693642285248, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,263 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,283 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.04782
 2023-07-02 10:34:36,283 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,283 [mcmc] New sample, #741:
   Omega_m:0.3164078, b1:0.4893901
 2023-07-02 10:34:36,283 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.4853377263595307}
 2023-07-02 10:34:36,284 [prior] Evaluating prior at array([0.31314705, 0.48533773])
 2023-07-02 10:34:36,284 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,284 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853377263595307, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,284 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,284 [classy] Computing new state
 2023-07-02 10:34:36,284 [classy] Setting parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
 2023-07-02 10:34:36,330 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,332 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000229295
 2023-07-02 10:34:36,332 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853377263595307, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,332 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,351 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.01101
 2023-07-02 10:34:36,351 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,351 [mcmc] New sample, #742:
   Omega_m:0.3164078, b1:0.4796694
 2023-07-02 10:34:36,352 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.49013806891124495}
 2023-07-02 10:34:36,352 [prior] Evaluating prior at array([0.31314705, 0.49013807])
 2023-07-02 10:34:36,352 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,352 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49013806891124495, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,352 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,352 [classy] Re-using computed results
 2023-07-02 10:34:36,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
 2023-07-02 10:34:36,352 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,352 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49013806891124495, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,352 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41384
 2023-07-02 10:34:36,371 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,371 [mcmc] New sample, #743:
   Omega_m:0.313147, b1:0.4853377
 2023-07-02 10:34:36,371 [model] Posterior to be computed for parameters {'Omega_m': 0.2930719948366561, 'b1': 0.5250361309081256}
 2023-07-02 10:34:36,371 [prior] Evaluating prior at array([0.29307199, 0.52503613])
 2023-07-02 10:34:36,372 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,372 [model] Got input parameters: {'Omega_m': 0.2930719948366561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5250361309081256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,372 [classy] Got parameters {'Omega_m': 0.2930719948366561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,372 [classy] Computing new state
 2023-07-02 10:34:36,372 [classy] Setting parameters: {'Omega_m': 0.2930719948366561, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.66247729967716}
 2023-07-02 10:34:36,418 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,420 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244759
 2023-07-02 10:34:36,420 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5250361309081256, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,420 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,439 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.685077
 2023-07-02 10:34:36,440 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,440 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.4696568252575498}
 2023-07-02 10:34:36,440 [prior] Evaluating prior at array([0.31314705, 0.46965683])
 2023-07-02 10:34:36,440 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,440 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4696568252575498, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,440 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,440 [classy] Re-using computed results
 2023-07-02 10:34:36,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
 2023-07-02 10:34:36,440 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4696568252575498, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,440 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.112946
 2023-07-02 10:34:36,459 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,460 [model] Posterior to be computed for parameters {'Omega_m': 0.35917293420651714, 'b1': 0.41012760238605056}
 2023-07-02 10:34:36,460 [prior] Evaluating prior at array([0.35917293, 0.4101276 ])
 2023-07-02 10:34:36,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,460 [model] Got input parameters: {'Omega_m': 0.35917293420651714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41012760238605056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,460 [classy] Got parameters {'Omega_m': 0.35917293420651714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,460 [classy] Computing new state
 2023-07-02 10:34:36,460 [classy] Setting parameters: {'Omega_m': 0.35917293420651714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.9876552379094}
 2023-07-02 10:34:36,507 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.1198
 2023-07-02 10:34:36,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41012760238605056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,528 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.40195
 2023-07-02 10:34:36,528 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,528 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.44739147781832467}
 2023-07-02 10:34:36,528 [prior] Evaluating prior at array([0.31314705, 0.44739148])
 2023-07-02 10:34:36,528 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,528 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44739147781832467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,528 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,528 [classy] Re-using computed results
 2023-07-02 10:34:36,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
 2023-07-02 10:34:36,528 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44739147781832467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,528 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,548 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.16119
 2023-07-02 10:34:36,548 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,548 [model] Posterior to be computed for parameters {'Omega_m': 0.3367056026860735, 'b1': 0.4491843545206343}
 2023-07-02 10:34:36,548 [prior] Evaluating prior at array([0.3367056 , 0.44918435])
 2023-07-02 10:34:36,549 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,549 [model] Got input parameters: {'Omega_m': 0.3367056026860735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4491843545206343, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,549 [classy] Got parameters {'Omega_m': 0.3367056026860735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,549 [classy] Computing new state
 2023-07-02 10:34:36,549 [classy] Setting parameters: {'Omega_m': 0.3367056026860735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.44197327068946}
 2023-07-02 10:34:36,595 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0341195
 2023-07-02 10:34:36,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4491843545206343, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,597 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.170146
 2023-07-02 10:34:36,616 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,616 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.5590726744269169}
 2023-07-02 10:34:36,617 [prior] Evaluating prior at array([0.31314705, 0.55907267])
 2023-07-02 10:34:36,617 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,617 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5590726744269169, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,617 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,617 [classy] Re-using computed results
 2023-07-02 10:34:36,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
 2023-07-02 10:34:36,617 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5590726744269169, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,617 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,636 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.81153
 2023-07-02 10:34:36,636 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3344704274065653, 'b1': 0.4530699377635604}
 2023-07-02 10:34:36,637 [prior] Evaluating prior at array([0.33447043, 0.45306994])
 2023-07-02 10:34:36,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,637 [model] Got input parameters: {'Omega_m': 0.3344704274065653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4530699377635604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,637 [classy] Got parameters {'Omega_m': 0.3344704274065653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,637 [classy] Computing new state
 2023-07-02 10:34:36,637 [classy] Setting parameters: {'Omega_m': 0.3344704274065653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.69425198804524}
 2023-07-02 10:34:36,684 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,686 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0282977
 2023-07-02 10:34:36,686 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4530699377635604, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,686 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,706 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.610885
 2023-07-02 10:34:36,706 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,706 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.42426879996283895}
 2023-07-02 10:34:36,706 [prior] Evaluating prior at array([0.31314705, 0.4242688 ])
 2023-07-02 10:34:36,706 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,706 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42426879996283895, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,706 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,706 [classy] Re-using computed results
 2023-07-02 10:34:36,706 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
 2023-07-02 10:34:36,706 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,706 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42426879996283895, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,706 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,725 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.7669
 2023-07-02 10:34:36,726 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,726 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.4777676762182187}
 2023-07-02 10:34:36,726 [prior] Evaluating prior at array([0.32026309, 0.47776768])
 2023-07-02 10:34:36,726 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,726 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4777676762182187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,726 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,726 [classy] Computing new state
 2023-07-02 10:34:36,726 [classy] Setting parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:36,772 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00384223
 2023-07-02 10:34:36,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4777676762182187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,774 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,794 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33133
 2023-07-02 10:34:36,794 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,794 [mcmc] New sample, #744:
   Omega_m:0.313147, b1:0.4901381
 2023-07-02 10:34:36,794 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.4660254405281234}
 2023-07-02 10:34:36,794 [prior] Evaluating prior at array([0.32026309, 0.46602544])
 2023-07-02 10:34:36,794 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,794 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4660254405281234, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,795 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,795 [classy] Re-using computed results
 2023-07-02 10:34:36,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:36,795 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,795 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4660254405281234, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,795 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,814 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16391
 2023-07-02 10:34:36,814 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,814 [model] Posterior to be computed for parameters {'Omega_m': 0.26844027490734024, 'b1': 0.567855411829511}
 2023-07-02 10:34:36,814 [prior] Evaluating prior at array([0.26844027, 0.56785541])
 2023-07-02 10:34:36,814 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,814 [model] Got input parameters: {'Omega_m': 0.26844027490734024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.567855411829511, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,814 [classy] Got parameters {'Omega_m': 0.26844027490734024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,814 [classy] Computing new state
 2023-07-02 10:34:36,815 [classy] Setting parameters: {'Omega_m': 0.26844027490734024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.91798514000342}
 2023-07-02 10:34:36,862 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.13359
 2023-07-02 10:34:36,864 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.567855411829511, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,864 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,883 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.7132
 2023-07-02 10:34:36,883 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,884 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.510739127035056}
 2023-07-02 10:34:36,884 [prior] Evaluating prior at array([0.32026309, 0.51073913])
 2023-07-02 10:34:36,884 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,884 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510739127035056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,884 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,884 [classy] Re-using computed results
 2023-07-02 10:34:36,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:36,884 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510739127035056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,884 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,905 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.68584
 2023-07-02 10:34:36,905 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,906 [mcmc] New sample, #745:
   Omega_m:0.3202631, b1:0.4777677
 2023-07-02 10:34:36,906 [model] Posterior to be computed for parameters {'Omega_m': 0.34028475515776324, 'b1': 0.475933879479856}
 2023-07-02 10:34:36,906 [prior] Evaluating prior at array([0.34028476, 0.47593388])
 2023-07-02 10:34:36,906 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,906 [model] Got input parameters: {'Omega_m': 0.34028475515776324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.475933879479856, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,906 [classy] Got parameters {'Omega_m': 0.34028475515776324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,906 [classy] Computing new state
 2023-07-02 10:34:36,906 [classy] Setting parameters: {'Omega_m': 0.34028475515776324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:36,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.04114786871142}
 2023-07-02 10:34:36,953 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:36,955 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0445068
 2023-07-02 10:34:36,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.475933879479856, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,955 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,974 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.5413
 2023-07-02 10:34:36,974 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,974 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.6710385676331297}
 2023-07-02 10:34:36,974 [prior] Evaluating prior at array([0.32026309, 0.67103857])
 2023-07-02 10:34:36,974 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,974 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6710385676331297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,974 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,974 [classy] Re-using computed results
 2023-07-02 10:34:36,975 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:36,975 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:36,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6710385676331297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,975 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:36,995 [fs_likelihood.fslikelihood] Computed log-likelihood = -102.22
 2023-07-02 10:34:36,995 [model] Computed derived parameters: {}
 2023-07-02 10:34:36,995 [model] Posterior to be computed for parameters {'Omega_m': 0.27752718083777406, 'b1': 0.5850303702025397}
 2023-07-02 10:34:36,995 [prior] Evaluating prior at array([0.27752718, 0.58503037])
 2023-07-02 10:34:36,995 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:36,995 [model] Got input parameters: {'Omega_m': 0.27752718083777406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5850303702025397, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:36,995 [classy] Got parameters {'Omega_m': 0.27752718083777406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:36,995 [classy] Computing new state
 2023-07-02 10:34:36,995 [classy] Setting parameters: {'Omega_m': 0.27752718083777406, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,045 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.68829370852148}
 2023-07-02 10:34:37,045 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,047 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0821957
 2023-07-02 10:34:37,047 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5850303702025397, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,047 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,067 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.15351
 2023-07-02 10:34:37,067 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,067 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.48769735467306813}
 2023-07-02 10:34:37,067 [prior] Evaluating prior at array([0.32026309, 0.48769735])
 2023-07-02 10:34:37,067 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,067 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48769735467306813, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,067 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,067 [classy] Re-using computed results
 2023-07-02 10:34:37,067 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:37,067 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,067 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48769735467306813, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,067 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,088 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75927
 2023-07-02 10:34:37,088 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,088 [mcmc] New sample, #746:
   Omega_m:0.3202631, b1:0.5107391
 2023-07-02 10:34:37,088 [model] Posterior to be computed for parameters {'Omega_m': 0.3862205947016154, 'b1': 0.3730381779796551}
 2023-07-02 10:34:37,088 [prior] Evaluating prior at array([0.38622059, 0.37303818])
 2023-07-02 10:34:37,089 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,089 [model] Got input parameters: {'Omega_m': 0.3862205947016154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3730381779796551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,089 [classy] Got parameters {'Omega_m': 0.3862205947016154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,089 [classy] Computing new state
 2023-07-02 10:34:37,089 [classy] Setting parameters: {'Omega_m': 0.3862205947016154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.21486279800766}
 2023-07-02 10:34:37,139 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,141 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.281035
 2023-07-02 10:34:37,141 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3730381779796551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,141 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,161 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.0128
 2023-07-02 10:34:37,161 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,161 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.45872511504971347}
 2023-07-02 10:34:37,161 [prior] Evaluating prior at array([0.32026309, 0.45872512])
 2023-07-02 10:34:37,161 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,161 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45872511504971347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,161 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,161 [classy] Re-using computed results
 2023-07-02 10:34:37,161 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:37,161 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,161 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45872511504971347, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,161 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,181 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0874987
 2023-07-02 10:34:37,181 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,181 [model] Posterior to be computed for parameters {'Omega_m': 0.3410817647151713, 'b1': 0.4515066019142681}
 2023-07-02 10:34:37,181 [prior] Evaluating prior at array([0.34108176, 0.4515066 ])
 2023-07-02 10:34:37,181 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,181 [model] Got input parameters: {'Omega_m': 0.3410817647151713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4515066019142681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,181 [classy] Got parameters {'Omega_m': 0.3410817647151713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,181 [classy] Computing new state
 2023-07-02 10:34:37,181 [classy] Setting parameters: {'Omega_m': 0.3410817647151713, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.95240939339246}
 2023-07-02 10:34:37,228 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0469957
 2023-07-02 10:34:37,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4515066019142681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,230 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,250 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.457608
 2023-07-02 10:34:37,250 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,250 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.4958450496577228}
 2023-07-02 10:34:37,250 [prior] Evaluating prior at array([0.32026309, 0.49584505])
 2023-07-02 10:34:37,250 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,250 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4958450496577228, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,250 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,251 [classy] Re-using computed results
 2023-07-02 10:34:37,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:37,251 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4958450496577228, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,251 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,270 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71578
 2023-07-02 10:34:37,270 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,270 [mcmc] New sample, #747:
   Omega_m:0.3202631, b1:0.4876974
 2023-07-02 10:34:37,270 [model] Posterior to be computed for parameters {'Omega_m': 0.3246187336868214, 'b1': 0.4882732951841952}
 2023-07-02 10:34:37,270 [prior] Evaluating prior at array([0.32461873, 0.4882733 ])
 2023-07-02 10:34:37,270 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,270 [model] Got input parameters: {'Omega_m': 0.3246187336868214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4882732951841952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,271 [classy] Got parameters {'Omega_m': 0.3246187336868214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,271 [classy] Computing new state
 2023-07-02 10:34:37,271 [classy] Setting parameters: {'Omega_m': 0.3246187336868214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.82467008377762}
 2023-07-02 10:34:37,317 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00896599
 2023-07-02 10:34:37,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4882732951841952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,319 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,338 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36756
 2023-07-02 10:34:37,338 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,339 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.49398858438585264}
 2023-07-02 10:34:37,339 [prior] Evaluating prior at array([0.32026309, 0.49398858])
 2023-07-02 10:34:37,339 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,339 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49398858438585264, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,339 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,339 [classy] Re-using computed results
 2023-07-02 10:34:37,339 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
 2023-07-02 10:34:37,339 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,339 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49398858438585264, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,339 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,358 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75749
 2023-07-02 10:34:37,359 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,359 [mcmc] New sample, #748:
   Omega_m:0.3202631, b1:0.495845
 2023-07-02 10:34:37,359 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.48487157037082246}
 2023-07-02 10:34:37,359 [prior] Evaluating prior at array([0.32550764, 0.48487157])
 2023-07-02 10:34:37,359 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,359 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48487157037082246, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,359 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,359 [classy] Computing new state
 2023-07-02 10:34:37,359 [classy] Setting parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,405 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
 2023-07-02 10:34:37,405 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,407 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0102753
 2023-07-02 10:34:37,407 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48487157037082246, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,407 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,427 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.31882
 2023-07-02 10:34:37,427 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,427 [mcmc] New sample, #749:
   Omega_m:0.3202631, b1:0.4939886
 2023-07-02 10:34:37,427 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.4844878589886201}
 2023-07-02 10:34:37,427 [prior] Evaluating prior at array([0.32550764, 0.48448786])
 2023-07-02 10:34:37,427 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,427 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4844878589886201, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,427 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,427 [classy] Re-using computed results
 2023-07-02 10:34:37,427 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
 2023-07-02 10:34:37,427 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,427 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4844878589886201, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,427 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,447 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32595
 2023-07-02 10:34:37,447 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,447 [mcmc] New sample, #750:
   Omega_m:0.3255076, b1:0.4848716
 2023-07-02 10:34:37,447 [model] Posterior to be computed for parameters {'Omega_m': 0.35069412778565917, 'b1': 0.44070418379645365}
 2023-07-02 10:34:37,447 [prior] Evaluating prior at array([0.35069413, 0.44070418])
 2023-07-02 10:34:37,447 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,447 [model] Got input parameters: {'Omega_m': 0.35069412778565917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44070418379645365, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,447 [classy] Got parameters {'Omega_m': 0.35069412778565917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,447 [classy] Computing new state
 2023-07-02 10:34:37,447 [classy] Setting parameters: {'Omega_m': 0.35069412778565917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.89690641318637}
 2023-07-02 10:34:37,494 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0818818
 2023-07-02 10:34:37,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44070418379645365, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,496 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,515 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.23403
 2023-07-02 10:34:37,515 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,515 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.3811148769491803}
 2023-07-02 10:34:37,515 [prior] Evaluating prior at array([0.32550764, 0.38111488])
 2023-07-02 10:34:37,515 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,515 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3811148769491803, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,515 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,515 [classy] Re-using computed results
 2023-07-02 10:34:37,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
 2023-07-02 10:34:37,515 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,515 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3811148769491803, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,515 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,534 [fs_likelihood.fslikelihood] Computed log-likelihood = -22.2976
 2023-07-02 10:34:37,534 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,535 [model] Posterior to be computed for parameters {'Omega_m': 0.33485819003418127, 'b1': 0.46823305588415043}
 2023-07-02 10:34:37,535 [prior] Evaluating prior at array([0.33485819, 0.46823306])
 2023-07-02 10:34:37,535 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,535 [model] Got input parameters: {'Omega_m': 0.33485819003418127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46823305588415043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,535 [classy] Got parameters {'Omega_m': 0.33485819003418127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,535 [classy] Computing new state
 2023-07-02 10:34:37,535 [classy] Setting parameters: {'Omega_m': 0.33485819003418127, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.65037772027145}
 2023-07-02 10:34:37,581 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292705
 2023-07-02 10:34:37,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46823305588415043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,583 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,603 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.88467
 2023-07-02 10:34:37,603 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,603 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.5074830659032157}
 2023-07-02 10:34:37,603 [prior] Evaluating prior at array([0.32550764, 0.50748307])
 2023-07-02 10:34:37,603 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,603 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5074830659032157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,603 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,603 [classy] Re-using computed results
 2023-07-02 10:34:37,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
 2023-07-02 10:34:37,603 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5074830659032157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,603 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.436058
 2023-07-02 10:34:37,622 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,623 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.46562780994757685}
 2023-07-02 10:34:37,623 [prior] Evaluating prior at array([0.33635685, 0.46562781])
 2023-07-02 10:34:37,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,623 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46562780994757685, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,623 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,623 [classy] Computing new state
 2023-07-02 10:34:37,623 [classy] Setting parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,669 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:37,669 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,671 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.033177
 2023-07-02 10:34:37,671 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46562780994757685, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,671 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,690 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.580561
 2023-07-02 10:34:37,690 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,691 [mcmc] New sample, #751:
   Omega_m:0.3255076, b1:0.4844879
 2023-07-02 10:34:37,691 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.4628278680361772}
 2023-07-02 10:34:37,691 [prior] Evaluating prior at array([0.33635685, 0.46282787])
 2023-07-02 10:34:37,691 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,691 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4628278680361772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,691 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,691 [classy] Re-using computed results
 2023-07-02 10:34:37,691 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:37,691 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4628278680361772, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,691 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,711 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.620249
 2023-07-02 10:34:37,711 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,711 [mcmc] New sample, #752:
   Omega_m:0.3363569, b1:0.4656278
 2023-07-02 10:34:37,711 [model] Posterior to be computed for parameters {'Omega_m': 0.3811396943962407, 'b1': 0.38497828814531226}
 2023-07-02 10:34:37,712 [prior] Evaluating prior at array([0.38113969, 0.38497829])
 2023-07-02 10:34:37,712 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,712 [model] Got input parameters: {'Omega_m': 0.3811396943962407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38497828814531226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,712 [classy] Got parameters {'Omega_m': 0.3811396943962407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,712 [classy] Computing new state
 2023-07-02 10:34:37,712 [classy] Setting parameters: {'Omega_m': 0.3811396943962407, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.7215758872967}
 2023-07-02 10:34:37,758 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.246389
 2023-07-02 10:34:37,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38497828814531226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,760 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,779 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5541
 2023-07-02 10:34:37,779 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,779 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.49827872943770196}
 2023-07-02 10:34:37,779 [prior] Evaluating prior at array([0.33635685, 0.49827873])
 2023-07-02 10:34:37,779 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,779 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49827872943770196, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,779 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,779 [classy] Re-using computed results
 2023-07-02 10:34:37,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:37,779 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49827872943770196, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,780 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.19835
 2023-07-02 10:34:37,799 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,799 [model] Posterior to be computed for parameters {'Omega_m': 0.3713272153695658, 'b1': 0.4020361021016301}
 2023-07-02 10:34:37,799 [prior] Evaluating prior at array([0.37132722, 0.4020361 ])
 2023-07-02 10:34:37,799 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,799 [model] Got input parameters: {'Omega_m': 0.3713272153695658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4020361021016301, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,799 [classy] Got parameters {'Omega_m': 0.3713272153695658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,800 [classy] Computing new state
 2023-07-02 10:34:37,800 [classy] Setting parameters: {'Omega_m': 0.3713272153695658, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.7183639463817}
 2023-07-02 10:34:37,846 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.185025
 2023-07-02 10:34:37,848 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4020361021016301, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,848 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,867 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.0455
 2023-07-02 10:34:37,867 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,867 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.48699445666645913}
 2023-07-02 10:34:37,867 [prior] Evaluating prior at array([0.33635685, 0.48699446])
 2023-07-02 10:34:37,867 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,867 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48699445666645913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,868 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,868 [classy] Re-using computed results
 2023-07-02 10:34:37,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:37,868 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,868 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48699445666645913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,868 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,887 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.18496
 2023-07-02 10:34:37,887 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3503070525538146, 'b1': 0.43857712559506806}
 2023-07-02 10:34:37,887 [prior] Evaluating prior at array([0.35030705, 0.43857713])
 2023-07-02 10:34:37,887 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,887 [model] Got input parameters: {'Omega_m': 0.3503070525538146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43857712559506806, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,887 [classy] Got parameters {'Omega_m': 0.3503070525538146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,887 [classy] Computing new state
 2023-07-02 10:34:37,888 [classy] Setting parameters: {'Omega_m': 0.3503070525538146, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:37,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.93889326041227}
 2023-07-02 10:34:37,935 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:37,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0803074
 2023-07-02 10:34:37,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43857712559506806, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,937 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,957 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.0575
 2023-07-02 10:34:37,957 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,957 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.4840158747602889}
 2023-07-02 10:34:37,957 [prior] Evaluating prior at array([0.33635685, 0.48401587])
 2023-07-02 10:34:37,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,958 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4840158747602889, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,958 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,958 [classy] Re-using computed results
 2023-07-02 10:34:37,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:37,958 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:37,958 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4840158747602889, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,958 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:37,977 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.780399
 2023-07-02 10:34:37,977 [model] Computed derived parameters: {}
 2023-07-02 10:34:37,977 [model] Posterior to be computed for parameters {'Omega_m': 0.35907154372119454, 'b1': 0.4233411124175072}
 2023-07-02 10:34:37,977 [prior] Evaluating prior at array([0.35907154, 0.42334111])
 2023-07-02 10:34:37,978 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:37,978 [model] Got input parameters: {'Omega_m': 0.35907154372119454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4233411124175072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:37,978 [classy] Got parameters {'Omega_m': 0.35907154372119454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:37,978 [classy] Computing new state
 2023-07-02 10:34:37,978 [classy] Setting parameters: {'Omega_m': 0.35907154372119454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,024 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99841206500398}
 2023-07-02 10:34:38,025 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,026 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119309
 2023-07-02 10:34:38,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4233411124175072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,027 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.07346
 2023-07-02 10:34:38,046 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,046 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.4729556847783608}
 2023-07-02 10:34:38,046 [prior] Evaluating prior at array([0.33635685, 0.47295568])
 2023-07-02 10:34:38,047 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,047 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4729556847783608, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,047 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,047 [classy] Re-using computed results
 2023-07-02 10:34:38,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:38,047 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,047 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4729556847783608, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,047 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,067 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.269415
 2023-07-02 10:34:38,067 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,067 [mcmc] New sample, #753:
   Omega_m:0.3363569, b1:0.4628279
 2023-07-02 10:34:38,067 [model] Posterior to be computed for parameters {'Omega_m': 0.34532150705747455, 'b1': 0.4573717132231961}
 2023-07-02 10:34:38,067 [prior] Evaluating prior at array([0.34532151, 0.45737171])
 2023-07-02 10:34:38,067 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,067 [model] Got input parameters: {'Omega_m': 0.34532150705747455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4573717132231961, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,067 [classy] Got parameters {'Omega_m': 0.34532150705747455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,067 [classy] Computing new state
 2023-07-02 10:34:38,067 [classy] Setting parameters: {'Omega_m': 0.34532150705747455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.48352484527382}
 2023-07-02 10:34:38,115 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,117 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0612887
 2023-07-02 10:34:38,117 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4573717132231961, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,117 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,139 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.95946
 2023-07-02 10:34:38,139 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,139 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.49949218989880756}
 2023-07-02 10:34:38,139 [prior] Evaluating prior at array([0.33635685, 0.49949219])
 2023-07-02 10:34:38,139 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,139 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49949218989880756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,139 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,139 [classy] Re-using computed results
 2023-07-02 10:34:38,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:38,139 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49949218989880756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,139 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,159 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.46085
 2023-07-02 10:34:38,160 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,160 [model] Posterior to be computed for parameters {'Omega_m': 0.3445862425760497, 'b1': 0.4586498820425881}
 2023-07-02 10:34:38,160 [prior] Evaluating prior at array([0.34458624, 0.45864988])
 2023-07-02 10:34:38,160 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,160 [model] Got input parameters: {'Omega_m': 0.3445862425760497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4586498820425881, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,160 [classy] Got parameters {'Omega_m': 0.3445862425760497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,160 [classy] Computing new state
 2023-07-02 10:34:38,160 [classy] Setting parameters: {'Omega_m': 0.3445862425760497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,207 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.56445448044835}
 2023-07-02 10:34:38,207 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,208 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0586847
 2023-07-02 10:34:38,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4586498820425881, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,208 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,228 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.75314
 2023-07-02 10:34:38,228 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,228 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.45542141185437185}
 2023-07-02 10:34:38,228 [prior] Evaluating prior at array([0.33635685, 0.45542141])
 2023-07-02 10:34:38,228 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,228 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45542141185437185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,228 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,228 [classy] Re-using computed results
 2023-07-02 10:34:38,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:38,228 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45542141185437185, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,229 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,248 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.517815
 2023-07-02 10:34:38,248 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,248 [mcmc] New sample, #754:
   Omega_m:0.3363569, b1:0.4729557
 2023-07-02 10:34:38,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3755867455110882, 'b1': 0.3872249653597034}
 2023-07-02 10:34:38,248 [prior] Evaluating prior at array([0.37558675, 0.38722497])
 2023-07-02 10:34:38,248 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,248 [model] Got input parameters: {'Omega_m': 0.3755867455110882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3872249653597034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,248 [classy] Got parameters {'Omega_m': 0.3755867455110882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,248 [classy] Computing new state
 2023-07-02 10:34:38,248 [classy] Setting parameters: {'Omega_m': 0.3755867455110882, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.28264618587073}
 2023-07-02 10:34:38,296 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,298 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.210747
 2023-07-02 10:34:38,298 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3872249653597034, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,298 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,318 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.9772
 2023-07-02 10:34:38,318 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,319 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.45654731895382333}
 2023-07-02 10:34:38,319 [prior] Evaluating prior at array([0.33635685, 0.45654732])
 2023-07-02 10:34:38,319 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,319 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45654731895382333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,319 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,319 [classy] Re-using computed results
 2023-07-02 10:34:38,319 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
 2023-07-02 10:34:38,319 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45654731895382333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,319 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,338 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.552611
 2023-07-02 10:34:38,338 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,338 [mcmc] New sample, #755:
   Omega_m:0.3363569, b1:0.4554214
 2023-07-02 10:34:38,339 [model] Posterior to be computed for parameters {'Omega_m': 0.3265152158172258, 'b1': 0.47365582157490144}
 2023-07-02 10:34:38,339 [prior] Evaluating prior at array([0.32651522, 0.47365582])
 2023-07-02 10:34:38,339 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,339 [model] Got input parameters: {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47365582157490144, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,339 [classy] Got parameters {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,339 [classy] Computing new state
 2023-07-02 10:34:38,339 [classy] Setting parameters: {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.60467261049305}
 2023-07-02 10:34:38,385 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0118658
 2023-07-02 10:34:38,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47365582157490144, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,387 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,407 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14824
 2023-07-02 10:34:38,407 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,407 [mcmc] New sample, #756:
   Omega_m:0.3363569, b1:0.4565473
 2023-07-02 10:34:38,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3265152158172258, 'b1': 0.4438026901837657}
 2023-07-02 10:34:38,407 [prior] Evaluating prior at array([0.32651522, 0.44380269])
 2023-07-02 10:34:38,407 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,407 [model] Got input parameters: {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4438026901837657, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,408 [classy] Got parameters {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,408 [classy] Re-using computed results
 2023-07-02 10:34:38,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.60467261049305}
 2023-07-02 10:34:38,408 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,408 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4438026901837657, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,408 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,428 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10147
 2023-07-02 10:34:38,428 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,428 [model] Posterior to be computed for parameters {'Omega_m': 0.31569369555732, 'b1': 0.49246773228739227}
 2023-07-02 10:34:38,428 [prior] Evaluating prior at array([0.3156937 , 0.49246773])
 2023-07-02 10:34:38,428 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,428 [model] Got input parameters: {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49246773228739227, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,428 [classy] Got parameters {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,428 [classy] Computing new state
 2023-07-02 10:34:38,428 [classy] Setting parameters: {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,475 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87565400572376}
 2023-07-02 10:34:38,475 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,477 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000829195
 2023-07-02 10:34:38,477 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49246773228739227, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,477 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,501 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80784
 2023-07-02 10:34:38,501 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,501 [mcmc] New sample, #757:
   Omega_m:0.3265152, b1:0.4736558
 2023-07-02 10:34:38,502 [model] Posterior to be computed for parameters {'Omega_m': 0.31569369555732, 'b1': 0.5113203711058749}
 2023-07-02 10:34:38,502 [prior] Evaluating prior at array([0.3156937 , 0.51132037])
 2023-07-02 10:34:38,502 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,502 [model] Got input parameters: {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5113203711058749, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,502 [classy] Got parameters {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,502 [classy] Re-using computed results
 2023-07-02 10:34:38,502 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87565400572376}
 2023-07-02 10:34:38,502 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,502 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5113203711058749, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,502 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,524 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51671
 2023-07-02 10:34:38,524 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,524 [model] Posterior to be computed for parameters {'Omega_m': 0.31379880877790595, 'b1': 0.49576176492314755}
 2023-07-02 10:34:38,524 [prior] Evaluating prior at array([0.31379881, 0.49576176])
 2023-07-02 10:34:38,525 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,525 [model] Got input parameters: {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49576176492314755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,525 [classy] Got parameters {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,525 [classy] Computing new state
 2023-07-02 10:34:38,525 [classy] Setting parameters: {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,585 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10220557808188}
 2023-07-02 10:34:38,585 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,587 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000308072
 2023-07-02 10:34:38,587 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49576176492314755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,587 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,608 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79327
 2023-07-02 10:34:38,608 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,608 [mcmc] New sample, #758:
   Omega_m:0.3156937, b1:0.4924677
 2023-07-02 10:34:38,608 [model] Posterior to be computed for parameters {'Omega_m': 0.31379880877790595, 'b1': 0.4593721149852985}
 2023-07-02 10:34:38,608 [prior] Evaluating prior at array([0.31379881, 0.45937211])
 2023-07-02 10:34:38,608 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,608 [model] Got input parameters: {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4593721149852985, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,608 [classy] Got parameters {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,608 [classy] Re-using computed results
 2023-07-02 10:34:38,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10220557808188}
 2023-07-02 10:34:38,608 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4593721149852985, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,608 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,629 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.88607
 2023-07-02 10:34:38,629 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,629 [model] Posterior to be computed for parameters {'Omega_m': 0.33139865813599606, 'b1': 0.4651665447760882}
 2023-07-02 10:34:38,629 [prior] Evaluating prior at array([0.33139866, 0.46516654])
 2023-07-02 10:34:38,629 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,629 [model] Got input parameters: {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4651665447760882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,629 [classy] Got parameters {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,629 [classy] Computing new state
 2023-07-02 10:34:38,629 [classy] Setting parameters: {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.04344216152742}
 2023-07-02 10:34:38,676 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0211496
 2023-07-02 10:34:38,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4651665447760882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,678 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,700 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46687
 2023-07-02 10:34:38,700 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,700 [mcmc] New sample, #759:
   Omega_m:0.3137988, b1:0.4957618
 2023-07-02 10:34:38,700 [model] Posterior to be computed for parameters {'Omega_m': 0.33139865813599606, 'b1': 0.411127302665654}
 2023-07-02 10:34:38,700 [prior] Evaluating prior at array([0.33139866, 0.4111273 ])
 2023-07-02 10:34:38,700 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,700 [model] Got input parameters: {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.411127302665654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,700 [classy] Got parameters {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,700 [classy] Re-using computed results
 2023-07-02 10:34:38,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.04344216152742}
 2023-07-02 10:34:38,700 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,700 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.411127302665654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,700 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,722 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.56461
 2023-07-02 10:34:38,722 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,722 [model] Posterior to be computed for parameters {'Omega_m': 0.33346782254831997, 'b1': 0.461569551448051}
 2023-07-02 10:34:38,722 [prior] Evaluating prior at array([0.33346782, 0.46156955])
 2023-07-02 10:34:38,722 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,722 [model] Got input parameters: {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.461569551448051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,722 [classy] Got parameters {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,722 [classy] Computing new state
 2023-07-02 10:34:38,723 [classy] Setting parameters: {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,769 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.80790504176113}
 2023-07-02 10:34:38,769 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,771 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0258554
 2023-07-02 10:34:38,771 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.461569551448051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,771 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,791 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.11172
 2023-07-02 10:34:38,791 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,791 [mcmc] New sample, #760:
   Omega_m:0.3313987, b1:0.4651665
 2023-07-02 10:34:38,791 [model] Posterior to be computed for parameters {'Omega_m': 0.33346782254831997, 'b1': 0.4969515998280746}
 2023-07-02 10:34:38,791 [prior] Evaluating prior at array([0.33346782, 0.4969516 ])
 2023-07-02 10:34:38,791 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,791 [model] Got input parameters: {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4969515998280746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,791 [classy] Got parameters {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,791 [classy] Re-using computed results
 2023-07-02 10:34:38,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.80790504176113}
 2023-07-02 10:34:38,791 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,791 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4969515998280746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,791 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,811 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.36627
 2023-07-02 10:34:38,812 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,812 [model] Posterior to be computed for parameters {'Omega_m': 0.3315139141755904, 'b1': 0.46496618602113987}
 2023-07-02 10:34:38,812 [prior] Evaluating prior at array([0.33151391, 0.46496619])
 2023-07-02 10:34:38,812 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,812 [model] Got input parameters: {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46496618602113987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,812 [classy] Got parameters {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,812 [classy] Computing new state
 2023-07-02 10:34:38,812 [classy] Setting parameters: {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0302858588546}
 2023-07-02 10:34:38,858 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0213999
 2023-07-02 10:34:38,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46496618602113987, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,860 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,880 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44811
 2023-07-02 10:34:38,880 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,880 [mcmc] New sample, #761:
   Omega_m:0.3334678, b1:0.4615696
 2023-07-02 10:34:38,880 [model] Posterior to be computed for parameters {'Omega_m': 0.3315139141755904, 'b1': 0.5687986012798748}
 2023-07-02 10:34:38,881 [prior] Evaluating prior at array([0.33151391, 0.5687986 ])
 2023-07-02 10:34:38,881 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,881 [model] Got input parameters: {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5687986012798748, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,881 [classy] Got parameters {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,881 [classy] Re-using computed results
 2023-07-02 10:34:38,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0302858588546}
 2023-07-02 10:34:38,881 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,881 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5687986012798748, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,881 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,900 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.6885
 2023-07-02 10:34:38,900 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,900 [model] Posterior to be computed for parameters {'Omega_m': 0.3003077317290742, 'b1': 0.5192143788593125}
 2023-07-02 10:34:38,901 [prior] Evaluating prior at array([0.30030773, 0.51921438])
 2023-07-02 10:34:38,901 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,901 [model] Got input parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5192143788593125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,901 [classy] Got parameters {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,901 [classy] Computing new state
 2023-07-02 10:34:38,901 [classy] Setting parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:38,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7510903153864}
 2023-07-02 10:34:38,948 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:38,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00957637
 2023-07-02 10:34:38,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5192143788593125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,950 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,970 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.43984
 2023-07-02 10:34:38,970 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,970 [mcmc] New sample, #762:
   Omega_m:0.3315139, b1:0.4649662
 2023-07-02 10:34:38,970 [model] Posterior to be computed for parameters {'Omega_m': 0.3003077317290742, 'b1': 0.4695065455964744}
 2023-07-02 10:34:38,970 [prior] Evaluating prior at array([0.30030773, 0.46950655])
 2023-07-02 10:34:38,970 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,970 [model] Got input parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4695065455964744, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,970 [classy] Got parameters {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,970 [classy] Re-using computed results
 2023-07-02 10:34:38,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7510903153864}
 2023-07-02 10:34:38,971 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:38,971 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4695065455964744, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,971 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:38,990 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.69413
 2023-07-02 10:34:38,990 [model] Computed derived parameters: {}
 2023-07-02 10:34:38,990 [model] Posterior to be computed for parameters {'Omega_m': 0.2786128976831972, 'b1': 0.5569282370965375}
 2023-07-02 10:34:38,990 [prior] Evaluating prior at array([0.2786129 , 0.55692824])
 2023-07-02 10:34:38,990 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:38,990 [model] Got input parameters: {'Omega_m': 0.2786128976831972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5569282370965375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:38,990 [classy] Got parameters {'Omega_m': 0.2786128976831972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:38,990 [classy] Computing new state
 2023-07-02 10:34:38,990 [classy] Setting parameters: {'Omega_m': 0.2786128976831972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.54367566879856}
 2023-07-02 10:34:39,037 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0769594
 2023-07-02 10:34:39,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5569282370965375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,039 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,059 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.0662
 2023-07-02 10:34:39,059 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,059 [model] Posterior to be computed for parameters {'Omega_m': 0.3003077317290742, 'b1': 0.5394917723483511}
 2023-07-02 10:34:39,059 [prior] Evaluating prior at array([0.30030773, 0.53949177])
 2023-07-02 10:34:39,059 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,059 [model] Got input parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5394917723483511, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,059 [classy] Got parameters {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,059 [classy] Re-using computed results
 2023-07-02 10:34:39,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7510903153864}
 2023-07-02 10:34:39,060 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5394917723483511, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,060 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,080 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.18292
 2023-07-02 10:34:39,080 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,080 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5104845832163388}
 2023-07-02 10:34:39,080 [prior] Evaluating prior at array([0.30532953, 0.51048458])
 2023-07-02 10:34:39,080 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,080 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5104845832163388, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,080 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,080 [classy] Computing new state
 2023-07-02 10:34:39,080 [classy] Setting parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,130 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00339803
 2023-07-02 10:34:39,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5104845832163388, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,133 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,153 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21057
 2023-07-02 10:34:39,153 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,153 [mcmc] New sample, #763:
   Omega_m:0.3003077, b1:0.5192144
 2023-07-02 10:34:39,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5236493443246252}
 2023-07-02 10:34:39,153 [prior] Evaluating prior at array([0.30532953, 0.52364934])
 2023-07-02 10:34:39,153 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,153 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5236493443246252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,153 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,153 [classy] Re-using computed results
 2023-07-02 10:34:39,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,153 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5236493443246252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,153 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,173 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26823
 2023-07-02 10:34:39,173 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,173 [mcmc] New sample, #764:
   Omega_m:0.3053295, b1:0.5104846
 2023-07-02 10:34:39,173 [model] Posterior to be computed for parameters {'Omega_m': 0.23460781564004618, 'b1': 0.6465905377749988}
 2023-07-02 10:34:39,173 [prior] Evaluating prior at array([0.23460782, 0.64659054])
 2023-07-02 10:34:39,173 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,173 [model] Got input parameters: {'Omega_m': 0.23460781564004618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6465905377749988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,173 [classy] Got parameters {'Omega_m': 0.23460781564004618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,173 [classy] Computing new state
 2023-07-02 10:34:39,174 [classy] Setting parameters: {'Omega_m': 0.23460781564004618, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.82599679170184}
 2023-07-02 10:34:39,220 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.459036
 2023-07-02 10:34:39,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6465905377749988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,222 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,241 [fs_likelihood.fslikelihood] Computed log-likelihood = -48.1099
 2023-07-02 10:34:39,241 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,241 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.48401793403836596}
 2023-07-02 10:34:39,241 [prior] Evaluating prior at array([0.30532953, 0.48401793])
 2023-07-02 10:34:39,241 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,241 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48401793403836596, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,241 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,241 [classy] Re-using computed results
 2023-07-02 10:34:39,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,242 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48401793403836596, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,242 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,261 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.607945
 2023-07-02 10:34:39,261 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,261 [model] Posterior to be computed for parameters {'Omega_m': 0.33810979996237267, 'b1': 0.46666479343654244}
 2023-07-02 10:34:39,261 [prior] Evaluating prior at array([0.3381098 , 0.46666479])
 2023-07-02 10:34:39,261 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,261 [model] Got input parameters: {'Omega_m': 0.33810979996237267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46666479343654244, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,261 [classy] Got parameters {'Omega_m': 0.33810979996237267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,261 [classy] Computing new state
 2023-07-02 10:34:39,261 [classy] Setting parameters: {'Omega_m': 0.33810979996237267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28426163359194}
 2023-07-02 10:34:39,307 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0380397
 2023-07-02 10:34:39,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46666479343654244, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,309 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,329 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.06168
 2023-07-02 10:34:39,329 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,329 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5354878330613593}
 2023-07-02 10:34:39,329 [prior] Evaluating prior at array([0.30532953, 0.53548783])
 2023-07-02 10:34:39,329 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,329 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5354878330613593, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,329 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,329 [classy] Re-using computed results
 2023-07-02 10:34:39,329 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,329 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,329 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5354878330613593, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,329 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,348 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51706
 2023-07-02 10:34:39,348 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,349 [model] Posterior to be computed for parameters {'Omega_m': 0.3414181474454102, 'b1': 0.4609136294630863}
 2023-07-02 10:34:39,349 [prior] Evaluating prior at array([0.34141815, 0.46091363])
 2023-07-02 10:34:39,349 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,349 [model] Got input parameters: {'Omega_m': 0.3414181474454102, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4609136294630863, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,349 [classy] Got parameters {'Omega_m': 0.3414181474454102, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,349 [classy] Computing new state
 2023-07-02 10:34:39,349 [classy] Setting parameters: {'Omega_m': 0.3414181474454102, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.91501721580573}
 2023-07-02 10:34:39,395 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,397 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0480649
 2023-07-02 10:34:39,397 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4609136294630863, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,397 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,416 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.729208
 2023-07-02 10:34:39,417 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,417 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5183514789114523}
 2023-07-02 10:34:39,417 [prior] Evaluating prior at array([0.30532953, 0.51835148])
 2023-07-02 10:34:39,417 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,417 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183514789114523, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,417 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,417 [classy] Re-using computed results
 2023-07-02 10:34:39,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,417 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,417 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183514789114523, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,417 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,437 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35618
 2023-07-02 10:34:39,437 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,437 [mcmc] New sample, #765:
   Omega_m:0.3053295, b1:0.5236493
 2023-07-02 10:34:39,437 [model] Posterior to be computed for parameters {'Omega_m': 0.28541073712308157, 'b1': 0.5529779069759072}
 2023-07-02 10:34:39,437 [prior] Evaluating prior at array([0.28541074, 0.55297791])
 2023-07-02 10:34:39,437 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,437 [model] Got input parameters: {'Omega_m': 0.28541073712308157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5529779069759072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,438 [classy] Got parameters {'Omega_m': 0.28541073712308157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,438 [classy] Computing new state
 2023-07-02 10:34:39,438 [classy] Setting parameters: {'Omega_m': 0.28541073712308157, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.64898226471203}
 2023-07-02 10:34:39,484 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,486 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0483665
 2023-07-02 10:34:39,486 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5529779069759072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,486 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,505 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.72614
 2023-07-02 10:34:39,505 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,506 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5344592517950444}
 2023-07-02 10:34:39,506 [prior] Evaluating prior at array([0.30532953, 0.53445925])
 2023-07-02 10:34:39,506 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,506 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5344592517950444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,506 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,506 [classy] Re-using computed results
 2023-07-02 10:34:39,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,506 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5344592517950444, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,506 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,525 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.6132
 2023-07-02 10:34:39,525 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,526 [model] Posterior to be computed for parameters {'Omega_m': 0.2695130115049873, 'b1': 0.5806141898341783}
 2023-07-02 10:34:39,526 [prior] Evaluating prior at array([0.26951301, 0.58061419])
 2023-07-02 10:34:39,526 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,526 [model] Got input parameters: {'Omega_m': 0.2695130115049873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5806141898341783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,526 [classy] Got parameters {'Omega_m': 0.2695130115049873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,526 [classy] Computing new state
 2023-07-02 10:34:39,526 [classy] Setting parameters: {'Omega_m': 0.2695130115049873, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.77098650270267}
 2023-07-02 10:34:39,573 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.126801
 2023-07-02 10:34:39,575 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5806141898341783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,575 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,594 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2842
 2023-07-02 10:34:39,594 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,594 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.4909378201764896}
 2023-07-02 10:34:39,594 [prior] Evaluating prior at array([0.30532953, 0.49093782])
 2023-07-02 10:34:39,594 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,594 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4909378201764896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,594 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,594 [classy] Re-using computed results
 2023-07-02 10:34:39,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
 2023-07-02 10:34:39,595 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,595 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4909378201764896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,595 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,614 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.465948
 2023-07-02 10:34:39,614 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,614 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.48216740425980387}
 2023-07-02 10:34:39,614 [prior] Evaluating prior at array([0.32614436, 0.4821674 ])
 2023-07-02 10:34:39,614 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,614 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48216740425980387, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,614 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,614 [classy] Computing new state
 2023-07-02 10:34:39,614 [classy] Setting parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
 2023-07-02 10:34:39,660 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0112673
 2023-07-02 10:34:39,662 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48216740425980387, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,662 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,682 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27148
 2023-07-02 10:34:39,682 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,682 [mcmc] New sample, #766:
   Omega_m:0.3053295, b1:0.5183515
 2023-07-02 10:34:39,682 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.4497161625034583}
 2023-07-02 10:34:39,682 [prior] Evaluating prior at array([0.32614436, 0.44971616])
 2023-07-02 10:34:39,683 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,683 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4497161625034583, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,683 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,683 [classy] Re-using computed results
 2023-07-02 10:34:39,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
 2023-07-02 10:34:39,683 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4497161625034583, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,683 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,702 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.160427
 2023-07-02 10:34:39,702 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,702 [model] Posterior to be computed for parameters {'Omega_m': 0.27772982751507047, 'b1': 0.5663302440104706}
 2023-07-02 10:34:39,702 [prior] Evaluating prior at array([0.27772983, 0.56633024])
 2023-07-02 10:34:39,703 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,703 [model] Got input parameters: {'Omega_m': 0.27772982751507047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5663302440104706, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,703 [classy] Got parameters {'Omega_m': 0.27772982751507047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,703 [classy] Computing new state
 2023-07-02 10:34:39,703 [classy] Setting parameters: {'Omega_m': 0.27772982751507047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,749 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.66126454272208}
 2023-07-02 10:34:39,749 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,751 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0812041
 2023-07-02 10:34:39,751 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5663302440104706, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,751 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,770 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.31035
 2023-07-02 10:34:39,770 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,770 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.49963888791574146}
 2023-07-02 10:34:39,770 [prior] Evaluating prior at array([0.32614436, 0.49963889])
 2023-07-02 10:34:39,771 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,771 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49963888791574146, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,771 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,771 [classy] Re-using computed results
 2023-07-02 10:34:39,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
 2023-07-02 10:34:39,771 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,771 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49963888791574146, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,771 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,790 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22596
 2023-07-02 10:34:39,790 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,790 [model] Posterior to be computed for parameters {'Omega_m': 0.40661443212211046, 'b1': 0.3422798688459525}
 2023-07-02 10:34:39,790 [prior] Evaluating prior at array([0.40661443, 0.34227987])
 2023-07-02 10:34:39,791 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,791 [model] Got input parameters: {'Omega_m': 0.40661443212211046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3422798688459525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,791 [classy] Got parameters {'Omega_m': 0.40661443212211046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,791 [classy] Computing new state
 2023-07-02 10:34:39,791 [classy] Setting parameters: {'Omega_m': 0.40661443212211046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,837 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.24253741553542}
 2023-07-02 10:34:39,837 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,839 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.438279
 2023-07-02 10:34:39,839 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3422798688459525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,839 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,858 [fs_likelihood.fslikelihood] Computed log-likelihood = -28.8837
 2023-07-02 10:34:39,858 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,858 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.478452255207607}
 2023-07-02 10:34:39,859 [prior] Evaluating prior at array([0.32614436, 0.47845226])
 2023-07-02 10:34:39,859 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,859 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.478452255207607, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,859 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,859 [classy] Re-using computed results
 2023-07-02 10:34:39,859 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
 2023-07-02 10:34:39,859 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,859 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.478452255207607, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,859 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,878 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2751
 2023-07-02 10:34:39,879 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,879 [mcmc] New sample, #767:
   Omega_m:0.3261444, b1:0.4821674
 2023-07-02 10:34:39,879 [model] Posterior to be computed for parameters {'Omega_m': 0.29475546985082696, 'b1': 0.5330180646195952}
 2023-07-02 10:34:39,879 [prior] Evaluating prior at array([0.29475547, 0.53301806])
 2023-07-02 10:34:39,879 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,879 [model] Got input parameters: {'Omega_m': 0.29475546985082696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330180646195952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,879 [classy] Got parameters {'Omega_m': 0.29475546985082696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,879 [classy] Computing new state
 2023-07-02 10:34:39,879 [classy] Setting parameters: {'Omega_m': 0.29475546985082696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:39,925 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4486975006506}
 2023-07-02 10:34:39,925 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:39,927 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0203604
 2023-07-02 10:34:39,927 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330180646195952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,927 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,946 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.324234
 2023-07-02 10:34:39,947 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,947 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.4608599315138536}
 2023-07-02 10:34:39,947 [prior] Evaluating prior at array([0.32614436, 0.46085993])
 2023-07-02 10:34:39,947 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,947 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4608599315138536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,947 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,947 [classy] Re-using computed results
 2023-07-02 10:34:39,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
 2023-07-02 10:34:39,947 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:39,947 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4608599315138536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,947 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:39,966 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29069
 2023-07-02 10:34:39,966 [model] Computed derived parameters: {}
 2023-07-02 10:34:39,966 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.4960454618630326}
 2023-07-02 10:34:39,966 [prior] Evaluating prior at array([0.3160239 , 0.49604546])
 2023-07-02 10:34:39,967 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:39,967 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4960454618630326, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:39,967 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:39,967 [classy] Computing new state
 2023-07-02 10:34:39,967 [classy] Setting parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,013 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,013 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,015 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000964149
 2023-07-02 10:34:40,015 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4960454618630326, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,015 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,035 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90678
 2023-07-02 10:34:40,035 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,035 [mcmc] New sample, #768:
   Omega_m:0.3261444, b1:0.4784523
 2023-07-02 10:34:40,035 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.47198623761670777}
 2023-07-02 10:34:40,035 [prior] Evaluating prior at array([0.3160239 , 0.47198624])
 2023-07-02 10:34:40,035 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,035 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47198623761670777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,035 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,035 [classy] Re-using computed results
 2023-07-02 10:34:40,035 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,035 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,035 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47198623761670777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,035 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,055 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07727
 2023-07-02 10:34:40,055 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,055 [model] Posterior to be computed for parameters {'Omega_m': 0.32671646172209057, 'b1': 0.4774577264300984}
 2023-07-02 10:34:40,055 [prior] Evaluating prior at array([0.32671646, 0.47745773])
 2023-07-02 10:34:40,055 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,055 [model] Got input parameters: {'Omega_m': 0.32671646172209057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4774577264300984, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,055 [classy] Got parameters {'Omega_m': 0.32671646172209057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,055 [classy] Computing new state
 2023-07-02 10:34:40,055 [classy] Setting parameters: {'Omega_m': 0.32671646172209057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,101 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58139602975714}
 2023-07-02 10:34:40,101 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,103 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.012197
 2023-07-02 10:34:40,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4774577264300984, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,103 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,124 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20817
 2023-07-02 10:34:40,124 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,125 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.5393181046647049}
 2023-07-02 10:34:40,125 [prior] Evaluating prior at array([0.3160239, 0.5393181])
 2023-07-02 10:34:40,125 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,125 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5393181046647049, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,125 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,125 [classy] Re-using computed results
 2023-07-02 10:34:40,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,125 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,125 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5393181046647049, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,125 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,146 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.76287
 2023-07-02 10:34:40,146 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,146 [model] Posterior to be computed for parameters {'Omega_m': 0.36346288775858804, 'b1': 0.41357848682243187}
 2023-07-02 10:34:40,146 [prior] Evaluating prior at array([0.36346289, 0.41357849])
 2023-07-02 10:34:40,146 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,146 [model] Got input parameters: {'Omega_m': 0.36346288775858804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41357848682243187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,146 [classy] Got parameters {'Omega_m': 0.36346288775858804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,146 [classy] Computing new state
 2023-07-02 10:34:40,146 [classy] Setting parameters: {'Omega_m': 0.36346288775858804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.5351660932445}
 2023-07-02 10:34:40,193 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,195 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.141402
 2023-07-02 10:34:40,195 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41357848682243187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,195 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,214 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.74218
 2023-07-02 10:34:40,214 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,214 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.49112070537120145}
 2023-07-02 10:34:40,214 [prior] Evaluating prior at array([0.3160239 , 0.49112071])
 2023-07-02 10:34:40,215 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,215 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49112070537120145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,215 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,215 [classy] Re-using computed results
 2023-07-02 10:34:40,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,215 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,215 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49112070537120145, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,215 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,235 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77741
 2023-07-02 10:34:40,235 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,235 [mcmc] New sample, #769:
   Omega_m:0.3160239, b1:0.4960455
 2023-07-02 10:34:40,235 [model] Posterior to be computed for parameters {'Omega_m': 0.33346454744745213, 'b1': 0.46080223496787026}
 2023-07-02 10:34:40,235 [prior] Evaluating prior at array([0.33346455, 0.46080223])
 2023-07-02 10:34:40,235 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,235 [model] Got input parameters: {'Omega_m': 0.33346454744745213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46080223496787026, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,235 [classy] Got parameters {'Omega_m': 0.33346454744745213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,235 [classy] Computing new state
 2023-07-02 10:34:40,235 [classy] Setting parameters: {'Omega_m': 0.33346454744745213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8082770406441}
 2023-07-02 10:34:40,282 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,283 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0258476
 2023-07-02 10:34:40,283 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46080223496787026, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,283 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,302 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08839
 2023-07-02 10:34:40,303 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,303 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.43861872524879814}
 2023-07-02 10:34:40,303 [prior] Evaluating prior at array([0.3160239 , 0.43861873])
 2023-07-02 10:34:40,303 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,303 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43861872524879814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,303 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,303 [classy] Re-using computed results
 2023-07-02 10:34:40,303 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,303 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,303 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43861872524879814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,303 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,323 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.18111
 2023-07-02 10:34:40,323 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,323 [model] Posterior to be computed for parameters {'Omega_m': 0.26827142854813074, 'b1': 0.5741326268488268}
 2023-07-02 10:34:40,323 [prior] Evaluating prior at array([0.26827143, 0.57413263])
 2023-07-02 10:34:40,323 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,323 [model] Got input parameters: {'Omega_m': 0.26827142854813074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5741326268488268, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,323 [classy] Got parameters {'Omega_m': 0.26827142854813074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,323 [classy] Computing new state
 2023-07-02 10:34:40,323 [classy] Setting parameters: {'Omega_m': 0.26827142854813074, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,369 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.94116581640944}
 2023-07-02 10:34:40,369 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,371 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.134676
 2023-07-02 10:34:40,371 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5741326268488268, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,371 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,390 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4227
 2023-07-02 10:34:40,390 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,391 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.5168026734130112}
 2023-07-02 10:34:40,391 [prior] Evaluating prior at array([0.3160239 , 0.51680267])
 2023-07-02 10:34:40,391 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,391 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5168026734130112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,391 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,391 [classy] Re-using computed results
 2023-07-02 10:34:40,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,391 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5168026734130112, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,391 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,411 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.00102
 2023-07-02 10:34:40,411 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,411 [mcmc] New sample, #770:
   Omega_m:0.3160239, b1:0.4911207
 2023-07-02 10:34:40,411 [model] Posterior to be computed for parameters {'Omega_m': 0.3283229725643699, 'b1': 0.4954222122079339}
 2023-07-02 10:34:40,411 [prior] Evaluating prior at array([0.32832297, 0.49542221])
 2023-07-02 10:34:40,411 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,411 [model] Got input parameters: {'Omega_m': 0.3283229725643699, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4954222122079339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,411 [classy] Got parameters {'Omega_m': 0.3283229725643699, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,411 [classy] Computing new state
 2023-07-02 10:34:40,411 [classy] Setting parameters: {'Omega_m': 0.3283229725643699, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39603148429538}
 2023-07-02 10:34:40,458 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,459 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150004
 2023-07-02 10:34:40,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4954222122079339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,460 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.980245
 2023-07-02 10:34:40,479 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,479 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.42416777057580346}
 2023-07-02 10:34:40,479 [prior] Evaluating prior at array([0.3160239 , 0.42416777])
 2023-07-02 10:34:40,479 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,479 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42416777057580346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,479 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,479 [classy] Re-using computed results
 2023-07-02 10:34:40,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,479 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,479 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42416777057580346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,480 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,499 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.9002
 2023-07-02 10:34:40,499 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,499 [model] Posterior to be computed for parameters {'Omega_m': 0.29262265512236846, 'b1': 0.557482917912546}
 2023-07-02 10:34:40,499 [prior] Evaluating prior at array([0.29262266, 0.55748292])
 2023-07-02 10:34:40,500 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,500 [model] Got input parameters: {'Omega_m': 0.29262265512236846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.557482917912546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,500 [classy] Got parameters {'Omega_m': 0.29262265512236846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,500 [classy] Computing new state
 2023-07-02 10:34:40,500 [classy] Setting parameters: {'Omega_m': 0.29262265512236846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7197163896965}
 2023-07-02 10:34:40,546 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,548 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0256421
 2023-07-02 10:34:40,548 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.557482917912546, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,548 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,568 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.95211
 2023-07-02 10:34:40,568 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,568 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.481421286094445}
 2023-07-02 10:34:40,568 [prior] Evaluating prior at array([0.3160239 , 0.48142129])
 2023-07-02 10:34:40,568 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,568 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.481421286094445, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,568 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,568 [classy] Re-using computed results
 2023-07-02 10:34:40,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
 2023-07-02 10:34:40,568 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,568 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.481421286094445, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,568 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,588 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15009
 2023-07-02 10:34:40,588 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,588 [mcmc] New sample, #771:
   Omega_m:0.3160239, b1:0.5168027
 2023-07-02 10:34:40,588 [model] Posterior to be computed for parameters {'Omega_m': 0.3175506987124721, 'b1': 0.4787671266478385}
 2023-07-02 10:34:40,588 [prior] Evaluating prior at array([0.3175507 , 0.47876713])
 2023-07-02 10:34:40,588 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,588 [model] Got input parameters: {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4787671266478385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,588 [classy] Got parameters {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,588 [classy] Computing new state
 2023-07-02 10:34:40,589 [classy] Setting parameters: {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65482018296456}
 2023-07-02 10:34:40,635 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,637 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00175689
 2023-07-02 10:34:40,637 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4787671266478385, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,637 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,656 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1324
 2023-07-02 10:34:40,656 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,656 [mcmc] New sample, #772:
   Omega_m:0.3160239, b1:0.4814213
 2023-07-02 10:34:40,656 [model] Posterior to be computed for parameters {'Omega_m': 0.3175506987124721, 'b1': 0.49083957429593067}
 2023-07-02 10:34:40,656 [prior] Evaluating prior at array([0.3175507 , 0.49083957])
 2023-07-02 10:34:40,657 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,657 [model] Got input parameters: {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49083957429593067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,657 [classy] Got parameters {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,657 [classy] Re-using computed results
 2023-07-02 10:34:40,657 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65482018296456}
 2023-07-02 10:34:40,657 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,657 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49083957429593067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,657 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,676 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83176
 2023-07-02 10:34:40,676 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,676 [mcmc] New sample, #773:
   Omega_m:0.3175507, b1:0.4787671
 2023-07-02 10:34:40,676 [model] Posterior to be computed for parameters {'Omega_m': 0.30584831429012355, 'b1': 0.5111827613518297}
 2023-07-02 10:34:40,676 [prior] Evaluating prior at array([0.30584831, 0.51118276])
 2023-07-02 10:34:40,676 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,676 [model] Got input parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5111827613518297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,676 [classy] Got parameters {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,676 [classy] Computing new state
 2023-07-02 10:34:40,676 [classy] Setting parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,723 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.06618918910124}
 2023-07-02 10:34:40,723 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,725 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00294782
 2023-07-02 10:34:40,725 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5111827613518297, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,725 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,745 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32732
 2023-07-02 10:34:40,745 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,745 [mcmc] New sample, #774:
   Omega_m:0.3175507, b1:0.4908396
 2023-07-02 10:34:40,745 [model] Posterior to be computed for parameters {'Omega_m': 0.30584831429012355, 'b1': 0.48785006240798906}
 2023-07-02 10:34:40,745 [prior] Evaluating prior at array([0.30584831, 0.48785006])
 2023-07-02 10:34:40,745 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,745 [model] Got input parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48785006240798906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,745 [classy] Got parameters {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,745 [classy] Re-using computed results
 2023-07-02 10:34:40,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.06618918910124}
 2023-07-02 10:34:40,745 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,746 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48785006240798906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,746 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,765 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.216264
 2023-07-02 10:34:40,765 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,765 [mcmc] New sample, #775:
   Omega_m:0.3058483, b1:0.5111828
 2023-07-02 10:34:40,765 [model] Posterior to be computed for parameters {'Omega_m': 0.3322652118899987, 'b1': 0.44192746493422236}
 2023-07-02 10:34:40,765 [prior] Evaluating prior at array([0.33226521, 0.44192746])
 2023-07-02 10:34:40,765 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,765 [model] Got input parameters: {'Omega_m': 0.3322652118899987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44192746493422236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,765 [classy] Got parameters {'Omega_m': 0.3322652118899987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,765 [classy] Computing new state
 2023-07-02 10:34:40,765 [classy] Setting parameters: {'Omega_m': 0.3322652118899987, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.94463939689018}
 2023-07-02 10:34:40,812 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0230652
 2023-07-02 10:34:40,814 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44192746493422236, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,814 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,833 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.557584
 2023-07-02 10:34:40,833 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,833 [model] Posterior to be computed for parameters {'Omega_m': 0.30584831429012355, 'b1': 0.5426840624558239}
 2023-07-02 10:34:40,833 [prior] Evaluating prior at array([0.30584831, 0.54268406])
 2023-07-02 10:34:40,833 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,833 [model] Got input parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5426840624558239, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,833 [classy] Got parameters {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,833 [classy] Re-using computed results
 2023-07-02 10:34:40,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.06618918910124}
 2023-07-02 10:34:40,833 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,833 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5426840624558239, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,833 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,853 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.603565
 2023-07-02 10:34:40,853 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,854 [mcmc] New sample, #776:
   Omega_m:0.3058483, b1:0.4878501
 2023-07-02 10:34:40,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5384467432916884}
 2023-07-02 10:34:40,854 [prior] Evaluating prior at array([0.30828583, 0.53844674])
 2023-07-02 10:34:40,854 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,854 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5384467432916884, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,854 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,854 [classy] Computing new state
 2023-07-02 10:34:40,854 [classy] Setting parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
 2023-07-02 10:34:40,900 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0012946
 2023-07-02 10:34:40,902 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5384467432916884, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,902 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,922 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.806231
 2023-07-02 10:34:40,922 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,922 [mcmc] New sample, #777:
   Omega_m:0.3058483, b1:0.5426841
 2023-07-02 10:34:40,922 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5800332425820844}
 2023-07-02 10:34:40,922 [prior] Evaluating prior at array([0.30828583, 0.58003324])
 2023-07-02 10:34:40,922 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,923 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5800332425820844, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,923 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,923 [classy] Re-using computed results
 2023-07-02 10:34:40,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
 2023-07-02 10:34:40,923 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:40,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5800332425820844, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,923 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:40,942 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.3921
 2023-07-02 10:34:40,943 [model] Computed derived parameters: {}
 2023-07-02 10:34:40,943 [model] Posterior to be computed for parameters {'Omega_m': 0.2469184908734055, 'b1': 0.645126468863868}
 2023-07-02 10:34:40,943 [prior] Evaluating prior at array([0.24691849, 0.64512647])
 2023-07-02 10:34:40,943 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:40,943 [model] Got input parameters: {'Omega_m': 0.2469184908734055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.645126468863868, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,943 [classy] Got parameters {'Omega_m': 0.2469184908734055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:40,943 [classy] Computing new state
 2023-07-02 10:34:40,943 [classy] Setting parameters: {'Omega_m': 0.2469184908734055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:40,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.976321776195}
 2023-07-02 10:34:40,989 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:40,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.314057
 2023-07-02 10:34:40,991 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.645126468863868, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:40,991 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,010 [fs_likelihood.fslikelihood] Computed log-likelihood = -33.1863
 2023-07-02 10:34:41,011 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,011 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5526399073424195}
 2023-07-02 10:34:41,011 [prior] Evaluating prior at array([0.30828583, 0.55263991])
 2023-07-02 10:34:41,011 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,011 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5526399073424195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,011 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,011 [classy] Re-using computed results
 2023-07-02 10:34:41,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
 2023-07-02 10:34:41,011 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,011 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5526399073424195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,011 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.83095
 2023-07-02 10:34:41,031 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,031 [model] Posterior to be computed for parameters {'Omega_m': 0.2938648706093703, 'b1': 0.5635158372098505}
 2023-07-02 10:34:41,031 [prior] Evaluating prior at array([0.29386487, 0.56351584])
 2023-07-02 10:34:41,031 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,031 [model] Got input parameters: {'Omega_m': 0.2938648706093703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5635158372098505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,031 [classy] Got parameters {'Omega_m': 0.2938648706093703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,031 [classy] Computing new state
 2023-07-02 10:34:41,031 [classy] Setting parameters: {'Omega_m': 0.2938648706093703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.56165806521935}
 2023-07-02 10:34:41,078 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,079 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0224877
 2023-07-02 10:34:41,079 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5635158372098505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,079 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,100 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.53255
 2023-07-02 10:34:41,100 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,100 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5228464856309065}
 2023-07-02 10:34:41,100 [prior] Evaluating prior at array([0.30828583, 0.52284649])
 2023-07-02 10:34:41,100 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,100 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5228464856309065, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,100 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,100 [classy] Re-using computed results
 2023-07-02 10:34:41,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
 2023-07-02 10:34:41,100 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,100 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5228464856309065, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,100 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,120 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36328
 2023-07-02 10:34:41,120 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,120 [mcmc] New sample, #778:
   Omega_m:0.3082858, b1:0.5384467
 2023-07-02 10:34:41,120 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.5308580935480344}
 2023-07-02 10:34:41,120 [prior] Evaluating prior at array([0.30367716, 0.53085809])
 2023-07-02 10:34:41,120 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,120 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308580935480344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,120 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,120 [classy] Computing new state
 2023-07-02 10:34:41,121 [classy] Setting parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
 2023-07-02 10:34:41,169 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,171 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00506472
 2023-07-02 10:34:41,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308580935480344, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,171 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87785
 2023-07-02 10:34:41,190 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,190 [mcmc] New sample, #779:
   Omega_m:0.3082858, b1:0.5228465
 2023-07-02 10:34:41,190 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.5470873425066852}
 2023-07-02 10:34:41,190 [prior] Evaluating prior at array([0.30367716, 0.54708734])
 2023-07-02 10:34:41,191 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,191 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5470873425066852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,191 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,191 [classy] Re-using computed results
 2023-07-02 10:34:41,191 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
 2023-07-02 10:34:41,191 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,191 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5470873425066852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,191 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,211 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.269559
 2023-07-02 10:34:41,211 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,211 [model] Posterior to be computed for parameters {'Omega_m': 0.2816542705360652, 'b1': 0.5691422383555966}
 2023-07-02 10:34:41,211 [prior] Evaluating prior at array([0.28165427, 0.56914224])
 2023-07-02 10:34:41,212 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,212 [model] Got input parameters: {'Omega_m': 0.2816542705360652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5691422383555966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,212 [classy] Got parameters {'Omega_m': 0.2816542705360652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,212 [classy] Computing new state
 2023-07-02 10:34:41,212 [classy] Setting parameters: {'Omega_m': 0.2816542705360652, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,258 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.141101369418}
 2023-07-02 10:34:41,258 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,260 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0632824
 2023-07-02 10:34:41,260 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5691422383555966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,260 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,279 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.53401
 2023-07-02 10:34:41,280 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,280 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.5239350205432896}
 2023-07-02 10:34:41,280 [prior] Evaluating prior at array([0.30367716, 0.52393502])
 2023-07-02 10:34:41,280 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,280 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239350205432896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,280 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,280 [classy] Re-using computed results
 2023-07-02 10:34:41,280 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
 2023-07-02 10:34:41,280 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,280 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239350205432896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,280 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,300 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11981
 2023-07-02 10:34:41,300 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,300 [mcmc] New sample, #780:
   Omega_m:0.3036772, b1:0.5308581
 2023-07-02 10:34:41,300 [model] Posterior to be computed for parameters {'Omega_m': 0.342380037977216, 'b1': 0.45665472637983806}
 2023-07-02 10:34:41,301 [prior] Evaluating prior at array([0.34238004, 0.45665473])
 2023-07-02 10:34:41,301 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,301 [model] Got input parameters: {'Omega_m': 0.342380037977216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45665472637983806, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,301 [classy] Got parameters {'Omega_m': 0.342380037977216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,301 [classy] Computing new state
 2023-07-02 10:34:41,301 [classy] Setting parameters: {'Omega_m': 0.342380037977216, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,347 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.80826801596197}
 2023-07-02 10:34:41,347 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,349 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.051185
 2023-07-02 10:34:41,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45665472637983806, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,350 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,369 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.872241
 2023-07-02 10:34:41,369 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,369 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.503719821139953}
 2023-07-02 10:34:41,369 [prior] Evaluating prior at array([0.30367716, 0.50371982])
 2023-07-02 10:34:41,370 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,370 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.503719821139953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,370 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,370 [classy] Re-using computed results
 2023-07-02 10:34:41,370 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
 2023-07-02 10:34:41,370 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,370 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.503719821139953, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,370 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,389 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36997
 2023-07-02 10:34:41,389 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,389 [mcmc] New sample, #781:
   Omega_m:0.3036772, b1:0.523935
 2023-07-02 10:34:41,389 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5054777485644084}
 2023-07-02 10:34:41,389 [prior] Evaluating prior at array([0.30266592, 0.50547775])
 2023-07-02 10:34:41,389 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,389 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5054777485644084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,389 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,390 [classy] Computing new state
 2023-07-02 10:34:41,390 [classy] Setting parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
 2023-07-02 10:34:41,436 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00626089
 2023-07-02 10:34:41,438 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5054777485644084, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,438 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,458 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.21638
 2023-07-02 10:34:41,458 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,458 [mcmc] New sample, #782:
   Omega_m:0.3036772, b1:0.5037198
 2023-07-02 10:34:41,458 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5442602187845831}
 2023-07-02 10:34:41,459 [prior] Evaluating prior at array([0.30266592, 0.54426022])
 2023-07-02 10:34:41,459 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,459 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5442602187845831, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,459 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,459 [classy] Re-using computed results
 2023-07-02 10:34:41,459 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
 2023-07-02 10:34:41,459 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,459 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5442602187845831, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,459 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,478 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.737774
 2023-07-02 10:34:41,478 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,478 [mcmc] New sample, #783:
   Omega_m:0.3026659, b1:0.5054777
 2023-07-02 10:34:41,479 [model] Posterior to be computed for parameters {'Omega_m': 0.2833346185868904, 'b1': 0.5778653532940432}
 2023-07-02 10:34:41,479 [prior] Evaluating prior at array([0.28333462, 0.57786535])
 2023-07-02 10:34:41,479 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,479 [model] Got input parameters: {'Omega_m': 0.2833346185868904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5778653532940432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,479 [classy] Got parameters {'Omega_m': 0.2833346185868904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,479 [classy] Computing new state
 2023-07-02 10:34:41,479 [classy] Setting parameters: {'Omega_m': 0.2833346185868904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,525 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.92027446112164}
 2023-07-02 10:34:41,525 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,527 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563434
 2023-07-02 10:34:41,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5778653532940432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,527 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,547 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.66759
 2023-07-02 10:34:41,547 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,547 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.4869976580864138}
 2023-07-02 10:34:41,547 [prior] Evaluating prior at array([0.30266592, 0.48699766])
 2023-07-02 10:34:41,547 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,547 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4869976580864138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,547 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,547 [classy] Re-using computed results
 2023-07-02 10:34:41,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
 2023-07-02 10:34:41,547 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4869976580864138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,547 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,568 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.28638
 2023-07-02 10:34:41,568 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,568 [model] Posterior to be computed for parameters {'Omega_m': 0.2910660739730825, 'b1': 0.5644251485067799}
 2023-07-02 10:34:41,568 [prior] Evaluating prior at array([0.29106607, 0.56442515])
 2023-07-02 10:34:41,568 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,568 [model] Got input parameters: {'Omega_m': 0.2910660739730825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5644251485067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,568 [classy] Got parameters {'Omega_m': 0.2910660739730825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,568 [classy] Computing new state
 2023-07-02 10:34:41,568 [classy] Setting parameters: {'Omega_m': 0.2910660739730825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,615 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.91859362843394}
 2023-07-02 10:34:41,615 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,617 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0299053
 2023-07-02 10:34:41,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5644251485067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,617 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,636 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.83744
 2023-07-02 10:34:41,636 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,636 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5348174977176182}
 2023-07-02 10:34:41,636 [prior] Evaluating prior at array([0.30266592, 0.5348175 ])
 2023-07-02 10:34:41,636 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,636 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5348174977176182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,636 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,636 [classy] Re-using computed results
 2023-07-02 10:34:41,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
 2023-07-02 10:34:41,636 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,636 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5348174977176182, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,636 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,656 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60417
 2023-07-02 10:34:41,656 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,657 [mcmc] New sample, #784:
   Omega_m:0.3026659, b1:0.5442602
 2023-07-02 10:34:41,657 [model] Posterior to be computed for parameters {'Omega_m': 0.26220290395518897, 'b1': 0.6051575751284248}
 2023-07-02 10:34:41,657 [prior] Evaluating prior at array([0.2622029 , 0.60515758])
 2023-07-02 10:34:41,657 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,657 [model] Got input parameters: {'Omega_m': 0.26220290395518897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6051575751284248, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,657 [classy] Got parameters {'Omega_m': 0.26220290395518897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,657 [classy] Computing new state
 2023-07-02 10:34:41,657 [classy] Setting parameters: {'Omega_m': 0.26220290395518897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,703 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.78261164877955}
 2023-07-02 10:34:41,703 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,705 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17704
 2023-07-02 10:34:41,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6051575751284248, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,706 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,726 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.0012
 2023-07-02 10:34:41,726 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,726 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5444710670383351}
 2023-07-02 10:34:41,726 [prior] Evaluating prior at array([0.30266592, 0.54447107])
 2023-07-02 10:34:41,726 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,726 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5444710670383351, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,726 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,726 [classy] Re-using computed results
 2023-07-02 10:34:41,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
 2023-07-02 10:34:41,726 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,726 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5444710670383351, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,726 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,745 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.712706
 2023-07-02 10:34:41,746 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,746 [mcmc] New sample, #785:
   Omega_m:0.3026659, b1:0.5348175
 2023-07-02 10:34:41,746 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5414884131268335}
 2023-07-02 10:34:41,746 [prior] Evaluating prior at array([0.30438168, 0.54148841])
 2023-07-02 10:34:41,746 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,746 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5414884131268335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,746 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,746 [classy] Computing new state
 2023-07-02 10:34:41,746 [classy] Setting parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:41,793 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,794 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00431064
 2023-07-02 10:34:41,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5414884131268335, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,794 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,815 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.936685
 2023-07-02 10:34:41,815 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,815 [mcmc] New sample, #786:
   Omega_m:0.3026659, b1:0.5444711
 2023-07-02 10:34:41,815 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5752089902239124}
 2023-07-02 10:34:41,815 [prior] Evaluating prior at array([0.30438168, 0.57520899])
 2023-07-02 10:34:41,815 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,815 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5752089902239124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,815 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,815 [classy] Re-using computed results
 2023-07-02 10:34:41,815 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:41,815 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,815 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5752089902239124, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,815 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,835 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46639
 2023-07-02 10:34:41,835 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,835 [model] Posterior to be computed for parameters {'Omega_m': 0.2856089630700188, 'b1': 0.5741225273579887}
 2023-07-02 10:34:41,835 [prior] Evaluating prior at array([0.28560896, 0.57412253])
 2023-07-02 10:34:41,835 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,835 [model] Got input parameters: {'Omega_m': 0.2856089630700188, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5741225273579887, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,835 [classy] Got parameters {'Omega_m': 0.2856089630700188, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,835 [classy] Computing new state
 2023-07-02 10:34:41,835 [classy] Setting parameters: {'Omega_m': 0.2856089630700188, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.6231671360117}
 2023-07-02 10:34:41,882 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,884 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.047639
 2023-07-02 10:34:41,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5741225273579887, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,884 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,903 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75951
 2023-07-02 10:34:41,903 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,903 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5362285178165631}
 2023-07-02 10:34:41,903 [prior] Evaluating prior at array([0.30438168, 0.53622852])
 2023-07-02 10:34:41,903 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,903 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5362285178165631, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,903 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,903 [classy] Re-using computed results
 2023-07-02 10:34:41,903 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:41,903 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,903 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5362285178165631, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,904 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,924 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.49202
 2023-07-02 10:34:41,924 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,924 [mcmc] New sample, #787:
   Omega_m:0.3043817, b1:0.5414884
 2023-07-02 10:34:41,924 [model] Posterior to be computed for parameters {'Omega_m': 0.3369676934174711, 'b1': 0.4795816598369268}
 2023-07-02 10:34:41,924 [prior] Evaluating prior at array([0.33696769, 0.47958166])
 2023-07-02 10:34:41,924 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,924 [model] Got input parameters: {'Omega_m': 0.3369676934174711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4795816598369268, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,924 [classy] Got parameters {'Omega_m': 0.3369676934174711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,924 [classy] Computing new state
 2023-07-02 10:34:41,924 [classy] Setting parameters: {'Omega_m': 0.3369676934174711, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:41,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.41249149916416}
 2023-07-02 10:34:41,971 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:41,973 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0348359
 2023-07-02 10:34:41,973 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4795816598369268, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,973 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:41,992 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.518652
 2023-07-02 10:34:41,992 [model] Computed derived parameters: {}
 2023-07-02 10:34:41,992 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.591308321744088}
 2023-07-02 10:34:41,992 [prior] Evaluating prior at array([0.30438168, 0.59130832])
 2023-07-02 10:34:41,992 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:41,992 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.591308321744088, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,992 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:41,992 [classy] Re-using computed results
 2023-07-02 10:34:41,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:41,992 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:41,992 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.591308321744088, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:41,992 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,012 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4699
 2023-07-02 10:34:42,012 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,012 [model] Posterior to be computed for parameters {'Omega_m': 0.40267265769820704, 'b1': 0.36536148635574106}
 2023-07-02 10:34:42,012 [prior] Evaluating prior at array([0.40267266, 0.36536149])
 2023-07-02 10:34:42,013 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,013 [model] Got input parameters: {'Omega_m': 0.40267265769820704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.36536148635574106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,013 [classy] Got parameters {'Omega_m': 0.40267265769820704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,013 [classy] Computing new state
 2023-07-02 10:34:42,013 [classy] Setting parameters: {'Omega_m': 0.40267265769820704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.61631940004492}
 2023-07-02 10:34:42,061 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,063 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.405723
 2023-07-02 10:34:42,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.36536148635574106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,063 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,083 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.938
 2023-07-02 10:34:42,083 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,083 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5264408056703963}
 2023-07-02 10:34:42,083 [prior] Evaluating prior at array([0.30438168, 0.52644081])
 2023-07-02 10:34:42,083 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,083 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5264408056703963, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,083 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,083 [classy] Re-using computed results
 2023-07-02 10:34:42,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:42,083 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5264408056703963, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,083 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11458
 2023-07-02 10:34:42,102 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,102 [mcmc] New sample, #788:
   Omega_m:0.3043817, b1:0.5362285
 2023-07-02 10:34:42,103 [model] Posterior to be computed for parameters {'Omega_m': 0.3547698331407739, 'b1': 0.43884707008735613}
 2023-07-02 10:34:42,103 [prior] Evaluating prior at array([0.35476983, 0.43884707])
 2023-07-02 10:34:42,103 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,103 [model] Got input parameters: {'Omega_m': 0.3547698331407739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43884707008735613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,103 [classy] Got parameters {'Omega_m': 0.3547698331407739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,103 [classy] Computing new state
 2023-07-02 10:34:42,103 [classy] Setting parameters: {'Omega_m': 0.3547698331407739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.45734625143666}
 2023-07-02 10:34:42,153 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0992993
 2023-07-02 10:34:42,155 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43884707008735613, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,155 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,175 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.81555
 2023-07-02 10:34:42,175 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,175 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5012873130838296}
 2023-07-02 10:34:42,175 [prior] Evaluating prior at array([0.30438168, 0.50128731])
 2023-07-02 10:34:42,175 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,175 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5012873130838296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,175 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,175 [classy] Re-using computed results
 2023-07-02 10:34:42,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:42,175 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,175 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5012873130838296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,175 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,195 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35783
 2023-07-02 10:34:42,195 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,195 [mcmc] New sample, #789:
   Omega_m:0.3043817, b1:0.5264408
 2023-07-02 10:34:42,195 [model] Posterior to be computed for parameters {'Omega_m': 0.3602424143771391, 'b1': 0.40418015359058446}
 2023-07-02 10:34:42,195 [prior] Evaluating prior at array([0.36024241, 0.40418015])
 2023-07-02 10:34:42,195 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,195 [model] Got input parameters: {'Omega_m': 0.3602424143771391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40418015359058446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,195 [classy] Got parameters {'Omega_m': 0.3602424143771391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,196 [classy] Computing new state
 2023-07-02 10:34:42,196 [classy] Setting parameters: {'Omega_m': 0.3602424143771391, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,243 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.8743783163688}
 2023-07-02 10:34:42,243 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,245 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125038
 2023-07-02 10:34:42,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40418015359058446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,245 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.08152
 2023-07-02 10:34:42,265 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,265 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5038994006916178}
 2023-07-02 10:34:42,265 [prior] Evaluating prior at array([0.30438168, 0.5038994 ])
 2023-07-02 10:34:42,265 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,265 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038994006916178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,265 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,265 [classy] Re-using computed results
 2023-07-02 10:34:42,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:42,265 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,265 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038994006916178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,265 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58925
 2023-07-02 10:34:42,285 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,285 [mcmc] New sample, #790:
   Omega_m:0.3043817, b1:0.5012873
 2023-07-02 10:34:42,285 [model] Posterior to be computed for parameters {'Omega_m': 0.29667274637761143, 'b1': 0.5173004590557603}
 2023-07-02 10:34:42,285 [prior] Evaluating prior at array([0.29667275, 0.51730046])
 2023-07-02 10:34:42,285 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,285 [model] Got input parameters: {'Omega_m': 0.29667274637761143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5173004590557603, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,285 [classy] Got parameters {'Omega_m': 0.29667274637761143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,285 [classy] Computing new state
 2023-07-02 10:34:42,285 [classy] Setting parameters: {'Omega_m': 0.29667274637761143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.20652241366867}
 2023-07-02 10:34:42,332 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0161572
 2023-07-02 10:34:42,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5173004590557603, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,334 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,353 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.148945
 2023-07-02 10:34:42,353 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.4823589532902795}
 2023-07-02 10:34:42,354 [prior] Evaluating prior at array([0.30438168, 0.48235895])
 2023-07-02 10:34:42,354 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,354 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4823589532902795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,354 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,354 [classy] Re-using computed results
 2023-07-02 10:34:42,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
 2023-07-02 10:34:42,354 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,354 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4823589532902795, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,354 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,374 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33071
 2023-07-02 10:34:42,374 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,374 [model] Posterior to be computed for parameters {'Omega_m': 0.3403286488422774, 'b1': 0.4414099261625883}
 2023-07-02 10:34:42,374 [prior] Evaluating prior at array([0.34032865, 0.44140993])
 2023-07-02 10:34:42,374 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,374 [model] Got input parameters: {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4414099261625883, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,374 [classy] Got parameters {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,374 [classy] Computing new state
 2023-07-02 10:34:42,375 [classy] Setting parameters: {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.03625300742303}
 2023-07-02 10:34:42,421 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,423 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0446424
 2023-07-02 10:34:42,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4414099261625883, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,423 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.732306
 2023-07-02 10:34:42,442 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,442 [mcmc] New sample, #791:
   Omega_m:0.3043817, b1:0.5038994
 2023-07-02 10:34:42,442 [model] Posterior to be computed for parameters {'Omega_m': 0.3403286488422774, 'b1': 0.43483404863056474}
 2023-07-02 10:34:42,442 [prior] Evaluating prior at array([0.34032865, 0.43483405])
 2023-07-02 10:34:42,442 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,442 [model] Got input parameters: {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43483404863056474, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,443 [classy] Got parameters {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,443 [classy] Re-using computed results
 2023-07-02 10:34:42,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.03625300742303}
 2023-07-02 10:34:42,443 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43483404863056474, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,443 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,462 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.31069
 2023-07-02 10:34:42,462 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,462 [mcmc] New sample, #792:
   Omega_m:0.3403286, b1:0.4414099
 2023-07-02 10:34:42,462 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.4252070001285323}
 2023-07-02 10:34:42,462 [prior] Evaluating prior at array([0.34586659, 0.425207  ])
 2023-07-02 10:34:42,462 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,462 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4252070001285323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,462 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,462 [classy] Computing new state
 2023-07-02 10:34:42,462 [classy] Setting parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,508 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
 2023-07-02 10:34:42,508 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,510 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0632527
 2023-07-02 10:34:42,510 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4252070001285323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,510 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.7304
 2023-07-02 10:34:42,531 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,531 [mcmc] New sample, #793:
   Omega_m:0.3403286, b1:0.434834
 2023-07-02 10:34:42,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.37153771754793086}
 2023-07-02 10:34:42,531 [prior] Evaluating prior at array([0.34586659, 0.37153772])
 2023-07-02 10:34:42,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,531 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37153771754793086, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,531 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,531 [classy] Re-using computed results
 2023-07-02 10:34:42,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
 2023-07-02 10:34:42,531 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,531 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37153771754793086, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,531 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,550 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.3922
 2023-07-02 10:34:42,550 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,551 [model] Posterior to be computed for parameters {'Omega_m': 0.36015791900005417, 'b1': 0.4003632487112563}
 2023-07-02 10:34:42,551 [prior] Evaluating prior at array([0.36015792, 0.40036325])
 2023-07-02 10:34:42,551 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,551 [model] Got input parameters: {'Omega_m': 0.36015791900005417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4003632487112563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,551 [classy] Got parameters {'Omega_m': 0.36015791900005417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,551 [classy] Computing new state
 2023-07-02 10:34:42,551 [classy] Setting parameters: {'Omega_m': 0.36015791900005417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.88331589515113}
 2023-07-02 10:34:42,598 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.12462
 2023-07-02 10:34:42,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4003632487112563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,600 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,620 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.40806
 2023-07-02 10:34:42,620 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,620 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.4136453673454006}
 2023-07-02 10:34:42,620 [prior] Evaluating prior at array([0.34586659, 0.41364537])
 2023-07-02 10:34:42,620 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,620 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4136453673454006, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,620 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,620 [classy] Re-using computed results
 2023-07-02 10:34:42,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
 2023-07-02 10:34:42,620 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4136453673454006, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,620 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,640 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.27433
 2023-07-02 10:34:42,640 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,640 [model] Posterior to be computed for parameters {'Omega_m': 0.3815199072723073, 'b1': 0.36322800279688966}
 2023-07-02 10:34:42,640 [prior] Evaluating prior at array([0.38151991, 0.363228  ])
 2023-07-02 10:34:42,640 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,640 [model] Got input parameters: {'Omega_m': 0.3815199072723073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.36322800279688966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,640 [classy] Got parameters {'Omega_m': 0.3815199072723073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,640 [classy] Computing new state
 2023-07-02 10:34:42,640 [classy] Setting parameters: {'Omega_m': 0.3815199072723073, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,686 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.6834397324104}
 2023-07-02 10:34:42,686 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,688 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.248916
 2023-07-02 10:34:42,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.36322800279688966, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,688 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,707 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.5998
 2023-07-02 10:34:42,707 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,708 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.42088960539487486}
 2023-07-02 10:34:42,708 [prior] Evaluating prior at array([0.34586659, 0.42088961])
 2023-07-02 10:34:42,708 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,708 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42088960539487486, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,708 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,708 [classy] Re-using computed results
 2023-07-02 10:34:42,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
 2023-07-02 10:34:42,708 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,708 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42088960539487486, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,708 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,728 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22678
 2023-07-02 10:34:42,728 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,728 [mcmc] New sample, #794:
   Omega_m:0.3458666, b1:0.425207
 2023-07-02 10:34:42,729 [model] Posterior to be computed for parameters {'Omega_m': 0.3137597747715905, 'b1': 0.4767034441763654}
 2023-07-02 10:34:42,729 [prior] Evaluating prior at array([0.31375977, 0.47670344])
 2023-07-02 10:34:42,729 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,729 [model] Got input parameters: {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4767034441763654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,729 [classy] Got parameters {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,729 [classy] Computing new state
 2023-07-02 10:34:42,729 [classy] Setting parameters: {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10688291892384}
 2023-07-02 10:34:42,775 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,777 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000301913
 2023-07-02 10:34:42,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4767034441763654, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,777 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,797 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15573
 2023-07-02 10:34:42,797 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,797 [mcmc] New sample, #795:
   Omega_m:0.3458666, b1:0.4208896
 2023-07-02 10:34:42,797 [model] Posterior to be computed for parameters {'Omega_m': 0.3137597747715905, 'b1': 0.42204928489382776}
 2023-07-02 10:34:42,797 [prior] Evaluating prior at array([0.31375977, 0.42204928])
 2023-07-02 10:34:42,797 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,797 [model] Got input parameters: {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42204928489382776, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,797 [classy] Got parameters {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,797 [classy] Re-using computed results
 2023-07-02 10:34:42,797 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10688291892384}
 2023-07-02 10:34:42,797 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,797 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42204928489382776, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,797 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,817 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.1853
 2023-07-02 10:34:42,817 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,817 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.4738739108237639}
 2023-07-02 10:34:42,817 [prior] Evaluating prior at array([0.31538746, 0.47387391])
 2023-07-02 10:34:42,817 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,817 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4738739108237639, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,817 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,817 [classy] Computing new state
 2023-07-02 10:34:42,817 [classy] Setting parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
 2023-07-02 10:34:42,864 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,865 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000715725
 2023-07-02 10:34:42,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4738739108237639, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,865 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.18125
 2023-07-02 10:34:42,886 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,886 [mcmc] New sample, #796:
   Omega_m:0.3137598, b1:0.4767034
 2023-07-02 10:34:42,886 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.42379505715565974}
 2023-07-02 10:34:42,886 [prior] Evaluating prior at array([0.31538746, 0.42379506])
 2023-07-02 10:34:42,886 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,886 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42379505715565974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,886 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,886 [classy] Re-using computed results
 2023-07-02 10:34:42,886 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
 2023-07-02 10:34:42,886 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42379505715565974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,886 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,905 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.4399
 2023-07-02 10:34:42,906 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,906 [model] Posterior to be computed for parameters {'Omega_m': 0.3461063187541538, 'b1': 0.4204728700386298}
 2023-07-02 10:34:42,906 [prior] Evaluating prior at array([0.34610632, 0.42047287])
 2023-07-02 10:34:42,906 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,906 [model] Got input parameters: {'Omega_m': 0.3461063187541538, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4204728700386298, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,906 [classy] Got parameters {'Omega_m': 0.3461063187541538, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,906 [classy] Computing new state
 2023-07-02 10:34:42,906 [classy] Setting parameters: {'Omega_m': 0.3461063187541538, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:42,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.39731779911975}
 2023-07-02 10:34:42,955 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:42,957 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0641255
 2023-07-02 10:34:42,957 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4204728700386298, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,957 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.29331
 2023-07-02 10:34:42,978 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,978 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.4942549780272488}
 2023-07-02 10:34:42,978 [prior] Evaluating prior at array([0.31538746, 0.49425498])
 2023-07-02 10:34:42,978 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:42,978 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4942549780272488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,978 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:42,978 [classy] Re-using computed results
 2023-07-02 10:34:42,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
 2023-07-02 10:34:42,978 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:42,979 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4942549780272488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:42,979 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:42,999 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8486
 2023-07-02 10:34:42,999 [model] Computed derived parameters: {}
 2023-07-02 10:34:42,999 [mcmc] New sample, #797:
   Omega_m:0.3153875, b1:0.4738739
 2023-07-02 10:34:42,999 [model] Posterior to be computed for parameters {'Omega_m': 0.2356799079964429, 'b1': 0.6328169636545408}
 2023-07-02 10:34:42,999 [prior] Evaluating prior at array([0.23567991, 0.63281696])
 2023-07-02 10:34:43,000 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,000 [model] Got input parameters: {'Omega_m': 0.2356799079964429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6328169636545408, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,000 [classy] Got parameters {'Omega_m': 0.2356799079964429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,000 [classy] Computing new state
 2023-07-02 10:34:43,000 [classy] Setting parameters: {'Omega_m': 0.2356799079964429, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.6618313408032}
 2023-07-02 10:34:43,048 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,051 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.445091
 2023-07-02 10:34:43,051 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6328169636545408, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,051 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,073 [fs_likelihood.fslikelihood] Computed log-likelihood = -46.7176
 2023-07-02 10:34:43,073 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,073 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.47374242746918743}
 2023-07-02 10:34:43,073 [prior] Evaluating prior at array([0.31538746, 0.47374243])
 2023-07-02 10:34:43,073 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,073 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47374242746918743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,073 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,073 [classy] Re-using computed results
 2023-07-02 10:34:43,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
 2023-07-02 10:34:43,073 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,073 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47374242746918743, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,073 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,094 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16363
 2023-07-02 10:34:43,094 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,094 [model] Posterior to be computed for parameters {'Omega_m': 0.32631991305359587, 'b1': 0.4752502224608477}
 2023-07-02 10:34:43,094 [prior] Evaluating prior at array([0.32631991, 0.47525022])
 2023-07-02 10:34:43,095 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,095 [model] Got input parameters: {'Omega_m': 0.32631991305359587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4752502224608477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,095 [classy] Got parameters {'Omega_m': 0.32631991305359587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,095 [classy] Computing new state
 2023-07-02 10:34:43,095 [classy] Setting parameters: {'Omega_m': 0.32631991305359587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,143 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62727700823066}
 2023-07-02 10:34:43,143 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,145 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0115487
 2023-07-02 10:34:43,145 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4752502224608477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,145 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,165 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20597
 2023-07-02 10:34:43,165 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,165 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.48195540245663937}
 2023-07-02 10:34:43,165 [prior] Evaluating prior at array([0.31538746, 0.4819554 ])
 2023-07-02 10:34:43,165 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,165 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48195540245663937, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,165 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,165 [classy] Re-using computed results
 2023-07-02 10:34:43,166 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
 2023-07-02 10:34:43,166 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48195540245663937, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,166 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,186 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09749
 2023-07-02 10:34:43,186 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,186 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.4874643263561518}
 2023-07-02 10:34:43,186 [prior] Evaluating prior at array([0.31929377, 0.48746433])
 2023-07-02 10:34:43,186 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,186 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4874643263561518, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,186 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,186 [classy] Computing new state
 2023-07-02 10:34:43,186 [classy] Setting parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,233 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
 2023-07-02 10:34:43,233 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,235 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00299834
 2023-07-02 10:34:43,235 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4874643263561518, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,235 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76397
 2023-07-02 10:34:43,255 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,255 [mcmc] New sample, #798:
   Omega_m:0.3153875, b1:0.494255
 2023-07-02 10:34:43,255 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.49814941208734426}
 2023-07-02 10:34:43,255 [prior] Evaluating prior at array([0.31929377, 0.49814941])
 2023-07-02 10:34:43,255 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,255 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49814941208734426, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,255 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,256 [classy] Re-using computed results
 2023-07-02 10:34:43,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
 2023-07-02 10:34:43,256 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,256 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49814941208734426, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,256 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,275 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74854
 2023-07-02 10:34:43,275 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,275 [mcmc] New sample, #799:
   Omega_m:0.3192938, b1:0.4874643
 2023-07-02 10:34:43,275 [model] Posterior to be computed for parameters {'Omega_m': 0.3453512456537857, 'b1': 0.4528516266929673}
 2023-07-02 10:34:43,275 [prior] Evaluating prior at array([0.34535125, 0.45285163])
 2023-07-02 10:34:43,275 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,275 [model] Got input parameters: {'Omega_m': 0.3453512456537857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4528516266929673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,275 [classy] Got parameters {'Omega_m': 0.3453512456537857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,275 [classy] Computing new state
 2023-07-02 10:34:43,275 [classy] Setting parameters: {'Omega_m': 0.3453512456537857, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.48025714747325}
 2023-07-02 10:34:43,322 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.061395
 2023-07-02 10:34:43,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4528516266929673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,324 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,344 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.72606
 2023-07-02 10:34:43,344 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,345 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.47447788549897574}
 2023-07-02 10:34:43,345 [prior] Evaluating prior at array([0.31929377, 0.47447789])
 2023-07-02 10:34:43,345 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,345 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47447788549897574, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,345 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,345 [classy] Re-using computed results
 2023-07-02 10:34:43,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
 2023-07-02 10:34:43,345 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47447788549897574, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,345 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9652
 2023-07-02 10:34:43,364 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,364 [model] Posterior to be computed for parameters {'Omega_m': 0.3338476446344413, 'b1': 0.4728492527242945}
 2023-07-02 10:34:43,364 [prior] Evaluating prior at array([0.33384764, 0.47284925])
 2023-07-02 10:34:43,365 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,365 [model] Got input parameters: {'Omega_m': 0.3338476446344413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4728492527242945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,365 [classy] Got parameters {'Omega_m': 0.3338476446344413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,365 [classy] Computing new state
 2023-07-02 10:34:43,365 [classy] Setting parameters: {'Omega_m': 0.3338476446344413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.76481309330012}
 2023-07-02 10:34:43,411 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0267682
 2023-07-02 10:34:43,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4728492527242945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,413 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,434 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.996145
 2023-07-02 10:34:43,434 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,434 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.46539182933233414}
 2023-07-02 10:34:43,434 [prior] Evaluating prior at array([0.31929377, 0.46539183])
 2023-07-02 10:34:43,434 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,434 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46539182933233414, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,434 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,434 [classy] Re-using computed results
 2023-07-02 10:34:43,434 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
 2023-07-02 10:34:43,434 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46539182933233414, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,434 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,454 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.890601
 2023-07-02 10:34:43,454 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,454 [model] Posterior to be computed for parameters {'Omega_m': 0.3265792281624715, 'b1': 0.4854845200811828}
 2023-07-02 10:34:43,454 [prior] Evaluating prior at array([0.32657923, 0.48548452])
 2023-07-02 10:34:43,454 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,454 [model] Got input parameters: {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4854845200811828, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,454 [classy] Got parameters {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,454 [classy] Computing new state
 2023-07-02 10:34:43,454 [classy] Setting parameters: {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59726813422216}
 2023-07-02 10:34:43,500 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,502 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0119706
 2023-07-02 10:34:43,502 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4854845200811828, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,502 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,522 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12857
 2023-07-02 10:34:43,522 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,522 [mcmc] New sample, #800:
   Omega_m:0.3192938, b1:0.4981494
 2023-07-02 10:34:43,522 [mcmc] Learn + convergence test @ 800 samples accepted.
 2023-07-02 10:34:43,522 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:43,527 [mcmc]  - Acceptance rate: 0.472
 2023-07-02 10:34:43,527 [mcmc]  - Condition number = 22.5773
 2023-07-02 10:34:43,527 [mcmc]  - Eigenvalues = array([0.00184236, 0.04159555])
 2023-07-02 10:34:43,527 [mcmc]  - Convergence of means: R-1 = 0.041596 after 640 accepted steps
 2023-07-02 10:34:43,534 [mcmc]  - normalized std's of bounds = array([[0.21469746, 0.24337169],
       [0.19071008, 0.24074066]])
 2023-07-02 10:34:43,535 [mcmc]  - Convergence of bounds: R-1 = 0.243372 after 800 accepted steps
 2023-07-02 10:34:43,535 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:43,535 [mcmc] array([[ 0.00010823, -0.00019247],
       [-0.00019247,  0.00051802]])
 2023-07-02 10:34:43,545 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:43,545 [model] Posterior to be computed for parameters {'Omega_m': 0.3265792281624715, 'b1': 0.46017549491572796}
 2023-07-02 10:34:43,545 [prior] Evaluating prior at array([0.32657923, 0.46017549])
 2023-07-02 10:34:43,546 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,546 [model] Got input parameters: {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46017549491572796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,546 [classy] Got parameters {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,546 [classy] Re-using computed results
 2023-07-02 10:34:43,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59726813422216}
 2023-07-02 10:34:43,546 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46017549491572796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,546 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,566 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24997
 2023-07-02 10:34:43,566 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,566 [mcmc] New sample, #801:
   Omega_m:0.3265792, b1:0.4854845
 2023-07-02 10:34:43,566 [model] Posterior to be computed for parameters {'Omega_m': 0.3211735150038671, 'b1': 0.4697889634134423}
 2023-07-02 10:34:43,566 [prior] Evaluating prior at array([0.32117352, 0.46978896])
 2023-07-02 10:34:43,567 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,567 [model] Got input parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4697889634134423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,567 [classy] Got parameters {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,567 [classy] Computing new state
 2023-07-02 10:34:43,567 [classy] Setting parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2272802000452}
 2023-07-02 10:34:43,614 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00473397
 2023-07-02 10:34:43,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4697889634134423, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,616 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,637 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7344
 2023-07-02 10:34:43,637 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,637 [mcmc] New sample, #802:
   Omega_m:0.3265792, b1:0.4601755
 2023-07-02 10:34:43,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3211735150038671, 'b1': 0.5178756627271432}
 2023-07-02 10:34:43,637 [prior] Evaluating prior at array([0.32117352, 0.51787566])
 2023-07-02 10:34:43,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,637 [model] Got input parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5178756627271432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,637 [classy] Got parameters {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,637 [classy] Re-using computed results
 2023-07-02 10:34:43,637 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2272802000452}
 2023-07-02 10:34:43,637 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,637 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5178756627271432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,637 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,657 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.426808
 2023-07-02 10:34:43,657 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,657 [model] Posterior to be computed for parameters {'Omega_m': 0.2987883390517092, 'b1': 0.5095985458899606}
 2023-07-02 10:34:43,657 [prior] Evaluating prior at array([0.29878834, 0.50959855])
 2023-07-02 10:34:43,658 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,658 [model] Got input parameters: {'Omega_m': 0.2987883390517092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5095985458899606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,658 [classy] Got parameters {'Omega_m': 0.2987883390517092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,658 [classy] Computing new state
 2023-07-02 10:34:43,658 [classy] Setting parameters: {'Omega_m': 0.2987883390517092, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.94087056930633}
 2023-07-02 10:34:43,705 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,707 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0121083
 2023-07-02 10:34:43,707 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5095985458899606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,707 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,726 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.24688
 2023-07-02 10:34:43,726 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,726 [model] Posterior to be computed for parameters {'Omega_m': 0.3211735150038671, 'b1': 0.403262490309104}
 2023-07-02 10:34:43,727 [prior] Evaluating prior at array([0.32117352, 0.40326249])
 2023-07-02 10:34:43,727 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,727 [model] Got input parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.403262490309104, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,727 [classy] Got parameters {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,727 [classy] Re-using computed results
 2023-07-02 10:34:43,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2272802000452}
 2023-07-02 10:34:43,727 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.403262490309104, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,727 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5922
 2023-07-02 10:34:43,747 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,748 [model] Posterior to be computed for parameters {'Omega_m': 0.3185501778092259, 'b1': 0.4744542811503672}
 2023-07-02 10:34:43,748 [prior] Evaluating prior at array([0.31855018, 0.47445428])
 2023-07-02 10:34:43,748 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,748 [model] Got input parameters: {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4744542811503672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,748 [classy] Got parameters {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,748 [classy] Computing new state
 2023-07-02 10:34:43,748 [classy] Setting parameters: {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53643702601312}
 2023-07-02 10:34:43,794 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,796 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00242513
 2023-07-02 10:34:43,796 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4744542811503672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,796 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,815 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8608
 2023-07-02 10:34:43,815 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,816 [mcmc] New sample, #803:
   Omega_m:0.3211735, b1:0.469789
 2023-07-02 10:34:43,816 [model] Posterior to be computed for parameters {'Omega_m': 0.3185501778092259, 'b1': 0.44333947827431247}
 2023-07-02 10:34:43,816 [prior] Evaluating prior at array([0.31855018, 0.44333948])
 2023-07-02 10:34:43,816 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,816 [model] Got input parameters: {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44333947827431247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,816 [classy] Got parameters {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,816 [classy] Re-using computed results
 2023-07-02 10:34:43,816 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53643702601312}
 2023-07-02 10:34:43,816 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44333947827431247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,816 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,835 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.70658
 2023-07-02 10:34:43,835 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,835 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.46599719566817394}
 2023-07-02 10:34:43,835 [prior] Evaluating prior at array([0.32330565, 0.4659972 ])
 2023-07-02 10:34:43,836 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,836 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46599719566817394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,836 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,836 [classy] Computing new state
 2023-07-02 10:34:43,836 [classy] Setting parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
 2023-07-02 10:34:43,882 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,884 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00719422
 2023-07-02 10:34:43,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46599719566817394, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,884 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,904 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57862
 2023-07-02 10:34:43,904 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,904 [mcmc] New sample, #804:
   Omega_m:0.3185502, b1:0.4744543
 2023-07-02 10:34:43,904 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.45960177027095306}
 2023-07-02 10:34:43,904 [prior] Evaluating prior at array([0.32330565, 0.45960177])
 2023-07-02 10:34:43,904 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,904 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45960177027095306, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,904 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,904 [classy] Re-using computed results
 2023-07-02 10:34:43,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
 2023-07-02 10:34:43,905 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,905 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45960177027095306, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,905 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,924 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.823947
 2023-07-02 10:34:43,924 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,924 [model] Posterior to be computed for parameters {'Omega_m': 0.2804086928800967, 'b1': 0.5422847325753728}
 2023-07-02 10:34:43,924 [prior] Evaluating prior at array([0.28040869, 0.54228473])
 2023-07-02 10:34:43,924 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,924 [model] Got input parameters: {'Omega_m': 0.2804086928800967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5422847325753728, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,924 [classy] Got parameters {'Omega_m': 0.2804086928800967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,924 [classy] Computing new state
 2023-07-02 10:34:43,924 [classy] Setting parameters: {'Omega_m': 0.2804086928800967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:43,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.30552220515216}
 2023-07-02 10:34:43,971 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:43,972 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0687083
 2023-07-02 10:34:43,973 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5422847325753728, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,973 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:43,993 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.03853
 2023-07-02 10:34:43,993 [model] Computed derived parameters: {}
 2023-07-02 10:34:43,993 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.4083034658192367}
 2023-07-02 10:34:43,993 [prior] Evaluating prior at array([0.32330565, 0.40830347])
 2023-07-02 10:34:43,993 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:43,993 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4083034658192367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,993 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:43,993 [classy] Re-using computed results
 2023-07-02 10:34:43,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
 2023-07-02 10:34:43,993 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:43,993 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4083034658192367, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:43,993 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,012 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.313
 2023-07-02 10:34:44,012 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,013 [model] Posterior to be computed for parameters {'Omega_m': 0.2787236575280344, 'b1': 0.5452813833038342}
 2023-07-02 10:34:44,013 [prior] Evaluating prior at array([0.27872366, 0.54528138])
 2023-07-02 10:34:44,013 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,013 [model] Got input parameters: {'Omega_m': 0.2787236575280344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5452813833038342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,013 [classy] Got parameters {'Omega_m': 0.2787236575280344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,013 [classy] Computing new state
 2023-07-02 10:34:44,013 [classy] Setting parameters: {'Omega_m': 0.2787236575280344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.5289474096781}
 2023-07-02 10:34:44,059 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,061 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0764357
 2023-07-02 10:34:44,061 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5452813833038342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,061 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,081 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.88205
 2023-07-02 10:34:44,081 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,081 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.4570735419698748}
 2023-07-02 10:34:44,081 [prior] Evaluating prior at array([0.32330565, 0.45707354])
 2023-07-02 10:34:44,081 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,081 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4570735419698748, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,081 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,081 [classy] Re-using computed results
 2023-07-02 10:34:44,081 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
 2023-07-02 10:34:44,081 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4570735419698748, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,082 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.46876
 2023-07-02 10:34:44,102 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,102 [mcmc] New sample, #805:
   Omega_m:0.3233056, b1:0.4659972
 2023-07-02 10:34:44,102 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.46410803972400577}
 2023-07-02 10:34:44,102 [prior] Evaluating prior at array([0.31935011, 0.46410804])
 2023-07-02 10:34:44,102 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,102 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46410803972400577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,102 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,102 [classy] Computing new state
 2023-07-02 10:34:44,102 [classy] Setting parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,151 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
 2023-07-02 10:34:44,151 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,153 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00304435
 2023-07-02 10:34:44,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46410803972400577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,153 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,172 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.71775
 2023-07-02 10:34:44,173 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,173 [mcmc] New sample, #806:
   Omega_m:0.3233056, b1:0.4570735
 2023-07-02 10:34:44,173 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.400960577124302}
 2023-07-02 10:34:44,173 [prior] Evaluating prior at array([0.31935011, 0.40096058])
 2023-07-02 10:34:44,173 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,173 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.400960577124302, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,173 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,173 [classy] Re-using computed results
 2023-07-02 10:34:44,173 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
 2023-07-02 10:34:44,173 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.400960577124302, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,173 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,193 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.8106
 2023-07-02 10:34:44,193 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,194 [model] Posterior to be computed for parameters {'Omega_m': 0.30051770302265146, 'b1': 0.49759940787202595}
 2023-07-02 10:34:44,194 [prior] Evaluating prior at array([0.3005177 , 0.49759941])
 2023-07-02 10:34:44,194 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,194 [model] Got input parameters: {'Omega_m': 0.30051770302265146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49759940787202595, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,194 [classy] Got parameters {'Omega_m': 0.30051770302265146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,194 [classy] Computing new state
 2023-07-02 10:34:44,194 [classy] Setting parameters: {'Omega_m': 0.30051770302265146, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,240 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72492975341956}
 2023-07-02 10:34:44,240 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,242 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00925096
 2023-07-02 10:34:44,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49759940787202595, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,242 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,262 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.538344
 2023-07-02 10:34:44,262 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,262 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.4670020740648544}
 2023-07-02 10:34:44,262 [prior] Evaluating prior at array([0.31935011, 0.46700207])
 2023-07-02 10:34:44,262 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,262 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4670020740648544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,262 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,262 [classy] Re-using computed results
 2023-07-02 10:34:44,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
 2023-07-02 10:34:44,262 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,262 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4670020740648544, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,262 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,281 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.12229
 2023-07-02 10:34:44,282 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,282 [mcmc] New sample, #807:
   Omega_m:0.3193501, b1:0.464108
 2023-07-02 10:34:44,282 [model] Posterior to be computed for parameters {'Omega_m': 0.3384871190541839, 'b1': 0.4329689964670364}
 2023-07-02 10:34:44,282 [prior] Evaluating prior at array([0.33848712, 0.432969  ])
 2023-07-02 10:34:44,282 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,282 [model] Got input parameters: {'Omega_m': 0.3384871190541839, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4329689964670364, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,282 [classy] Got parameters {'Omega_m': 0.3384871190541839, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,282 [classy] Computing new state
 2023-07-02 10:34:44,282 [classy] Setting parameters: {'Omega_m': 0.3384871190541839, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.24198431157012}
 2023-07-02 10:34:44,328 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0391273
 2023-07-02 10:34:44,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4329689964670364, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,330 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,351 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.49366
 2023-07-02 10:34:44,351 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,351 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.4822868164429757}
 2023-07-02 10:34:44,351 [prior] Evaluating prior at array([0.31935011, 0.48228682])
 2023-07-02 10:34:44,351 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,351 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4822868164429757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,351 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,351 [classy] Re-using computed results
 2023-07-02 10:34:44,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
 2023-07-02 10:34:44,352 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,352 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4822868164429757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,352 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55431
 2023-07-02 10:34:44,371 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,371 [mcmc] New sample, #808:
   Omega_m:0.3193501, b1:0.4670021
 2023-07-02 10:34:44,371 [model] Posterior to be computed for parameters {'Omega_m': 0.31751122942987536, 'b1': 0.48555706001636156}
 2023-07-02 10:34:44,371 [prior] Evaluating prior at array([0.31751123, 0.48555706])
 2023-07-02 10:34:44,371 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,371 [model] Got input parameters: {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48555706001636156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,371 [classy] Got parameters {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,371 [classy] Computing new state
 2023-07-02 10:34:44,371 [classy] Setting parameters: {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65950154047135}
 2023-07-02 10:34:44,418 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173292
 2023-07-02 10:34:44,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48555706001636156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,419 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,439 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61673
 2023-07-02 10:34:44,439 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,439 [mcmc] New sample, #809:
   Omega_m:0.3193501, b1:0.4822868
 2023-07-02 10:34:44,439 [model] Posterior to be computed for parameters {'Omega_m': 0.31751122942987536, 'b1': 0.49361526932882077}
 2023-07-02 10:34:44,439 [prior] Evaluating prior at array([0.31751123, 0.49361527])
 2023-07-02 10:34:44,439 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,439 [model] Got input parameters: {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49361526932882077, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,439 [classy] Got parameters {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,439 [classy] Re-using computed results
 2023-07-02 10:34:44,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65950154047135}
 2023-07-02 10:34:44,439 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49361526932882077, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,439 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,460 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88403
 2023-07-02 10:34:44,460 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,460 [mcmc] New sample, #810:
   Omega_m:0.3175112, b1:0.4855571
 2023-07-02 10:34:44,460 [model] Posterior to be computed for parameters {'Omega_m': 0.321725000739603, 'b1': 0.4861215387970482}
 2023-07-02 10:34:44,460 [prior] Evaluating prior at array([0.321725  , 0.48612154])
 2023-07-02 10:34:44,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,460 [model] Got input parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4861215387970482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,460 [classy] Got parameters {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,460 [classy] Computing new state
 2023-07-02 10:34:44,460 [classy] Setting parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.16257601232937}
 2023-07-02 10:34:44,507 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,508 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0053205
 2023-07-02 10:34:44,508 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4861215387970482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,509 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,528 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68221
 2023-07-02 10:34:44,528 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,528 [mcmc] New sample, #811:
   Omega_m:0.3175112, b1:0.4936153
 2023-07-02 10:34:44,528 [model] Posterior to be computed for parameters {'Omega_m': 0.321725000739603, 'b1': 0.5452725187805577}
 2023-07-02 10:34:44,528 [prior] Evaluating prior at array([0.321725  , 0.54527252])
 2023-07-02 10:34:44,528 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,528 [model] Got input parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5452725187805577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,528 [classy] Got parameters {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,528 [classy] Re-using computed results
 2023-07-02 10:34:44,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.16257601232937}
 2023-07-02 10:34:44,528 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5452725187805577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,528 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,549 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.68054
 2023-07-02 10:34:44,549 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,549 [model] Posterior to be computed for parameters {'Omega_m': 0.3339480319069712, 'b1': 0.46438421725843904}
 2023-07-02 10:34:44,549 [prior] Evaluating prior at array([0.33394803, 0.46438422])
 2023-07-02 10:34:44,549 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,549 [model] Got input parameters: {'Omega_m': 0.3339480319069712, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46438421725843904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,549 [classy] Got parameters {'Omega_m': 0.3339480319069712, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,549 [classy] Computing new state
 2023-07-02 10:34:44,549 [classy] Setting parameters: {'Omega_m': 0.3339480319069712, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.75342971210551}
 2023-07-02 10:34:44,595 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0270121
 2023-07-02 10:34:44,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46438421725843904, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,597 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,617 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09249
 2023-07-02 10:34:44,617 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,617 [model] Posterior to be computed for parameters {'Omega_m': 0.321725000739603, 'b1': 0.495136032557442}
 2023-07-02 10:34:44,617 [prior] Evaluating prior at array([0.321725  , 0.49513603])
 2023-07-02 10:34:44,617 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,618 [model] Got input parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.495136032557442, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,618 [classy] Got parameters {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,618 [classy] Re-using computed results
 2023-07-02 10:34:44,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.16257601232937}
 2023-07-02 10:34:44,618 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,618 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.495136032557442, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,618 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,639 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55972
 2023-07-02 10:34:44,639 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,639 [mcmc] New sample, #812:
   Omega_m:0.321725, b1:0.4861215
 2023-07-02 10:34:44,639 [model] Posterior to be computed for parameters {'Omega_m': 0.31738083303731285, 'b1': 0.5028616587846272}
 2023-07-02 10:34:44,639 [prior] Evaluating prior at array([0.31738083, 0.50286166])
 2023-07-02 10:34:44,639 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,639 [model] Got input parameters: {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5028616587846272, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,639 [classy] Got parameters {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,639 [classy] Computing new state
 2023-07-02 10:34:44,639 [classy] Setting parameters: {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6749739503329}
 2023-07-02 10:34:44,689 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,691 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00165501
 2023-07-02 10:34:44,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5028616587846272, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,691 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,711 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77292
 2023-07-02 10:34:44,711 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,711 [mcmc] New sample, #813:
   Omega_m:0.321725, b1:0.495136
 2023-07-02 10:34:44,712 [model] Posterior to be computed for parameters {'Omega_m': 0.31738083303731285, 'b1': 0.4518097602518478}
 2023-07-02 10:34:44,712 [prior] Evaluating prior at array([0.31738083, 0.45180976])
 2023-07-02 10:34:44,712 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,712 [model] Got input parameters: {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4518097602518478, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,712 [classy] Got parameters {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,712 [classy] Re-using computed results
 2023-07-02 10:34:44,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6749739503329}
 2023-07-02 10:34:44,712 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,712 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4518097602518478, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,712 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,732 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.15174
 2023-07-02 10:34:44,732 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,732 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.511496253653432}
 2023-07-02 10:34:44,732 [prior] Evaluating prior at array([0.31252555, 0.51149625])
 2023-07-02 10:34:44,732 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,732 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.511496253653432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,732 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,733 [classy] Computing new state
 2023-07-02 10:34:44,733 [classy] Setting parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
 2023-07-02 10:34:44,782 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202477
 2023-07-02 10:34:44,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.511496253653432, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,784 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,804 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76639
 2023-07-02 10:34:44,804 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,804 [mcmc] New sample, #814:
   Omega_m:0.3173808, b1:0.5028617
 2023-07-02 10:34:44,804 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.5460347698825926}
 2023-07-02 10:34:44,804 [prior] Evaluating prior at array([0.31252555, 0.54603477])
 2023-07-02 10:34:44,805 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,805 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5460347698825926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,805 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,805 [classy] Re-using computed results
 2023-07-02 10:34:44,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
 2023-07-02 10:34:44,805 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,805 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5460347698825926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,805 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,824 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86886
 2023-07-02 10:34:44,824 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,825 [model] Posterior to be computed for parameters {'Omega_m': 0.35190808623443864, 'b1': 0.4414587224496056}
 2023-07-02 10:34:44,825 [prior] Evaluating prior at array([0.35190809, 0.44145872])
 2023-07-02 10:34:44,825 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,825 [model] Got input parameters: {'Omega_m': 0.35190808623443864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4414587224496056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,825 [classy] Got parameters {'Omega_m': 0.35190808623443864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,825 [classy] Computing new state
 2023-07-02 10:34:44,825 [classy] Setting parameters: {'Omega_m': 0.35190808623443864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.76549322293175}
 2023-07-02 10:34:44,872 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,874 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0869104
 2023-07-02 10:34:44,874 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4414587224496056, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,874 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,893 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.72824
 2023-07-02 10:34:44,893 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,893 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.5678910905830066}
 2023-07-02 10:34:44,893 [prior] Evaluating prior at array([0.31252555, 0.56789109])
 2023-07-02 10:34:44,893 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,894 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5678910905830066, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,894 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,894 [classy] Re-using computed results
 2023-07-02 10:34:44,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
 2023-07-02 10:34:44,894 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,894 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5678910905830066, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,894 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,914 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.49612
 2023-07-02 10:34:44,914 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,914 [model] Posterior to be computed for parameters {'Omega_m': 0.2527700807802294, 'b1': 0.6177648016656777}
 2023-07-02 10:34:44,914 [prior] Evaluating prior at array([0.25277008, 0.6177648 ])
 2023-07-02 10:34:44,914 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,914 [model] Got input parameters: {'Omega_m': 0.2527700807802294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6177648016656777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,914 [classy] Got parameters {'Omega_m': 0.2527700807802294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,914 [classy] Computing new state
 2023-07-02 10:34:44,914 [classy] Setting parameters: {'Omega_m': 0.2527700807802294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:44,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.12351889071076}
 2023-07-02 10:34:44,961 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:44,963 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.256257
 2023-07-02 10:34:44,963 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6177648016656777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,963 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:44,982 [fs_likelihood.fslikelihood] Computed log-likelihood = -25.5657
 2023-07-02 10:34:44,982 [model] Computed derived parameters: {}
 2023-07-02 10:34:44,983 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.4693947894357663}
 2023-07-02 10:34:44,983 [prior] Evaluating prior at array([0.31252555, 0.46939479])
 2023-07-02 10:34:44,983 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:44,983 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4693947894357663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,983 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:44,983 [classy] Re-using computed results
 2023-07-02 10:34:44,983 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
 2023-07-02 10:34:44,983 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:44,983 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4693947894357663, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:44,983 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,002 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.37446
 2023-07-02 10:34:45,002 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,002 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.4973365395589126}
 2023-07-02 10:34:45,002 [prior] Evaluating prior at array([0.32048764, 0.49733654])
 2023-07-02 10:34:45,003 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,003 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4973365395589126, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,003 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,003 [classy] Computing new state
 2023-07-02 10:34:45,003 [classy] Setting parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,049 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
 2023-07-02 10:34:45,049 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,051 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00405327
 2023-07-02 10:34:45,051 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4973365395589126, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,051 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,071 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6408
 2023-07-02 10:34:45,071 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,071 [mcmc] New sample, #815:
   Omega_m:0.3125255, b1:0.5114963
 2023-07-02 10:34:45,071 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.47377498629139825}
 2023-07-02 10:34:45,071 [prior] Evaluating prior at array([0.32048764, 0.47377499])
 2023-07-02 10:34:45,072 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,072 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47377498629139825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,072 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,072 [classy] Re-using computed results
 2023-07-02 10:34:45,072 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
 2023-07-02 10:34:45,072 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,072 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47377498629139825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,072 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,092 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03701
 2023-07-02 10:34:45,092 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,092 [mcmc] New sample, #816:
   Omega_m:0.3204876, b1:0.4973365
 2023-07-02 10:34:45,092 [model] Posterior to be computed for parameters {'Omega_m': 0.33952668949190945, 'b1': 0.4399161265425179}
 2023-07-02 10:34:45,093 [prior] Evaluating prior at array([0.33952669, 0.43991613])
 2023-07-02 10:34:45,093 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,093 [model] Got input parameters: {'Omega_m': 0.33952668949190945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4399161265425179, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,093 [classy] Got parameters {'Omega_m': 0.33952668949190945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,093 [classy] Computing new state
 2023-07-02 10:34:45,093 [classy] Setting parameters: {'Omega_m': 0.33952668949190945, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.12572477990747}
 2023-07-02 10:34:45,141 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,143 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0421985
 2023-07-02 10:34:45,144 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4399161265425179, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,144 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,164 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.772138
 2023-07-02 10:34:45,164 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,164 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.4136859348999085}
 2023-07-02 10:34:45,164 [prior] Evaluating prior at array([0.32048764, 0.41368593])
 2023-07-02 10:34:45,164 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,164 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4136859348999085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,164 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,164 [classy] Re-using computed results
 2023-07-02 10:34:45,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
 2023-07-02 10:34:45,164 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,164 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4136859348999085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,164 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,184 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.9729
 2023-07-02 10:34:45,184 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,184 [model] Posterior to be computed for parameters {'Omega_m': 0.3305533320724319, 'b1': 0.45587425941783843}
 2023-07-02 10:34:45,184 [prior] Evaluating prior at array([0.33055333, 0.45587426])
 2023-07-02 10:34:45,184 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,184 [model] Got input parameters: {'Omega_m': 0.3305533320724319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45587425941783843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,184 [classy] Got parameters {'Omega_m': 0.3305533320724319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,184 [classy] Computing new state
 2023-07-02 10:34:45,184 [classy] Setting parameters: {'Omega_m': 0.3305533320724319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1400474048332}
 2023-07-02 10:34:45,231 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,233 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0193583
 2023-07-02 10:34:45,233 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45587425941783843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,233 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,252 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.971141
 2023-07-02 10:34:45,252 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,253 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.4989240005776111}
 2023-07-02 10:34:45,253 [prior] Evaluating prior at array([0.32048764, 0.498924  ])
 2023-07-02 10:34:45,253 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,253 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4989240005776111, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,253 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,253 [classy] Re-using computed results
 2023-07-02 10:34:45,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
 2023-07-02 10:34:45,253 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4989240005776111, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,253 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,273 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57341
 2023-07-02 10:34:45,273 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,273 [mcmc] New sample, #817:
   Omega_m:0.3204876, b1:0.473775
 2023-07-02 10:34:45,273 [model] Posterior to be computed for parameters {'Omega_m': 0.3110468065852951, 'b1': 0.5157134917693519}
 2023-07-02 10:34:45,274 [prior] Evaluating prior at array([0.31104681, 0.51571349])
 2023-07-02 10:34:45,274 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,274 [model] Got input parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5157134917693519, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,274 [classy] Got parameters {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,274 [classy] Computing new state
 2023-07-02 10:34:45,274 [classy] Setting parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,321 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43341770905127}
 2023-07-02 10:34:45,321 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,323 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000329491
 2023-07-02 10:34:45,323 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5157134917693519, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,323 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,343 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64694
 2023-07-02 10:34:45,344 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,344 [mcmc] New sample, #818:
   Omega_m:0.3204876, b1:0.498924
 2023-07-02 10:34:45,344 [model] Posterior to be computed for parameters {'Omega_m': 0.3110468065852951, 'b1': 0.503626689582094}
 2023-07-02 10:34:45,344 [prior] Evaluating prior at array([0.31104681, 0.50362669])
 2023-07-02 10:34:45,344 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,344 [model] Got input parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.503626689582094, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,344 [classy] Got parameters {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,344 [classy] Re-using computed results
 2023-07-02 10:34:45,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43341770905127}
 2023-07-02 10:34:45,344 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.503626689582094, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,344 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78775
 2023-07-02 10:34:45,366 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,366 [mcmc] New sample, #819:
   Omega_m:0.3110468, b1:0.5157135
 2023-07-02 10:34:45,366 [model] Posterior to be computed for parameters {'Omega_m': 0.28929336299207714, 'b1': 0.5423128052830974}
 2023-07-02 10:34:45,366 [prior] Evaluating prior at array([0.28929336, 0.54231281])
 2023-07-02 10:34:45,366 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,366 [model] Got input parameters: {'Omega_m': 0.28929336299207714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5423128052830974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,366 [classy] Got parameters {'Omega_m': 0.28929336299207714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,367 [classy] Computing new state
 2023-07-02 10:34:45,367 [classy] Setting parameters: {'Omega_m': 0.28929336299207714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.1462047965422}
 2023-07-02 10:34:45,413 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,415 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.035186
 2023-07-02 10:34:45,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5423128052830974, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,415 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,436 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33468
 2023-07-02 10:34:45,436 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,436 [model] Posterior to be computed for parameters {'Omega_m': 0.3110468065852951, 'b1': 0.5388189108731091}
 2023-07-02 10:34:45,436 [prior] Evaluating prior at array([0.31104681, 0.53881891])
 2023-07-02 10:34:45,436 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,436 [model] Got input parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5388189108731091, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,436 [classy] Got parameters {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,436 [classy] Re-using computed results
 2023-07-02 10:34:45,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43341770905127}
 2023-07-02 10:34:45,436 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,436 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5388189108731091, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,436 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,456 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.115236
 2023-07-02 10:34:45,456 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,456 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.4868798121245692}
 2023-07-02 10:34:45,456 [prior] Evaluating prior at array([0.32046368, 0.48687981])
 2023-07-02 10:34:45,456 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,456 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4868798121245692, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,456 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,456 [classy] Computing new state
 2023-07-02 10:34:45,456 [classy] Setting parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,503 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,505 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00403051
 2023-07-02 10:34:45,505 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4868798121245692, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,505 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,525 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73984
 2023-07-02 10:34:45,525 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,525 [mcmc] New sample, #820:
   Omega_m:0.3110468, b1:0.5036267
 2023-07-02 10:34:45,525 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.5135692831210197}
 2023-07-02 10:34:45,525 [prior] Evaluating prior at array([0.32046368, 0.51356928])
 2023-07-02 10:34:45,526 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,526 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135692831210197, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,526 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,526 [classy] Re-using computed results
 2023-07-02 10:34:45,526 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,526 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,526 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135692831210197, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,526 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,546 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2892
 2023-07-02 10:34:45,546 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,547 [model] Posterior to be computed for parameters {'Omega_m': 0.3390098003316239, 'b1': 0.45389756937263087}
 2023-07-02 10:34:45,547 [prior] Evaluating prior at array([0.3390098 , 0.45389757])
 2023-07-02 10:34:45,547 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,547 [model] Got input parameters: {'Omega_m': 0.3390098003316239, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45389756937263087, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,547 [classy] Got parameters {'Omega_m': 0.3390098003316239, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,547 [classy] Computing new state
 2023-07-02 10:34:45,547 [classy] Setting parameters: {'Omega_m': 0.3390098003316239, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,594 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.18349014347302}
 2023-07-02 10:34:45,594 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,596 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0406578
 2023-07-02 10:34:45,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45389756937263087, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,596 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0190102
 2023-07-02 10:34:45,616 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,616 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.48218086538620747}
 2023-07-02 10:34:45,616 [prior] Evaluating prior at array([0.32046368, 0.48218087])
 2023-07-02 10:34:45,616 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,616 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48218086538620747, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,616 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,616 [classy] Re-using computed results
 2023-07-02 10:34:45,616 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,616 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48218086538620747, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,616 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,636 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59095
 2023-07-02 10:34:45,636 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,636 [mcmc] New sample, #821:
   Omega_m:0.3204637, b1:0.4868798
 2023-07-02 10:34:45,636 [model] Posterior to be computed for parameters {'Omega_m': 0.3065134691333626, 'b1': 0.5069897867415467}
 2023-07-02 10:34:45,636 [prior] Evaluating prior at array([0.30651347, 0.50698979])
 2023-07-02 10:34:45,636 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,636 [model] Got input parameters: {'Omega_m': 0.3065134691333626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5069897867415467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,636 [classy] Got parameters {'Omega_m': 0.3065134691333626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,636 [classy] Computing new state
 2023-07-02 10:34:45,636 [classy] Setting parameters: {'Omega_m': 0.3065134691333626, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.9847007998794}
 2023-07-02 10:34:45,683 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,685 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00242133
 2023-07-02 10:34:45,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5069897867415467, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,685 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,705 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28372
 2023-07-02 10:34:45,705 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.5239422943059711}
 2023-07-02 10:34:45,705 [prior] Evaluating prior at array([0.32046368, 0.52394229])
 2023-07-02 10:34:45,705 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,705 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239422943059711, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,705 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,705 [classy] Re-using computed results
 2023-07-02 10:34:45,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,705 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239422943059711, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,705 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,725 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.37289
 2023-07-02 10:34:45,725 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,725 [model] Posterior to be computed for parameters {'Omega_m': 0.32880092626619056, 'b1': 0.46735398647723597}
 2023-07-02 10:34:45,725 [prior] Evaluating prior at array([0.32880093, 0.46735399])
 2023-07-02 10:34:45,725 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,725 [model] Got input parameters: {'Omega_m': 0.32880092626619056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46735398647723597, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,726 [classy] Got parameters {'Omega_m': 0.32880092626619056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,726 [classy] Computing new state
 2023-07-02 10:34:45,726 [classy] Setting parameters: {'Omega_m': 0.32880092626619056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.34103974095072}
 2023-07-02 10:34:45,774 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,776 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0158891
 2023-07-02 10:34:45,776 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46735398647723597, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,776 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,795 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.77175
 2023-07-02 10:34:45,795 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,795 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.462676559115909}
 2023-07-02 10:34:45,795 [prior] Evaluating prior at array([0.32046368, 0.46267656])
 2023-07-02 10:34:45,795 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,795 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.462676559115909, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,795 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,795 [classy] Re-using computed results
 2023-07-02 10:34:45,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,795 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,795 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.462676559115909, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,795 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,815 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.744115
 2023-07-02 10:34:45,815 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,815 [model] Posterior to be computed for parameters {'Omega_m': 0.28794603904077964, 'b1': 0.5400099265531533}
 2023-07-02 10:34:45,815 [prior] Evaluating prior at array([0.28794604, 0.54000993])
 2023-07-02 10:34:45,815 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,815 [model] Got input parameters: {'Omega_m': 0.28794603904077964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5400099265531533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,815 [classy] Got parameters {'Omega_m': 0.28794603904077964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,815 [classy] Computing new state
 2023-07-02 10:34:45,815 [classy] Setting parameters: {'Omega_m': 0.28794603904077964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.32000792177155}
 2023-07-02 10:34:45,862 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0395066
 2023-07-02 10:34:45,864 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5400099265531533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,864 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,884 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.9829
 2023-07-02 10:34:45,884 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,884 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.459186532814003}
 2023-07-02 10:34:45,884 [prior] Evaluating prior at array([0.32046368, 0.45918653])
 2023-07-02 10:34:45,884 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,884 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.459186532814003, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,884 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,884 [classy] Re-using computed results
 2023-07-02 10:34:45,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,884 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.459186532814003, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,884 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,903 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.210661
 2023-07-02 10:34:45,904 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,904 [mcmc] New sample, #822:
   Omega_m:0.3204637, b1:0.4821809
 2023-07-02 10:34:45,904 [model] Posterior to be computed for parameters {'Omega_m': 0.254984134023796, 'b1': 0.5756347301075192}
 2023-07-02 10:34:45,904 [prior] Evaluating prior at array([0.25498413, 0.57563473])
 2023-07-02 10:34:45,904 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,904 [model] Got input parameters: {'Omega_m': 0.254984134023796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5756347301075192, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,904 [classy] Got parameters {'Omega_m': 0.254984134023796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,904 [classy] Computing new state
 2023-07-02 10:34:45,904 [classy] Setting parameters: {'Omega_m': 0.254984134023796, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:45,951 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.80508460443411}
 2023-07-02 10:34:45,951 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:45,953 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.236149
 2023-07-02 10:34:45,953 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5756347301075192, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,953 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,974 [fs_likelihood.fslikelihood] Computed log-likelihood = -25.8701
 2023-07-02 10:34:45,974 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,974 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.49537861958575924}
 2023-07-02 10:34:45,974 [prior] Evaluating prior at array([0.32046368, 0.49537862])
 2023-07-02 10:34:45,974 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,974 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49537861958575924, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,974 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,974 [classy] Re-using computed results
 2023-07-02 10:34:45,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:45,974 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:45,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49537861958575924, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,974 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:45,994 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70727
 2023-07-02 10:34:45,994 [model] Computed derived parameters: {}
 2023-07-02 10:34:45,994 [mcmc] New sample, #823:
   Omega_m:0.3204637, b1:0.4591865
 2023-07-02 10:34:45,994 [model] Posterior to be computed for parameters {'Omega_m': 0.2635018359035426, 'b1': 0.5966790174509006}
 2023-07-02 10:34:45,994 [prior] Evaluating prior at array([0.26350184, 0.59667902])
 2023-07-02 10:34:45,994 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:45,994 [model] Got input parameters: {'Omega_m': 0.2635018359035426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5966790174509006, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:45,994 [classy] Got parameters {'Omega_m': 0.2635018359035426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:45,994 [classy] Computing new state
 2023-07-02 10:34:45,994 [classy] Setting parameters: {'Omega_m': 0.2635018359035426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.60113934414392}
 2023-07-02 10:34:46,040 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,042 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.167423
 2023-07-02 10:34:46,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5966790174509006, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,042 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,062 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.7442
 2023-07-02 10:34:46,062 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,063 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.46984769903106843}
 2023-07-02 10:34:46,063 [prior] Evaluating prior at array([0.32046368, 0.4698477 ])
 2023-07-02 10:34:46,063 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,063 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46984769903106843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,063 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,063 [classy] Re-using computed results
 2023-07-02 10:34:46,063 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:46,063 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46984769903106843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,063 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64934
 2023-07-02 10:34:46,083 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,083 [mcmc] New sample, #824:
   Omega_m:0.3204637, b1:0.4953786
 2023-07-02 10:34:46,083 [model] Posterior to be computed for parameters {'Omega_m': 0.3400290160286764, 'b1': 0.43505289284697796}
 2023-07-02 10:34:46,083 [prior] Evaluating prior at array([0.34002902, 0.43505289])
 2023-07-02 10:34:46,084 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,084 [model] Got input parameters: {'Omega_m': 0.3400290160286764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43505289284697796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,084 [classy] Got parameters {'Omega_m': 0.3400290160286764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,084 [classy] Computing new state
 2023-07-02 10:34:46,084 [classy] Setting parameters: {'Omega_m': 0.3400290160286764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.06965962747645}
 2023-07-02 10:34:46,131 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0437217
 2023-07-02 10:34:46,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43505289284697796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,133 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,153 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.27279
 2023-07-02 10:34:46,153 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.48421442736241566}
 2023-07-02 10:34:46,154 [prior] Evaluating prior at array([0.32046368, 0.48421443])
 2023-07-02 10:34:46,154 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,154 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48421442736241566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,154 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,154 [classy] Re-using computed results
 2023-07-02 10:34:46,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
 2023-07-02 10:34:46,154 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,154 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48421442736241566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,154 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,173 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66981
 2023-07-02 10:34:46,173 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,173 [mcmc] New sample, #825:
   Omega_m:0.3204637, b1:0.4698477
 2023-07-02 10:34:46,173 [model] Posterior to be computed for parameters {'Omega_m': 0.3241984784152171, 'b1': 0.4775724976228761}
 2023-07-02 10:34:46,173 [prior] Evaluating prior at array([0.32419848, 0.4775725 ])
 2023-07-02 10:34:46,174 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,174 [model] Got input parameters: {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4775724976228761, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,174 [classy] Got parameters {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,174 [classy] Computing new state
 2023-07-02 10:34:46,174 [classy] Setting parameters: {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.87357597307204}
 2023-07-02 10:34:46,220 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00837782
 2023-07-02 10:34:46,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4775724976228761, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,222 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38755
 2023-07-02 10:34:46,242 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,242 [mcmc] New sample, #826:
   Omega_m:0.3204637, b1:0.4842144
 2023-07-02 10:34:46,242 [model] Posterior to be computed for parameters {'Omega_m': 0.3241984784152171, 'b1': 0.45570863516076787}
 2023-07-02 10:34:46,242 [prior] Evaluating prior at array([0.32419848, 0.45570864])
 2023-07-02 10:34:46,242 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,242 [model] Got input parameters: {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45570863516076787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,242 [classy] Got parameters {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,242 [classy] Re-using computed results
 2023-07-02 10:34:46,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.87357597307204}
 2023-07-02 10:34:46,242 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45570863516076787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,242 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.422848
 2023-07-02 10:34:46,261 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,262 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.48314148223642067}
 2023-07-02 10:34:46,262 [prior] Evaluating prior at array([0.321067  , 0.48314148])
 2023-07-02 10:34:46,262 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,262 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48314148223642067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,262 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,262 [classy] Computing new state
 2023-07-02 10:34:46,262 [classy] Setting parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,308 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
 2023-07-02 10:34:46,308 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,310 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00462471
 2023-07-02 10:34:46,310 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48314148223642067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,310 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,330 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63397
 2023-07-02 10:34:46,330 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,330 [mcmc] New sample, #827:
   Omega_m:0.3241985, b1:0.4775725
 2023-07-02 10:34:46,330 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.4489491550452118}
 2023-07-02 10:34:46,330 [prior] Evaluating prior at array([0.321067  , 0.44894916])
 2023-07-02 10:34:46,330 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,330 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4489491550452118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,330 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,330 [classy] Re-using computed results
 2023-07-02 10:34:46,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
 2023-07-02 10:34:46,330 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4489491550452118, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,330 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,350 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.50803
 2023-07-02 10:34:46,350 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,350 [model] Posterior to be computed for parameters {'Omega_m': 0.2996137326025542, 'b1': 0.5212937740687329}
 2023-07-02 10:34:46,350 [prior] Evaluating prior at array([0.29961373, 0.52129377])
 2023-07-02 10:34:46,350 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,350 [model] Got input parameters: {'Omega_m': 0.2996137326025542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5212937740687329, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,350 [classy] Got parameters {'Omega_m': 0.2996137326025542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,350 [classy] Computing new state
 2023-07-02 10:34:46,350 [classy] Setting parameters: {'Omega_m': 0.2996137326025542, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,397 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.83766879806254}
 2023-07-02 10:34:46,397 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,399 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0106941
 2023-07-02 10:34:46,399 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5212937740687329, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,399 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,418 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34105
 2023-07-02 10:34:46,418 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,418 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.46341011972255525}
 2023-07-02 10:34:46,418 [prior] Evaluating prior at array([0.321067  , 0.46341012])
 2023-07-02 10:34:46,418 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,418 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46341011972255525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,418 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,418 [classy] Re-using computed results
 2023-07-02 10:34:46,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
 2023-07-02 10:34:46,418 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46341011972255525, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,418 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,438 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.961935
 2023-07-02 10:34:46,438 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,438 [model] Posterior to be computed for parameters {'Omega_m': 0.33315208663031154, 'b1': 0.4616494865434446}
 2023-07-02 10:34:46,438 [prior] Evaluating prior at array([0.33315209, 0.46164949])
 2023-07-02 10:34:46,439 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,439 [model] Got input parameters: {'Omega_m': 0.33315208663031154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4616494865434446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,439 [classy] Got parameters {'Omega_m': 0.33315208663031154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,439 [classy] Computing new state
 2023-07-02 10:34:46,439 [classy] Setting parameters: {'Omega_m': 0.33315208663031154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,486 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8437618458461}
 2023-07-02 10:34:46,486 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,488 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.025108
 2023-07-02 10:34:46,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4616494865434446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,488 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,507 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15421
 2023-07-02 10:34:46,507 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,507 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.49440852914269184}
 2023-07-02 10:34:46,507 [prior] Evaluating prior at array([0.321067  , 0.49440853])
 2023-07-02 10:34:46,507 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,507 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49440852914269184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,507 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,507 [classy] Re-using computed results
 2023-07-02 10:34:46,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
 2023-07-02 10:34:46,507 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,507 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49440852914269184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,507 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,526 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66734
 2023-07-02 10:34:46,527 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,527 [mcmc] New sample, #828:
   Omega_m:0.321067, b1:0.4831415
 2023-07-02 10:34:46,527 [model] Posterior to be computed for parameters {'Omega_m': 0.32331155137075734, 'b1': 0.4904168470887759}
 2023-07-02 10:34:46,527 [prior] Evaluating prior at array([0.32331155, 0.49041685])
 2023-07-02 10:34:46,527 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,527 [model] Got input parameters: {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904168470887759, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,527 [classy] Got parameters {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,527 [classy] Computing new state
 2023-07-02 10:34:46,527 [classy] Setting parameters: {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97697715697063}
 2023-07-02 10:34:46,574 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00720174
 2023-07-02 10:34:46,575 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904168470887759, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,575 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,595 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49612
 2023-07-02 10:34:46,595 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,595 [mcmc] New sample, #829:
   Omega_m:0.321067, b1:0.4944085
 2023-07-02 10:34:46,595 [model] Posterior to be computed for parameters {'Omega_m': 0.32331155137075734, 'b1': 0.4764687712503482}
 2023-07-02 10:34:46,595 [prior] Evaluating prior at array([0.32331155, 0.47646877])
 2023-07-02 10:34:46,595 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,595 [model] Got input parameters: {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4764687712503482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,596 [classy] Got parameters {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,596 [classy] Re-using computed results
 2023-07-02 10:34:46,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97697715697063}
 2023-07-02 10:34:46,596 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4764687712503482, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,596 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,615 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36009
 2023-07-02 10:34:46,615 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,615 [mcmc] New sample, #830:
   Omega_m:0.3233116, b1:0.4904168
 2023-07-02 10:34:46,615 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.475185897403032}
 2023-07-02 10:34:46,615 [prior] Evaluating prior at array([0.32403292, 0.4751859 ])
 2023-07-02 10:34:46,615 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,615 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.475185897403032, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,615 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,615 [classy] Computing new state
 2023-07-02 10:34:46,615 [classy] Setting parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,661 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
 2023-07-02 10:34:46,661 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,663 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00815153
 2023-07-02 10:34:46,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.475185897403032, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,663 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,683 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29596
 2023-07-02 10:34:46,683 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,683 [mcmc] New sample, #831:
   Omega_m:0.3233116, b1:0.4764688
 2023-07-02 10:34:46,683 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.4924010266341708}
 2023-07-02 10:34:46,683 [prior] Evaluating prior at array([0.32403292, 0.49240103])
 2023-07-02 10:34:46,683 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,684 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4924010266341708, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,684 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,684 [classy] Re-using computed results
 2023-07-02 10:34:46,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
 2023-07-02 10:34:46,684 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,684 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4924010266341708, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,684 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,703 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30798
 2023-07-02 10:34:46,703 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,703 [mcmc] New sample, #832:
   Omega_m:0.3240329, b1:0.4751859
 2023-07-02 10:34:46,703 [model] Posterior to be computed for parameters {'Omega_m': 0.34032158399284984, 'b1': 0.4634334214124502}
 2023-07-02 10:34:46,703 [prior] Evaluating prior at array([0.34032158, 0.46343342])
 2023-07-02 10:34:46,703 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,703 [model] Got input parameters: {'Omega_m': 0.34032158399284984, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4634334214124502, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,703 [classy] Got parameters {'Omega_m': 0.34032158399284984, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,703 [classy] Computing new state
 2023-07-02 10:34:46,703 [classy] Setting parameters: {'Omega_m': 0.34032158399284984, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,750 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.0370433254932}
 2023-07-02 10:34:46,750 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,752 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0446204
 2023-07-02 10:34:46,752 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4634334214124502, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,752 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,771 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.486859
 2023-07-02 10:34:46,771 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,771 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.526459826091082}
 2023-07-02 10:34:46,772 [prior] Evaluating prior at array([0.32403292, 0.52645983])
 2023-07-02 10:34:46,772 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,772 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.526459826091082, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,772 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,772 [classy] Re-using computed results
 2023-07-02 10:34:46,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
 2023-07-02 10:34:46,772 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,772 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.526459826091082, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,772 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,792 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.62071
 2023-07-02 10:34:46,792 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,792 [model] Posterior to be computed for parameters {'Omega_m': 0.2945567422101325, 'b1': 0.5448211776386088}
 2023-07-02 10:34:46,792 [prior] Evaluating prior at array([0.29455674, 0.54482118])
 2023-07-02 10:34:46,792 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,792 [model] Got input parameters: {'Omega_m': 0.2945567422101325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5448211776386088, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,792 [classy] Got parameters {'Omega_m': 0.2945567422101325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,792 [classy] Computing new state
 2023-07-02 10:34:46,792 [classy] Setting parameters: {'Omega_m': 0.2945567422101325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.47387734387172}
 2023-07-02 10:34:46,838 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0208254
 2023-07-02 10:34:46,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5448211776386088, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,840 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,860 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.171821
 2023-07-02 10:34:46,860 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.49649074141397276}
 2023-07-02 10:34:46,860 [prior] Evaluating prior at array([0.32403292, 0.49649074])
 2023-07-02 10:34:46,860 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,860 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49649074141397276, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,860 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,860 [classy] Re-using computed results
 2023-07-02 10:34:46,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
 2023-07-02 10:34:46,860 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49649074141397276, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,860 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,880 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07104
 2023-07-02 10:34:46,880 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,880 [model] Posterior to be computed for parameters {'Omega_m': 0.29740586748778725, 'b1': 0.5397543205377695}
 2023-07-02 10:34:46,880 [prior] Evaluating prior at array([0.29740587, 0.53975432])
 2023-07-02 10:34:46,880 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,880 [model] Got input parameters: {'Omega_m': 0.29740586748778725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5397543205377695, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,880 [classy] Got parameters {'Omega_m': 0.29740586748778725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,880 [classy] Computing new state
 2023-07-02 10:34:46,880 [classy] Setting parameters: {'Omega_m': 0.29740586748778725, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:46,927 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1142772528522}
 2023-07-02 10:34:46,927 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:46,928 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0146845
 2023-07-02 10:34:46,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5397543205377695, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,929 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,948 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.861591
 2023-07-02 10:34:46,948 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,948 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.5428104433336355}
 2023-07-02 10:34:46,948 [prior] Evaluating prior at array([0.32403292, 0.54281044])
 2023-07-02 10:34:46,948 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,948 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5428104433336355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,949 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,949 [classy] Re-using computed results
 2023-07-02 10:34:46,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
 2023-07-02 10:34:46,949 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:46,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5428104433336355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,949 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:46,968 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.48262
 2023-07-02 10:34:46,969 [model] Computed derived parameters: {}
 2023-07-02 10:34:46,969 [model] Posterior to be computed for parameters {'Omega_m': 0.34210341483664924, 'b1': 0.46026463050872723}
 2023-07-02 10:34:46,969 [prior] Evaluating prior at array([0.34210341, 0.46026463])
 2023-07-02 10:34:46,969 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:46,969 [model] Got input parameters: {'Omega_m': 0.34210341483664924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46026463050872723, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:46,969 [classy] Got parameters {'Omega_m': 0.34210341483664924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:46,969 [classy] Computing new state
 2023-07-02 10:34:46,969 [classy] Setting parameters: {'Omega_m': 0.34210341483664924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8389398909406}
 2023-07-02 10:34:47,018 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0502783
 2023-07-02 10:34:47,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46026463050872723, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,020 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,041 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.930303
 2023-07-02 10:34:47,041 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,041 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.47383756776374836}
 2023-07-02 10:34:47,041 [prior] Evaluating prior at array([0.32403292, 0.47383757])
 2023-07-02 10:34:47,041 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,042 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47383756776374836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,042 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,042 [classy] Re-using computed results
 2023-07-02 10:34:47,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
 2023-07-02 10:34:47,042 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47383756776374836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,042 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,061 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.22769
 2023-07-02 10:34:47,061 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,061 [mcmc] New sample, #833:
   Omega_m:0.3240329, b1:0.492401
 2023-07-02 10:34:47,061 [model] Posterior to be computed for parameters {'Omega_m': 0.301444991466047, 'b1': 0.5140077222768383}
 2023-07-02 10:34:47,062 [prior] Evaluating prior at array([0.30144499, 0.51400772])
 2023-07-02 10:34:47,062 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,062 [model] Got input parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5140077222768383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,062 [classy] Got parameters {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,062 [classy] Computing new state
 2023-07-02 10:34:47,062 [classy] Setting parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,108 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60960776742837}
 2023-07-02 10:34:47,109 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,110 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00788493
 2023-07-02 10:34:47,111 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5140077222768383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,111 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,134 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.4853
 2023-07-02 10:34:47,134 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,134 [mcmc] New sample, #834:
   Omega_m:0.3240329, b1:0.4738376
 2023-07-02 10:34:47,134 [model] Posterior to be computed for parameters {'Omega_m': 0.301444991466047, 'b1': 0.5749514980759027}
 2023-07-02 10:34:47,134 [prior] Evaluating prior at array([0.30144499, 0.5749515 ])
 2023-07-02 10:34:47,135 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,135 [model] Got input parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5749514980759027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,135 [classy] Got parameters {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,135 [classy] Re-using computed results
 2023-07-02 10:34:47,135 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60960776742837}
 2023-07-02 10:34:47,135 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5749514980759027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,135 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.1807
 2023-07-02 10:34:47,156 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,156 [model] Posterior to be computed for parameters {'Omega_m': 0.28172726617433125, 'b1': 0.5490735360514323}
 2023-07-02 10:34:47,156 [prior] Evaluating prior at array([0.28172727, 0.54907354])
 2023-07-02 10:34:47,157 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,157 [model] Got input parameters: {'Omega_m': 0.28172726617433125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5490735360514323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,157 [classy] Got parameters {'Omega_m': 0.28172726617433125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,157 [classy] Computing new state
 2023-07-02 10:34:47,157 [classy] Setting parameters: {'Omega_m': 0.28172726617433125, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.1314847539365}
 2023-07-02 10:34:47,204 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,205 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0629719
 2023-07-02 10:34:47,205 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5490735360514323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,226 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.66316
 2023-07-02 10:34:47,226 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,226 [model] Posterior to be computed for parameters {'Omega_m': 0.301444991466047, 'b1': 0.5045257792372396}
 2023-07-02 10:34:47,226 [prior] Evaluating prior at array([0.30144499, 0.50452578])
 2023-07-02 10:34:47,226 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,226 [model] Got input parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5045257792372396, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,226 [classy] Got parameters {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,226 [classy] Re-using computed results
 2023-07-02 10:34:47,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60960776742837}
 2023-07-02 10:34:47,226 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5045257792372396, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,226 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,246 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.712692
 2023-07-02 10:34:47,246 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,247 [model] Posterior to be computed for parameters {'Omega_m': 0.29679947600017464, 'b1': 0.522269262480044}
 2023-07-02 10:34:47,247 [prior] Evaluating prior at array([0.29679948, 0.52226926])
 2023-07-02 10:34:47,247 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,247 [model] Got input parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.522269262480044, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,247 [classy] Got parameters {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,247 [classy] Computing new state
 2023-07-02 10:34:47,247 [classy] Setting parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19056183055284}
 2023-07-02 10:34:47,294 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,296 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0158973
 2023-07-02 10:34:47,296 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.522269262480044, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,296 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,316 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.548139
 2023-07-02 10:34:47,316 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,316 [mcmc] New sample, #835:
   Omega_m:0.301445, b1:0.5140077
 2023-07-02 10:34:47,316 [model] Posterior to be computed for parameters {'Omega_m': 0.29679947600017464, 'b1': 0.5484701391944216}
 2023-07-02 10:34:47,316 [prior] Evaluating prior at array([0.29679948, 0.54847014])
 2023-07-02 10:34:47,316 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,316 [model] Got input parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5484701391944216, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,316 [classy] Got parameters {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,316 [classy] Re-using computed results
 2023-07-02 10:34:47,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19056183055284}
 2023-07-02 10:34:47,316 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,316 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5484701391944216, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,316 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,335 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.261447
 2023-07-02 10:34:47,336 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,336 [mcmc] New sample, #836:
   Omega_m:0.2967995, b1:0.5222693
 2023-07-02 10:34:47,336 [model] Posterior to be computed for parameters {'Omega_m': 0.28580216197621516, 'b1': 0.5680276571068408}
 2023-07-02 10:34:47,336 [prior] Evaluating prior at array([0.28580216, 0.56802766])
 2023-07-02 10:34:47,336 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,336 [model] Got input parameters: {'Omega_m': 0.28580216197621516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5680276571068408, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,336 [classy] Got parameters {'Omega_m': 0.28580216197621516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,336 [classy] Computing new state
 2023-07-02 10:34:47,336 [classy] Setting parameters: {'Omega_m': 0.28580216197621516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,382 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.59802156619912}
 2023-07-02 10:34:47,382 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,384 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0469356
 2023-07-02 10:34:47,384 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5680276571068408, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,384 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,405 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.14085
 2023-07-02 10:34:47,405 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,405 [model] Posterior to be computed for parameters {'Omega_m': 0.29679947600017464, 'b1': 0.5195493455265492}
 2023-07-02 10:34:47,405 [prior] Evaluating prior at array([0.29679948, 0.51954935])
 2023-07-02 10:34:47,406 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,406 [model] Got input parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195493455265492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,406 [classy] Got parameters {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,406 [classy] Re-using computed results
 2023-07-02 10:34:47,406 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19056183055284}
 2023-07-02 10:34:47,406 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,406 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195493455265492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,406 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,426 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.371791
 2023-07-02 10:34:47,426 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,426 [mcmc] New sample, #837:
   Omega_m:0.2967995, b1:0.5484701
 2023-07-02 10:34:47,426 [model] Posterior to be computed for parameters {'Omega_m': 0.32409833934501886, 'b1': 0.4710013084611083}
 2023-07-02 10:34:47,426 [prior] Evaluating prior at array([0.32409834, 0.47100131])
 2023-07-02 10:34:47,427 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,427 [model] Got input parameters: {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4710013084611083, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,427 [classy] Got parameters {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,427 [classy] Computing new state
 2023-07-02 10:34:47,427 [classy] Setting parameters: {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.88523769549832}
 2023-07-02 10:34:47,474 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00824059
 2023-07-02 10:34:47,476 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4710013084611083, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,476 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,495 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0548
 2023-07-02 10:34:47,495 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,495 [mcmc] New sample, #838:
   Omega_m:0.2967995, b1:0.5195493
 2023-07-02 10:34:47,495 [model] Posterior to be computed for parameters {'Omega_m': 0.32409833934501886, 'b1': 0.44928352353592915}
 2023-07-02 10:34:47,496 [prior] Evaluating prior at array([0.32409834, 0.44928352])
 2023-07-02 10:34:47,496 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,496 [model] Got input parameters: {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44928352353592915, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,496 [classy] Got parameters {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,496 [classy] Re-using computed results
 2023-07-02 10:34:47,496 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.88523769549832}
 2023-07-02 10:34:47,496 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44928352353592915, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,496 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,515 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.637678
 2023-07-02 10:34:47,515 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,516 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.4799960176719383}
 2023-07-02 10:34:47,516 [prior] Evaluating prior at array([0.31904056, 0.47999602])
 2023-07-02 10:34:47,516 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,516 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4799960176719383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,516 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,516 [classy] Computing new state
 2023-07-02 10:34:47,516 [classy] Setting parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
 2023-07-02 10:34:47,562 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,564 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00279585
 2023-07-02 10:34:47,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4799960176719383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,564 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,583 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39214
 2023-07-02 10:34:47,583 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,583 [mcmc] New sample, #839:
   Omega_m:0.3240983, b1:0.4710013
 2023-07-02 10:34:47,584 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.46708924711558697}
 2023-07-02 10:34:47,584 [prior] Evaluating prior at array([0.31904056, 0.46708925])
 2023-07-02 10:34:47,584 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,584 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46708924711558697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,584 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,584 [classy] Re-using computed results
 2023-07-02 10:34:47,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
 2023-07-02 10:34:47,584 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46708924711558697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,584 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,604 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07291
 2023-07-02 10:34:47,604 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,604 [mcmc] New sample, #840:
   Omega_m:0.3190406, b1:0.479996
 2023-07-02 10:34:47,604 [model] Posterior to be computed for parameters {'Omega_m': 0.3431241161118568, 'b1': 0.42425927875834646}
 2023-07-02 10:34:47,604 [prior] Evaluating prior at array([0.34312412, 0.42425928])
 2023-07-02 10:34:47,604 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,604 [model] Got input parameters: {'Omega_m': 0.3431241161118568, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42425927875834646, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,605 [classy] Got parameters {'Omega_m': 0.3431241161118568, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,605 [classy] Computing new state
 2023-07-02 10:34:47,605 [classy] Setting parameters: {'Omega_m': 0.3431241161118568, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.72587887103907}
 2023-07-02 10:34:47,651 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0536611
 2023-07-02 10:34:47,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42425927875834646, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,653 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,672 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.67877
 2023-07-02 10:34:47,672 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,672 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.5029299393766773}
 2023-07-02 10:34:47,672 [prior] Evaluating prior at array([0.31904056, 0.50292994])
 2023-07-02 10:34:47,673 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,673 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029299393766773, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,673 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,673 [classy] Re-using computed results
 2023-07-02 10:34:47,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
 2023-07-02 10:34:47,673 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029299393766773, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,673 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57604
 2023-07-02 10:34:47,692 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,692 [mcmc] New sample, #841:
   Omega_m:0.3190406, b1:0.4670892
 2023-07-02 10:34:47,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3859178305625387, 'b1': 0.38399603917892033}
 2023-07-02 10:34:47,692 [prior] Evaluating prior at array([0.38591783, 0.38399604])
 2023-07-02 10:34:47,693 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,693 [model] Got input parameters: {'Omega_m': 0.3859178305625387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38399603917892033, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,693 [classy] Got parameters {'Omega_m': 0.3859178305625387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,693 [classy] Computing new state
 2023-07-02 10:34:47,693 [classy] Setting parameters: {'Omega_m': 0.3859178305625387, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.2448833921163}
 2023-07-02 10:34:47,739 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,741 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.278917
 2023-07-02 10:34:47,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38399603917892033, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,741 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,761 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.1828
 2023-07-02 10:34:47,761 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,762 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.43592660179220477}
 2023-07-02 10:34:47,762 [prior] Evaluating prior at array([0.31904056, 0.4359266 ])
 2023-07-02 10:34:47,762 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,762 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43592660179220477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,762 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,762 [classy] Re-using computed results
 2023-07-02 10:34:47,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
 2023-07-02 10:34:47,762 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,762 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43592660179220477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,762 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,782 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.47869
 2023-07-02 10:34:47,782 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,782 [model] Posterior to be computed for parameters {'Omega_m': 0.32869453131635723, 'b1': 0.48576140639283083}
 2023-07-02 10:34:47,782 [prior] Evaluating prior at array([0.32869453, 0.48576141])
 2023-07-02 10:34:47,782 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,782 [model] Got input parameters: {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48576140639283083, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,782 [classy] Got parameters {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,782 [classy] Computing new state
 2023-07-02 10:34:47,782 [classy] Setting parameters: {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35327563092815}
 2023-07-02 10:34:47,828 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156891
 2023-07-02 10:34:47,830 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48576140639283083, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,830 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,850 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66891
 2023-07-02 10:34:47,850 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,850 [mcmc] New sample, #842:
   Omega_m:0.3190406, b1:0.5029299
 2023-07-02 10:34:47,850 [model] Posterior to be computed for parameters {'Omega_m': 0.32869453131635723, 'b1': 0.4709479747084497}
 2023-07-02 10:34:47,850 [prior] Evaluating prior at array([0.32869453, 0.47094797])
 2023-07-02 10:34:47,850 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,850 [model] Got input parameters: {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4709479747084497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,851 [classy] Got parameters {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,851 [classy] Re-using computed results
 2023-07-02 10:34:47,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35327563092815}
 2023-07-02 10:34:47,851 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4709479747084497, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,851 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,870 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90187
 2023-07-02 10:34:47,870 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,870 [mcmc] New sample, #843:
   Omega_m:0.3286945, b1:0.4857614
 2023-07-02 10:34:47,870 [model] Posterior to be computed for parameters {'Omega_m': 0.3115643998545878, 'b1': 0.5014120364034917}
 2023-07-02 10:34:47,870 [prior] Evaluating prior at array([0.3115644 , 0.50141204])
 2023-07-02 10:34:47,871 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,871 [model] Got input parameters: {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5014120364034917, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,871 [classy] Got parameters {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,871 [classy] Computing new state
 2023-07-02 10:34:47,871 [classy] Setting parameters: {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:47,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.37092612240352}
 2023-07-02 10:34:47,917 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:47,918 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000254345
 2023-07-02 10:34:47,919 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5014120364034917, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,919 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,938 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78004
 2023-07-02 10:34:47,938 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,938 [mcmc] New sample, #844:
   Omega_m:0.3286945, b1:0.470948
 2023-07-02 10:34:47,938 [model] Posterior to be computed for parameters {'Omega_m': 0.3115643998545878, 'b1': 0.5291632861224524}
 2023-07-02 10:34:47,938 [prior] Evaluating prior at array([0.3115644 , 0.52916329])
 2023-07-02 10:34:47,938 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,938 [model] Got input parameters: {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5291632861224524, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,938 [classy] Got parameters {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,938 [classy] Re-using computed results
 2023-07-02 10:34:47,938 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.37092612240352}
 2023-07-02 10:34:47,939 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:47,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5291632861224524, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,939 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:47,958 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45076
 2023-07-02 10:34:47,958 [model] Computed derived parameters: {}
 2023-07-02 10:34:47,959 [model] Posterior to be computed for parameters {'Omega_m': 0.3104685369835521, 'b1': 0.5033609084356209}
 2023-07-02 10:34:47,959 [prior] Evaluating prior at array([0.31046854, 0.50336091])
 2023-07-02 10:34:47,959 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:47,959 [model] Got input parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5033609084356209, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:47,959 [classy] Got parameters {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:47,959 [classy] Computing new state
 2023-07-02 10:34:47,959 [classy] Setting parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50334483659913}
 2023-07-02 10:34:48,005 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,007 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000452739
 2023-07-02 10:34:48,007 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5033609084356209, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,007 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72615
 2023-07-02 10:34:48,026 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,026 [mcmc] New sample, #845:
   Omega_m:0.3115644, b1:0.501412
 2023-07-02 10:34:48,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3104685369835521, 'b1': 0.5501529142575533}
 2023-07-02 10:34:48,027 [prior] Evaluating prior at array([0.31046854, 0.55015291])
 2023-07-02 10:34:48,027 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,027 [model] Got input parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5501529142575533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,027 [classy] Got parameters {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,027 [classy] Re-using computed results
 2023-07-02 10:34:48,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50334483659913}
 2023-07-02 10:34:48,027 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5501529142575533, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,027 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.03694
 2023-07-02 10:34:48,046 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,046 [model] Posterior to be computed for parameters {'Omega_m': 0.29074059409736447, 'b1': 0.5384448930823451}
 2023-07-02 10:34:48,046 [prior] Evaluating prior at array([0.29074059, 0.53844489])
 2023-07-02 10:34:48,046 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,047 [model] Got input parameters: {'Omega_m': 0.29074059409736447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5384448930823451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,047 [classy] Got parameters {'Omega_m': 0.29074059409736447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,047 [classy] Computing new state
 2023-07-02 10:34:48,047 [classy] Setting parameters: {'Omega_m': 0.29074059409736447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.96029194232824}
 2023-07-02 10:34:48,093 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,095 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0308406
 2023-07-02 10:34:48,095 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5384448930823451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,095 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,114 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.889967
 2023-07-02 10:34:48,114 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,115 [model] Posterior to be computed for parameters {'Omega_m': 0.3104685369835521, 'b1': 0.546824643797829}
 2023-07-02 10:34:48,115 [prior] Evaluating prior at array([0.31046854, 0.54682464])
 2023-07-02 10:34:48,115 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,115 [model] Got input parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.546824643797829, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,115 [classy] Got parameters {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,115 [classy] Re-using computed results
 2023-07-02 10:34:48,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50334483659913}
 2023-07-02 10:34:48,115 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,115 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.546824643797829, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,115 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,136 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.28026
 2023-07-02 10:34:48,136 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,137 [model] Posterior to be computed for parameters {'Omega_m': 0.31747201728014973, 'b1': 0.49090598616536735}
 2023-07-02 10:34:48,137 [prior] Evaluating prior at array([0.31747202, 0.49090599])
 2023-07-02 10:34:48,137 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,137 [model] Got input parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49090598616536735, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,137 [classy] Got parameters {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,137 [classy] Computing new state
 2023-07-02 10:34:48,137 [classy] Setting parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.66415246300454}
 2023-07-02 10:34:48,184 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,185 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0017093
 2023-07-02 10:34:48,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49090598616536735, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,205 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83177
 2023-07-02 10:34:48,205 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,205 [mcmc] New sample, #846:
   Omega_m:0.3104685, b1:0.5033609
 2023-07-02 10:34:48,205 [model] Posterior to be computed for parameters {'Omega_m': 0.31747201728014973, 'b1': 0.4956267208219138}
 2023-07-02 10:34:48,205 [prior] Evaluating prior at array([0.31747202, 0.49562672])
 2023-07-02 10:34:48,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,206 [model] Got input parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4956267208219138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,206 [classy] Got parameters {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,206 [classy] Re-using computed results
 2023-07-02 10:34:48,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.66415246300454}
 2023-07-02 10:34:48,206 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4956267208219138, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,225 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89763
 2023-07-02 10:34:48,225 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,225 [mcmc] New sample, #847:
   Omega_m:0.317472, b1:0.490906
 2023-07-02 10:34:48,225 [model] Posterior to be computed for parameters {'Omega_m': 0.26609426637254247, 'b1': 0.5869964208674137}
 2023-07-02 10:34:48,225 [prior] Evaluating prior at array([0.26609427, 0.58699642])
 2023-07-02 10:34:48,226 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,226 [model] Got input parameters: {'Omega_m': 0.26609426637254247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5869964208674137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,226 [classy] Got parameters {'Omega_m': 0.26609426637254247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,226 [classy] Computing new state
 2023-07-02 10:34:48,226 [classy] Setting parameters: {'Omega_m': 0.26609426637254247, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,272 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.24119210357722}
 2023-07-02 10:34:48,272 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,274 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.149129
 2023-07-02 10:34:48,274 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5869964208674137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,274 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,294 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.7207
 2023-07-02 10:34:48,294 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,294 [model] Posterior to be computed for parameters {'Omega_m': 0.31747201728014973, 'b1': 0.5297735251088072}
 2023-07-02 10:34:48,294 [prior] Evaluating prior at array([0.31747202, 0.52977353])
 2023-07-02 10:34:48,294 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,294 [model] Got input parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5297735251088072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,294 [classy] Got parameters {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,294 [classy] Re-using computed results
 2023-07-02 10:34:48,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.66415246300454}
 2023-07-02 10:34:48,294 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5297735251088072, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,294 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,314 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.317312
 2023-07-02 10:34:48,314 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,314 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.5012532612779295}
 2023-07-02 10:34:48,314 [prior] Evaluating prior at array([0.31430818, 0.50125326])
 2023-07-02 10:34:48,314 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,314 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5012532612779295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,314 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,314 [classy] Computing new state
 2023-07-02 10:34:48,314 [classy] Setting parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
 2023-07-02 10:34:48,360 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000405595
 2023-07-02 10:34:48,363 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5012532612779295, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,363 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,382 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.922
 2023-07-02 10:34:48,382 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,382 [mcmc] New sample, #848:
   Omega_m:0.317472, b1:0.4956267
 2023-07-02 10:34:48,382 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.5066477099922623}
 2023-07-02 10:34:48,382 [prior] Evaluating prior at array([0.31430818, 0.50664771])
 2023-07-02 10:34:48,382 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,382 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066477099922623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,383 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,383 [classy] Re-using computed results
 2023-07-02 10:34:48,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
 2023-07-02 10:34:48,383 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,383 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066477099922623, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,383 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,402 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85345
 2023-07-02 10:34:48,402 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,402 [mcmc] New sample, #849:
   Omega_m:0.3143082, b1:0.5012533
 2023-07-02 10:34:48,402 [model] Posterior to be computed for parameters {'Omega_m': 0.32723143762514656, 'b1': 0.48366510988420214}
 2023-07-02 10:34:48,402 [prior] Evaluating prior at array([0.32723144, 0.48366511])
 2023-07-02 10:34:48,402 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,402 [model] Got input parameters: {'Omega_m': 0.32723143762514656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48366510988420214, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,402 [classy] Got parameters {'Omega_m': 0.32723143762514656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,402 [classy] Computing new state
 2023-07-02 10:34:48,402 [classy] Setting parameters: {'Omega_m': 0.32723143762514656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,448 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5218862726905}
 2023-07-02 10:34:48,449 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,450 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0130648
 2023-07-02 10:34:48,450 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48366510988420214, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,450 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,470 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06921
 2023-07-02 10:34:48,470 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,471 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.45797125188107785}
 2023-07-02 10:34:48,471 [prior] Evaluating prior at array([0.31430818, 0.45797125])
 2023-07-02 10:34:48,471 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,471 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45797125188107785, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,471 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,471 [classy] Re-using computed results
 2023-07-02 10:34:48,471 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
 2023-07-02 10:34:48,471 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,471 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45797125188107785, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,471 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.98598
 2023-07-02 10:34:48,490 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,490 [model] Posterior to be computed for parameters {'Omega_m': 0.35912640677829033, 'b1': 0.42694340227726757}
 2023-07-02 10:34:48,491 [prior] Evaluating prior at array([0.35912641, 0.4269434 ])
 2023-07-02 10:34:48,491 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,491 [model] Got input parameters: {'Omega_m': 0.35912640677829033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42694340227726757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,491 [classy] Got parameters {'Omega_m': 0.35912640677829033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,491 [classy] Computing new state
 2023-07-02 10:34:48,491 [classy] Setting parameters: {'Omega_m': 0.35912640677829033, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,537 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99259201442393}
 2023-07-02 10:34:48,537 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,539 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119575
 2023-07-02 10:34:48,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42694340227726757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,539 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,558 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.18388
 2023-07-02 10:34:48,558 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,559 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.4935075616414551}
 2023-07-02 10:34:48,559 [prior] Evaluating prior at array([0.31430818, 0.49350756])
 2023-07-02 10:34:48,559 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,559 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935075616414551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,559 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,559 [classy] Re-using computed results
 2023-07-02 10:34:48,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
 2023-07-02 10:34:48,559 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,559 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935075616414551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,559 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,579 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74714
 2023-07-02 10:34:48,579 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,579 [mcmc] New sample, #850:
   Omega_m:0.3143082, b1:0.5066477
 2023-07-02 10:34:48,579 [model] Posterior to be computed for parameters {'Omega_m': 0.3035474520177017, 'b1': 0.5126443346590441}
 2023-07-02 10:34:48,579 [prior] Evaluating prior at array([0.30354745, 0.51264433])
 2023-07-02 10:34:48,579 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,579 [model] Got input parameters: {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5126443346590441, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,579 [classy] Got parameters {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,579 [classy] Computing new state
 2023-07-02 10:34:48,579 [classy] Setting parameters: {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.34928096773456}
 2023-07-02 10:34:48,625 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00521066
 2023-07-02 10:34:48,627 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5126443346590441, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,627 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,647 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9351
 2023-07-02 10:34:48,647 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,647 [mcmc] New sample, #851:
   Omega_m:0.3143082, b1:0.4935076
 2023-07-02 10:34:48,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3035474520177017, 'b1': 0.5002412882166071}
 2023-07-02 10:34:48,647 [prior] Evaluating prior at array([0.30354745, 0.50024129])
 2023-07-02 10:34:48,647 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,647 [model] Got input parameters: {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5002412882166071, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,647 [classy] Got parameters {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,647 [classy] Re-using computed results
 2023-07-02 10:34:48,647 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.34928096773456}
 2023-07-02 10:34:48,647 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,647 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5002412882166071, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,647 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,667 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.985486
 2023-07-02 10:34:48,667 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,667 [model] Posterior to be computed for parameters {'Omega_m': 0.2991481277164094, 'b1': 0.520468050853527}
 2023-07-02 10:34:48,667 [prior] Evaluating prior at array([0.29914813, 0.52046805])
 2023-07-02 10:34:48,668 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,668 [model] Got input parameters: {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520468050853527, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,668 [classy] Got parameters {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,668 [classy] Computing new state
 2023-07-02 10:34:48,668 [classy] Setting parameters: {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89585662271068}
 2023-07-02 10:34:48,714 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114805
 2023-07-02 10:34:48,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520468050853527, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,716 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.18113
 2023-07-02 10:34:48,736 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,736 [mcmc] New sample, #852:
   Omega_m:0.3035475, b1:0.5126443
 2023-07-02 10:34:48,736 [model] Posterior to be computed for parameters {'Omega_m': 0.2991481277164094, 'b1': 0.4563736950417163}
 2023-07-02 10:34:48,736 [prior] Evaluating prior at array([0.29914813, 0.4563737 ])
 2023-07-02 10:34:48,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,736 [model] Got input parameters: {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4563736950417163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,736 [classy] Got parameters {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,736 [classy] Re-using computed results
 2023-07-02 10:34:48,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89585662271068}
 2023-07-02 10:34:48,736 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4563736950417163, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,736 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,755 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.6734
 2023-07-02 10:34:48,755 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,755 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.5050961338844887}
 2023-07-02 10:34:48,756 [prior] Evaluating prior at array([0.30779185, 0.50509613])
 2023-07-02 10:34:48,756 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,756 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5050961338844887, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,756 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,756 [classy] Computing new state
 2023-07-02 10:34:48,756 [classy] Setting parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,802 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
 2023-07-02 10:34:48,802 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,804 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00156845
 2023-07-02 10:34:48,804 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5050961338844887, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,804 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,824 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42439
 2023-07-02 10:34:48,824 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,824 [mcmc] New sample, #853:
   Omega_m:0.2991481, b1:0.5204681
 2023-07-02 10:34:48,824 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.5211063072151036}
 2023-07-02 10:34:48,824 [prior] Evaluating prior at array([0.30779185, 0.52110631])
 2023-07-02 10:34:48,824 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,824 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5211063072151036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,825 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,825 [classy] Re-using computed results
 2023-07-02 10:34:48,825 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
 2023-07-02 10:34:48,825 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,825 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5211063072151036, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,825 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,844 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45049
 2023-07-02 10:34:48,844 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,844 [mcmc] New sample, #854:
   Omega_m:0.3077919, b1:0.5050961
 2023-07-02 10:34:48,844 [model] Posterior to be computed for parameters {'Omega_m': 0.37910410519323506, 'b1': 0.3942852797705202}
 2023-07-02 10:34:48,844 [prior] Evaluating prior at array([0.37910411, 0.39428528])
 2023-07-02 10:34:48,844 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,844 [model] Got input parameters: {'Omega_m': 0.37910410519323506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3942852797705202, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,844 [classy] Got parameters {'Omega_m': 0.37910410519323506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,844 [classy] Computing new state
 2023-07-02 10:34:48,844 [classy] Setting parameters: {'Omega_m': 0.37910410519323506, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.92635743321486}
 2023-07-02 10:34:48,891 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,893 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.23305
 2023-07-02 10:34:48,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3942852797705202, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,893 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,913 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.7838
 2023-07-02 10:34:48,913 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,913 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.5057991659602125}
 2023-07-02 10:34:48,913 [prior] Evaluating prior at array([0.30779185, 0.50579917])
 2023-07-02 10:34:48,913 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,913 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5057991659602125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,913 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,913 [classy] Re-using computed results
 2023-07-02 10:34:48,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
 2023-07-02 10:34:48,913 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:48,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5057991659602125, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,913 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:48,933 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4541
 2023-07-02 10:34:48,933 [model] Computed derived parameters: {}
 2023-07-02 10:34:48,933 [mcmc] New sample, #855:
   Omega_m:0.3077919, b1:0.5211063
 2023-07-02 10:34:48,933 [model] Posterior to be computed for parameters {'Omega_m': 0.29508295484762087, 'b1': 0.5284005474171428}
 2023-07-02 10:34:48,933 [prior] Evaluating prior at array([0.29508295, 0.52840055])
 2023-07-02 10:34:48,933 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:48,933 [model] Got input parameters: {'Omega_m': 0.29508295484762087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5284005474171428, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,933 [classy] Got parameters {'Omega_m': 0.29508295484762087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:48,933 [classy] Computing new state
 2023-07-02 10:34:48,933 [classy] Setting parameters: {'Omega_m': 0.29508295484762087, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:48,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.40723801759458}
 2023-07-02 10:34:48,980 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:48,982 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0196062
 2023-07-02 10:34:48,982 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5284005474171428, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:48,982 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,001 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.280668
 2023-07-02 10:34:49,001 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,001 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.4559757099326681}
 2023-07-02 10:34:49,001 [prior] Evaluating prior at array([0.30779185, 0.45597571])
 2023-07-02 10:34:49,001 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,001 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4559757099326681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,001 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,001 [classy] Re-using computed results
 2023-07-02 10:34:49,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
 2023-07-02 10:34:49,002 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,002 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4559757099326681, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,002 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,022 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.73246
 2023-07-02 10:34:49,022 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,022 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.4957652741814575}
 2023-07-02 10:34:49,022 [prior] Evaluating prior at array([0.31343397, 0.49576527])
 2023-07-02 10:34:49,022 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,022 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4957652741814575, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,022 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,022 [classy] Computing new state
 2023-07-02 10:34:49,022 [classy] Setting parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,069 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
 2023-07-02 10:34:49,069 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,070 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000257606
 2023-07-02 10:34:49,071 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4957652741814575, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,071 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,090 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76188
 2023-07-02 10:34:49,090 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,090 [mcmc] New sample, #856:
   Omega_m:0.3077919, b1:0.5057992
 2023-07-02 10:34:49,090 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.46923495932215875}
 2023-07-02 10:34:49,090 [prior] Evaluating prior at array([0.31343397, 0.46923496])
 2023-07-02 10:34:49,090 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,091 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46923495932215875, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,091 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,091 [classy] Re-using computed results
 2023-07-02 10:34:49,091 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
 2023-07-02 10:34:49,091 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,091 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46923495932215875, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,091 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,110 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0903208
 2023-07-02 10:34:49,110 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,110 [model] Posterior to be computed for parameters {'Omega_m': 0.2762907563735879, 'b1': 0.5618204131651714}
 2023-07-02 10:34:49,110 [prior] Evaluating prior at array([0.27629076, 0.56182041])
 2023-07-02 10:34:49,110 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,111 [model] Got input parameters: {'Omega_m': 0.2762907563735879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5618204131651714, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,111 [classy] Got parameters {'Omega_m': 0.2762907563735879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,111 [classy] Computing new state
 2023-07-02 10:34:49,111 [classy] Setting parameters: {'Omega_m': 0.2762907563735879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.85357714959466}
 2023-07-02 10:34:49,158 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0883891
 2023-07-02 10:34:49,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5618204131651714, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,160 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,181 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.27767
 2023-07-02 10:34:49,181 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,181 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.5104951518761213}
 2023-07-02 10:34:49,181 [prior] Evaluating prior at array([0.31343397, 0.51049515])
 2023-07-02 10:34:49,181 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,181 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5104951518761213, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,181 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,181 [classy] Re-using computed results
 2023-07-02 10:34:49,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
 2023-07-02 10:34:49,181 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,181 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5104951518761213, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,182 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,201 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76458
 2023-07-02 10:34:49,201 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,201 [mcmc] New sample, #857:
   Omega_m:0.313434, b1:0.4957653
 2023-07-02 10:34:49,201 [model] Posterior to be computed for parameters {'Omega_m': 0.25648385931008455, 'b1': 0.6117746868591633}
 2023-07-02 10:34:49,201 [prior] Evaluating prior at array([0.25648386, 0.61177469])
 2023-07-02 10:34:49,202 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,202 [model] Got input parameters: {'Omega_m': 0.25648385931008455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6117746868591633, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,202 [classy] Got parameters {'Omega_m': 0.25648385931008455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,202 [classy] Computing new state
 2023-07-02 10:34:49,202 [classy] Setting parameters: {'Omega_m': 0.25648385931008455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.59068601990776}
 2023-07-02 10:34:49,248 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.223064
 2023-07-02 10:34:49,250 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6117746868591633, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,250 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -21.9196
 2023-07-02 10:34:49,270 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,271 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.4263976387719794}
 2023-07-02 10:34:49,271 [prior] Evaluating prior at array([0.31343397, 0.42639764])
 2023-07-02 10:34:49,271 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,271 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4263976387719794, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,271 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,271 [classy] Re-using computed results
 2023-07-02 10:34:49,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
 2023-07-02 10:34:49,271 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,271 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4263976387719794, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,271 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,290 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.7765
 2023-07-02 10:34:49,291 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,291 [model] Posterior to be computed for parameters {'Omega_m': 0.2692154022216236, 'b1': 0.5891330329059636}
 2023-07-02 10:34:49,291 [prior] Evaluating prior at array([0.2692154 , 0.58913303])
 2023-07-02 10:34:49,291 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,291 [model] Got input parameters: {'Omega_m': 0.2692154022216236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5891330329059636, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,291 [classy] Got parameters {'Omega_m': 0.2692154022216236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,291 [classy] Computing new state
 2023-07-02 10:34:49,291 [classy] Setting parameters: {'Omega_m': 0.2692154022216236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.811721065736}
 2023-07-02 10:34:49,338 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,340 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.128665
 2023-07-02 10:34:49,340 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5891330329059636, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,340 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,359 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.5696
 2023-07-02 10:34:49,359 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,359 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.49831227120806043}
 2023-07-02 10:34:49,359 [prior] Evaluating prior at array([0.31343397, 0.49831227])
 2023-07-02 10:34:49,360 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,360 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49831227120806043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,360 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,360 [classy] Re-using computed results
 2023-07-02 10:34:49,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
 2023-07-02 10:34:49,360 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,360 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49831227120806043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,360 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,382 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.84546
 2023-07-02 10:34:49,382 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,382 [mcmc] New sample, #858:
   Omega_m:0.313434, b1:0.5104952
 2023-07-02 10:34:49,382 [model] Posterior to be computed for parameters {'Omega_m': 0.30144081557143426, 'b1': 0.5196407858370766}
 2023-07-02 10:34:49,382 [prior] Evaluating prior at array([0.30144082, 0.51964079])
 2023-07-02 10:34:49,382 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,382 [model] Got input parameters: {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5196407858370766, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,383 [classy] Got parameters {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,383 [classy] Computing new state
 2023-07-02 10:34:49,383 [classy] Setting parameters: {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.61012596652807}
 2023-07-02 10:34:49,429 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00789082
 2023-07-02 10:34:49,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5196407858370766, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,431 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,451 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72515
 2023-07-02 10:34:49,451 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,451 [mcmc] New sample, #859:
   Omega_m:0.313434, b1:0.4983123
 2023-07-02 10:34:49,451 [model] Posterior to be computed for parameters {'Omega_m': 0.30144081557143426, 'b1': 0.5019421168539557}
 2023-07-02 10:34:49,451 [prior] Evaluating prior at array([0.30144082, 0.50194212])
 2023-07-02 10:34:49,451 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,451 [model] Got input parameters: {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5019421168539557, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,451 [classy] Got parameters {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,451 [classy] Re-using computed results
 2023-07-02 10:34:49,451 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.61012596652807}
 2023-07-02 10:34:49,451 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,451 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5019421168539557, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,451 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.42211
 2023-07-02 10:34:49,471 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,471 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.4994609822317079}
 2023-07-02 10:34:49,471 [prior] Evaluating prior at array([0.31278804, 0.49946098])
 2023-07-02 10:34:49,472 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,472 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4994609822317079, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,472 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,472 [classy] Computing new state
 2023-07-02 10:34:49,472 [classy] Setting parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,518 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,518 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,520 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000208038
 2023-07-02 10:34:49,520 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4994609822317079, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,520 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,540 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82955
 2023-07-02 10:34:49,540 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,540 [mcmc] New sample, #860:
   Omega_m:0.3014408, b1:0.5196408
 2023-07-02 10:34:49,540 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5420494118386683}
 2023-07-02 10:34:49,540 [prior] Evaluating prior at array([0.31278804, 0.54204941])
 2023-07-02 10:34:49,540 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,540 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5420494118386683, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,540 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,540 [classy] Re-using computed results
 2023-07-02 10:34:49,540 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,540 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5420494118386683, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,540 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,560 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.07295
 2023-07-02 10:34:49,560 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,560 [model] Posterior to be computed for parameters {'Omega_m': 0.35253862110303025, 'b1': 0.42876893796656346}
 2023-07-02 10:34:49,560 [prior] Evaluating prior at array([0.35253862, 0.42876894])
 2023-07-02 10:34:49,560 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,560 [model] Got input parameters: {'Omega_m': 0.35253862110303025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42876893796656346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,560 [classy] Got parameters {'Omega_m': 0.35253862110303025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,560 [classy] Computing new state
 2023-07-02 10:34:49,560 [classy] Setting parameters: {'Omega_m': 0.35253862110303025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,607 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.69740235943615}
 2023-07-02 10:34:49,608 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0895757
 2023-07-02 10:34:49,609 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42876893796656346, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,610 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,629 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.80469
 2023-07-02 10:34:49,630 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,630 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5105933358035578}
 2023-07-02 10:34:49,630 [prior] Evaluating prior at array([0.31278804, 0.51059334])
 2023-07-02 10:34:49,630 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,630 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5105933358035578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,630 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,630 [classy] Re-using computed results
 2023-07-02 10:34:49,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,630 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5105933358035578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,630 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,649 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78888
 2023-07-02 10:34:49,649 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,649 [mcmc] New sample, #861:
   Omega_m:0.312788, b1:0.499461
 2023-07-02 10:34:49,649 [model] Posterior to be computed for parameters {'Omega_m': 0.25501858851183784, 'b1': 0.6133299833141233}
 2023-07-02 10:34:49,650 [prior] Evaluating prior at array([0.25501859, 0.61332998])
 2023-07-02 10:34:49,650 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,650 [model] Got input parameters: {'Omega_m': 0.25501858851183784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6133299833141233, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,650 [classy] Got parameters {'Omega_m': 0.25501858851183784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,650 [classy] Computing new state
 2023-07-02 10:34:49,650 [classy] Setting parameters: {'Omega_m': 0.25501858851183784, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.80014580770938}
 2023-07-02 10:34:49,699 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,700 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.235843
 2023-07-02 10:34:49,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6133299833141233, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,720 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.2995
 2023-07-02 10:34:49,720 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,720 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5016276478959882}
 2023-07-02 10:34:49,720 [prior] Evaluating prior at array([0.31278804, 0.50162765])
 2023-07-02 10:34:49,720 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,720 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5016276478959882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,720 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,720 [classy] Re-using computed results
 2023-07-02 10:34:49,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,721 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5016276478959882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,721 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,741 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87383
 2023-07-02 10:34:49,741 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,741 [mcmc] New sample, #862:
   Omega_m:0.312788, b1:0.5105933
 2023-07-02 10:34:49,741 [model] Posterior to be computed for parameters {'Omega_m': 0.32660753010044036, 'b1': 0.47705120746527296}
 2023-07-02 10:34:49,741 [prior] Evaluating prior at array([0.32660753, 0.47705121])
 2023-07-02 10:34:49,741 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,741 [model] Got input parameters: {'Omega_m': 0.32660753010044036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47705120746527296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,742 [classy] Got parameters {'Omega_m': 0.32660753010044036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,742 [classy] Computing new state
 2023-07-02 10:34:49,742 [classy] Setting parameters: {'Omega_m': 0.32660753010044036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5939923405736}
 2023-07-02 10:34:49,790 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0120172
 2023-07-02 10:34:49,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47705120746527296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,792 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,811 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21487
 2023-07-02 10:34:49,811 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,811 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.512498170869073}
 2023-07-02 10:34:49,811 [prior] Evaluating prior at array([0.31278804, 0.51249817])
 2023-07-02 10:34:49,812 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,812 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.512498170869073, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,812 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,812 [classy] Re-using computed results
 2023-07-02 10:34:49,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,812 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.512498170869073, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,812 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,831 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71448
 2023-07-02 10:34:49,831 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,832 [mcmc] New sample, #863:
   Omega_m:0.312788, b1:0.5016276
 2023-07-02 10:34:49,832 [model] Posterior to be computed for parameters {'Omega_m': 0.2895232767840174, 'b1': 0.5538720112909825}
 2023-07-02 10:34:49,832 [prior] Evaluating prior at array([0.28952328, 0.55387201])
 2023-07-02 10:34:49,832 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,832 [model] Got input parameters: {'Omega_m': 0.2895232767840174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5538720112909825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,832 [classy] Got parameters {'Omega_m': 0.2895232767840174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,832 [classy] Computing new state
 2023-07-02 10:34:49,832 [classy] Setting parameters: {'Omega_m': 0.2895232767840174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.11661649397863}
 2023-07-02 10:34:49,878 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0344753
 2023-07-02 10:34:49,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5538720112909825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,880 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33972
 2023-07-02 10:34:49,899 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,900 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5004772375468736}
 2023-07-02 10:34:49,900 [prior] Evaluating prior at array([0.31278804, 0.50047724])
 2023-07-02 10:34:49,900 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,900 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5004772375468736, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,900 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,900 [classy] Re-using computed results
 2023-07-02 10:34:49,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,900 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,900 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5004772375468736, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,900 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,919 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85343
 2023-07-02 10:34:49,919 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,919 [mcmc] New sample, #864:
   Omega_m:0.312788, b1:0.5124982
 2023-07-02 10:34:49,919 [model] Posterior to be computed for parameters {'Omega_m': 0.3475050559084089, 'b1': 0.4387368374052543}
 2023-07-02 10:34:49,919 [prior] Evaluating prior at array([0.34750506, 0.43873684])
 2023-07-02 10:34:49,919 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,919 [model] Got input parameters: {'Omega_m': 0.3475050559084089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4387368374052543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,919 [classy] Got parameters {'Omega_m': 0.3475050559084089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,919 [classy] Computing new state
 2023-07-02 10:34:49,919 [classy] Setting parameters: {'Omega_m': 0.3475050559084089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:49,965 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.24411330120034}
 2023-07-02 10:34:49,965 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:49,967 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.069328
 2023-07-02 10:34:49,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4387368374052543, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,967 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:49,987 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.21405
 2023-07-02 10:34:49,988 [model] Computed derived parameters: {}
 2023-07-02 10:34:49,988 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.49367629884032677}
 2023-07-02 10:34:49,988 [prior] Evaluating prior at array([0.31278804, 0.4936763 ])
 2023-07-02 10:34:49,988 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:49,988 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49367629884032677, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,988 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:49,988 [classy] Re-using computed results
 2023-07-02 10:34:49,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:49,988 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:49,988 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49367629884032677, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:49,988 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58987
 2023-07-02 10:34:50,007 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,007 [mcmc] New sample, #865:
   Omega_m:0.312788, b1:0.5004772
 2023-07-02 10:34:50,008 [model] Posterior to be computed for parameters {'Omega_m': 0.27391495127361065, 'b1': 0.5628078358313796}
 2023-07-02 10:34:50,008 [prior] Evaluating prior at array([0.27391495, 0.56280784])
 2023-07-02 10:34:50,008 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,008 [model] Got input parameters: {'Omega_m': 0.27391495127361065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5628078358313796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,008 [classy] Got parameters {'Omega_m': 0.27391495127361065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,008 [classy] Computing new state
 2023-07-02 10:34:50,008 [classy] Setting parameters: {'Omega_m': 0.27391495127361065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.1729421040516}
 2023-07-02 10:34:50,054 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,056 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.100986
 2023-07-02 10:34:50,056 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5628078358313796, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,056 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,075 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.82013
 2023-07-02 10:34:50,075 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,076 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5304375458353453}
 2023-07-02 10:34:50,076 [prior] Evaluating prior at array([0.31278804, 0.53043755])
 2023-07-02 10:34:50,076 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,076 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5304375458353453, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,076 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,076 [classy] Re-using computed results
 2023-07-02 10:34:50,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:50,076 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,076 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5304375458353453, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,076 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,096 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.0168
 2023-07-02 10:34:50,096 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,096 [model] Posterior to be computed for parameters {'Omega_m': 0.2924143879655001, 'b1': 0.5299086148322296}
 2023-07-02 10:34:50,096 [prior] Evaluating prior at array([0.29241439, 0.52990861])
 2023-07-02 10:34:50,097 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,097 [model] Got input parameters: {'Omega_m': 0.2924143879655001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5299086148322296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,097 [classy] Got parameters {'Omega_m': 0.2924143879655001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,097 [classy] Computing new state
 2023-07-02 10:34:50,097 [classy] Setting parameters: {'Omega_m': 0.2924143879655001, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,145 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.74627076601556}
 2023-07-02 10:34:50,145 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,147 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0261923
 2023-07-02 10:34:50,147 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5299086148322296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,147 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,167 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.623396
 2023-07-02 10:34:50,167 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,167 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.4649819660309183}
 2023-07-02 10:34:50,167 [prior] Evaluating prior at array([0.31278804, 0.46498197])
 2023-07-02 10:34:50,167 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,167 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4649819660309183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,167 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,167 [classy] Re-using computed results
 2023-07-02 10:34:50,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
 2023-07-02 10:34:50,167 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4649819660309183, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,167 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,187 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.11623
 2023-07-02 10:34:50,188 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,188 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.4732073944825221}
 2023-07-02 10:34:50,188 [prior] Evaluating prior at array([0.32429784, 0.47320739])
 2023-07-02 10:34:50,188 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,188 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4732073944825221, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,188 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,188 [classy] Computing new state
 2023-07-02 10:34:50,188 [classy] Setting parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
 2023-07-02 10:34:50,234 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,236 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0085151
 2023-07-02 10:34:50,236 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4732073944825221, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,236 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.19418
 2023-07-02 10:34:50,256 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,256 [mcmc] New sample, #866:
   Omega_m:0.312788, b1:0.4936763
 2023-07-02 10:34:50,256 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.44930415750401115}
 2023-07-02 10:34:50,256 [prior] Evaluating prior at array([0.32429784, 0.44930416])
 2023-07-02 10:34:50,256 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,256 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44930415750401115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,256 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,256 [classy] Re-using computed results
 2023-07-02 10:34:50,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
 2023-07-02 10:34:50,256 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,256 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44930415750401115, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,256 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,276 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.589511
 2023-07-02 10:34:50,276 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,276 [model] Posterior to be computed for parameters {'Omega_m': 0.3283702970302716, 'b1': 0.46596497058786845}
 2023-07-02 10:34:50,276 [prior] Evaluating prior at array([0.3283703 , 0.46596497])
 2023-07-02 10:34:50,276 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,276 [model] Got input parameters: {'Omega_m': 0.3283702970302716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46596497058786845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,276 [classy] Got parameters {'Omega_m': 0.3283702970302716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,276 [classy] Computing new state
 2023-07-02 10:34:50,276 [classy] Setting parameters: {'Omega_m': 0.3283702970302716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39058145608325}
 2023-07-02 10:34:50,322 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150874
 2023-07-02 10:34:50,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46596497058786845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,324 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,344 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7257
 2023-07-02 10:34:50,344 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,344 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.4349136595346737}
 2023-07-02 10:34:50,345 [prior] Evaluating prior at array([0.32429784, 0.43491366])
 2023-07-02 10:34:50,345 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,345 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4349136595346737, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,345 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,345 [classy] Re-using computed results
 2023-07-02 10:34:50,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
 2023-07-02 10:34:50,345 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4349136595346737, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,345 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,364 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.62655
 2023-07-02 10:34:50,364 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,365 [model] Posterior to be computed for parameters {'Omega_m': 0.37529454787122135, 'b1': 0.3825153323990051}
 2023-07-02 10:34:50,365 [prior] Evaluating prior at array([0.37529455, 0.38251533])
 2023-07-02 10:34:50,365 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,365 [model] Got input parameters: {'Omega_m': 0.37529454787122135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3825153323990051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,365 [classy] Got parameters {'Omega_m': 0.37529454787122135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,365 [classy] Computing new state
 2023-07-02 10:34:50,365 [classy] Setting parameters: {'Omega_m': 0.37529454787122135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.3123876785926}
 2023-07-02 10:34:50,412 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.208937
 2023-07-02 10:34:50,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3825153323990051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,413 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,434 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.0468
 2023-07-02 10:34:50,434 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,434 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.3486853498920322}
 2023-07-02 10:34:50,434 [prior] Evaluating prior at array([0.32429784, 0.34868535])
 2023-07-02 10:34:50,434 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,434 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3486853498920322, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,434 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,434 [classy] Re-using computed results
 2023-07-02 10:34:50,434 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
 2023-07-02 10:34:50,434 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3486853498920322, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,434 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,454 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.5337
 2023-07-02 10:34:50,454 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,454 [model] Posterior to be computed for parameters {'Omega_m': 0.3184759319320715, 'b1': 0.48356101469631824}
 2023-07-02 10:34:50,454 [prior] Evaluating prior at array([0.31847593, 0.48356101])
 2023-07-02 10:34:50,454 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,454 [model] Got input parameters: {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48356101469631824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,454 [classy] Got parameters {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,454 [classy] Computing new state
 2023-07-02 10:34:50,454 [classy] Setting parameters: {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,501 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54522057195416}
 2023-07-02 10:34:50,501 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,503 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00237144
 2023-07-02 10:34:50,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48356101469631824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,503 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,522 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5731
 2023-07-02 10:34:50,522 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,522 [mcmc] New sample, #867:
   Omega_m:0.3242978, b1:0.4732074
 2023-07-02 10:34:50,522 [model] Posterior to be computed for parameters {'Omega_m': 0.3184759319320715, 'b1': 0.4254161575553489}
 2023-07-02 10:34:50,523 [prior] Evaluating prior at array([0.31847593, 0.42541616])
 2023-07-02 10:34:50,523 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,523 [model] Got input parameters: {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4254161575553489, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,523 [classy] Got parameters {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,523 [classy] Re-using computed results
 2023-07-02 10:34:50,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54522057195416}
 2023-07-02 10:34:50,523 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,523 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4254161575553489, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,523 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,543 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.01279
 2023-07-02 10:34:50,543 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,543 [model] Posterior to be computed for parameters {'Omega_m': 0.31194231564120145, 'b1': 0.49518033531980626}
 2023-07-02 10:34:50,543 [prior] Evaluating prior at array([0.31194232, 0.49518034])
 2023-07-02 10:34:50,543 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,543 [model] Got input parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49518033531980626, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,543 [classy] Got parameters {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,543 [classy] Computing new state
 2023-07-02 10:34:50,543 [classy] Setting parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.32535922724134}
 2023-07-02 10:34:50,590 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,592 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000220381
 2023-07-02 10:34:50,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49518033531980626, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,592 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,611 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56095
 2023-07-02 10:34:50,611 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,612 [mcmc] New sample, #868:
   Omega_m:0.3184759, b1:0.483561
 2023-07-02 10:34:50,612 [model] Posterior to be computed for parameters {'Omega_m': 0.31194231564120145, 'b1': 0.47984393237723777}
 2023-07-02 10:34:50,612 [prior] Evaluating prior at array([0.31194232, 0.47984393])
 2023-07-02 10:34:50,612 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,612 [model] Got input parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47984393237723777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,612 [classy] Got parameters {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,612 [classy] Re-using computed results
 2023-07-02 10:34:50,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.32535922724134}
 2023-07-02 10:34:50,612 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47984393237723777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,612 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,631 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08874
 2023-07-02 10:34:50,631 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,631 [model] Posterior to be computed for parameters {'Omega_m': 0.29189744042169186, 'b1': 0.5308279493920852}
 2023-07-02 10:34:50,631 [prior] Evaluating prior at array([0.29189744, 0.53082795])
 2023-07-02 10:34:50,631 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,631 [model] Got input parameters: {'Omega_m': 0.29189744042169186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308279493920852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,631 [classy] Got parameters {'Omega_m': 0.29189744042169186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,631 [classy] Computing new state
 2023-07-02 10:34:50,631 [classy] Setting parameters: {'Omega_m': 0.29189744042169186, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.81225810598522}
 2023-07-02 10:34:50,678 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,680 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0275851
 2023-07-02 10:34:50,680 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308279493920852, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,680 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.778829
 2023-07-02 10:34:50,700 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,700 [model] Posterior to be computed for parameters {'Omega_m': 0.31194231564120145, 'b1': 0.5045528280411137}
 2023-07-02 10:34:50,700 [prior] Evaluating prior at array([0.31194232, 0.50455283])
 2023-07-02 10:34:50,700 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,700 [model] Got input parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5045528280411137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,700 [classy] Got parameters {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,700 [classy] Re-using computed results
 2023-07-02 10:34:50,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.32535922724134}
 2023-07-02 10:34:50,700 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,700 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5045528280411137, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,700 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.86168
 2023-07-02 10:34:50,720 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,720 [mcmc] New sample, #869:
   Omega_m:0.3119423, b1:0.4951803
 2023-07-02 10:34:50,720 [model] Posterior to be computed for parameters {'Omega_m': 0.32034435365527164, 'b1': 0.4896107241234661}
 2023-07-02 10:34:50,720 [prior] Evaluating prior at array([0.32034435, 0.48961072])
 2023-07-02 10:34:50,720 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,720 [model] Got input parameters: {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4896107241234661, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,720 [classy] Got parameters {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,720 [classy] Computing new state
 2023-07-02 10:34:50,720 [classy] Setting parameters: {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32475374421782}
 2023-07-02 10:34:50,767 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,768 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00391791
 2023-07-02 10:34:50,768 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4896107241234661, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,769 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,789 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77776
 2023-07-02 10:34:50,789 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,789 [mcmc] New sample, #870:
   Omega_m:0.3119423, b1:0.5045528
 2023-07-02 10:34:50,789 [model] Posterior to be computed for parameters {'Omega_m': 0.32034435365527164, 'b1': 0.48300111674847046}
 2023-07-02 10:34:50,789 [prior] Evaluating prior at array([0.32034435, 0.48300112])
 2023-07-02 10:34:50,789 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,789 [model] Got input parameters: {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48300111674847046, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,790 [classy] Got parameters {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,790 [classy] Re-using computed results
 2023-07-02 10:34:50,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32475374421782}
 2023-07-02 10:34:50,790 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48300111674847046, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,790 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,809 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62343
 2023-07-02 10:34:50,809 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,809 [mcmc] New sample, #871:
   Omega_m:0.3203444, b1:0.4896107
 2023-07-02 10:34:50,809 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.5076797904788257}
 2023-07-02 10:34:50,809 [prior] Evaluating prior at array([0.30646738, 0.50767979])
 2023-07-02 10:34:50,809 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,809 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5076797904788257, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,809 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,809 [classy] Computing new state
 2023-07-02 10:34:50,809 [classy] Setting parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
 2023-07-02 10:34:50,856 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,858 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00245598
 2023-07-02 10:34:50,858 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5076797904788257, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,858 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,877 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30606
 2023-07-02 10:34:50,877 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,877 [mcmc] New sample, #872:
   Omega_m:0.3203444, b1:0.4830011
 2023-07-02 10:34:50,877 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.4799370928629178}
 2023-07-02 10:34:50,878 [prior] Evaluating prior at array([0.30646738, 0.47993709])
 2023-07-02 10:34:50,878 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,878 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4799370928629178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,878 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,878 [classy] Re-using computed results
 2023-07-02 10:34:50,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
 2023-07-02 10:34:50,878 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4799370928629178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,878 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.84183
 2023-07-02 10:34:50,899 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,899 [model] Posterior to be computed for parameters {'Omega_m': 0.29940509720019226, 'b1': 0.5202392898424413}
 2023-07-02 10:34:50,899 [prior] Evaluating prior at array([0.2994051 , 0.52023929])
 2023-07-02 10:34:50,899 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,899 [model] Got input parameters: {'Omega_m': 0.29940509720019226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5202392898424413, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,899 [classy] Got parameters {'Omega_m': 0.29940509720019226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,899 [classy] Computing new state
 2023-07-02 10:34:50,899 [classy] Setting parameters: {'Omega_m': 0.29940509720019226, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:50,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.86373232653347}
 2023-07-02 10:34:50,947 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:50,949 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0110428
 2023-07-02 10:34:50,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5202392898424413, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,949 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,968 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24252
 2023-07-02 10:34:50,968 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,968 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.5230224082872564}
 2023-07-02 10:34:50,968 [prior] Evaluating prior at array([0.30646738, 0.52302241])
 2023-07-02 10:34:50,968 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,968 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5230224082872564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,968 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,968 [classy] Re-using computed results
 2023-07-02 10:34:50,968 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
 2023-07-02 10:34:50,969 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:50,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5230224082872564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,969 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:50,988 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.344
 2023-07-02 10:34:50,988 [model] Computed derived parameters: {}
 2023-07-02 10:34:50,988 [mcmc] New sample, #873:
   Omega_m:0.3064674, b1:0.5076798
 2023-07-02 10:34:50,988 [model] Posterior to be computed for parameters {'Omega_m': 0.335779528895641, 'b1': 0.4708939667693149}
 2023-07-02 10:34:50,988 [prior] Evaluating prior at array([0.33577953, 0.47089397])
 2023-07-02 10:34:50,988 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:50,988 [model] Got input parameters: {'Omega_m': 0.335779528895641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4708939667693149, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:50,989 [classy] Got parameters {'Omega_m': 0.335779528895641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:50,989 [classy] Computing new state
 2023-07-02 10:34:50,989 [classy] Setting parameters: {'Omega_m': 0.335779528895641, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,035 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.54631334883643}
 2023-07-02 10:34:51,035 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,036 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0316446
 2023-07-02 10:34:51,036 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4708939667693149, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,036 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,056 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.556748
 2023-07-02 10:34:51,056 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,056 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.32869995619410863}
 2023-07-02 10:34:51,057 [prior] Evaluating prior at array([0.30646738, 0.32869996])
 2023-07-02 10:34:51,057 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,057 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.32869995619410863, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,057 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,057 [classy] Re-using computed results
 2023-07-02 10:34:51,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
 2023-07-02 10:34:51,057 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.32869995619410863, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,057 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,076 [fs_likelihood.fslikelihood] Computed log-likelihood = -74.769
 2023-07-02 10:34:51,076 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,076 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.515106842159031}
 2023-07-02 10:34:51,077 [prior] Evaluating prior at array([0.31091835, 0.51510684])
 2023-07-02 10:34:51,077 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,077 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.515106842159031, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,077 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,077 [classy] Computing new state
 2023-07-02 10:34:51,077 [classy] Setting parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
 2023-07-02 10:34:51,125 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,127 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00035328
 2023-07-02 10:34:51,127 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.515106842159031, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,127 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,148 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67617
 2023-07-02 10:34:51,148 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,148 [mcmc] New sample, #874:
   Omega_m:0.3064674, b1:0.5230224
 2023-07-02 10:34:51,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5337541208645746}
 2023-07-02 10:34:51,148 [prior] Evaluating prior at array([0.31091835, 0.53375412])
 2023-07-02 10:34:51,149 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,149 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5337541208645746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,149 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,149 [classy] Re-using computed results
 2023-07-02 10:34:51,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
 2023-07-02 10:34:51,149 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5337541208645746, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,149 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,168 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.960011
 2023-07-02 10:34:51,168 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,168 [model] Posterior to be computed for parameters {'Omega_m': 0.3260733796335274, 'b1': 0.48815528963786536}
 2023-07-02 10:34:51,168 [prior] Evaluating prior at array([0.32607338, 0.48815529])
 2023-07-02 10:34:51,168 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,168 [model] Got input parameters: {'Omega_m': 0.3260733796335274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48815528963786536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,169 [classy] Got parameters {'Omega_m': 0.3260733796335274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,169 [classy] Computing new state
 2023-07-02 10:34:51,169 [classy] Setting parameters: {'Omega_m': 0.3260733796335274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6558258426254}
 2023-07-02 10:34:51,215 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,217 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111544
 2023-07-02 10:34:51,217 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48815528963786536, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,217 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,237 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11985
 2023-07-02 10:34:51,237 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,237 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5204648931496998}
 2023-07-02 10:34:51,237 [prior] Evaluating prior at array([0.31091835, 0.52046489])
 2023-07-02 10:34:51,237 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,237 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204648931496998, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,237 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,237 [classy] Re-using computed results
 2023-07-02 10:34:51,237 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
 2023-07-02 10:34:51,237 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204648931496998, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,237 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,257 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38318
 2023-07-02 10:34:51,257 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,257 [mcmc] New sample, #875:
   Omega_m:0.3109184, b1:0.5151068
 2023-07-02 10:34:51,257 [model] Posterior to be computed for parameters {'Omega_m': 0.3317925299787476, 'b1': 0.48334245844068585}
 2023-07-02 10:34:51,257 [prior] Evaluating prior at array([0.33179253, 0.48334246])
 2023-07-02 10:34:51,258 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,258 [model] Got input parameters: {'Omega_m': 0.3317925299787476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48334245844068585, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,258 [classy] Got parameters {'Omega_m': 0.3317925299787476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,258 [classy] Computing new state
 2023-07-02 10:34:51,258 [classy] Setting parameters: {'Omega_m': 0.3317925299787476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99850419625255}
 2023-07-02 10:34:51,304 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0220104
 2023-07-02 10:34:51,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48334245844068585, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,306 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,325 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.981671
 2023-07-02 10:34:51,325 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,325 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5518290624267989}
 2023-07-02 10:34:51,325 [prior] Evaluating prior at array([0.31091835, 0.55182906])
 2023-07-02 10:34:51,326 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,326 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5518290624267989, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,326 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,326 [classy] Re-using computed results
 2023-07-02 10:34:51,326 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
 2023-07-02 10:34:51,326 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5518290624267989, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,326 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,345 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.62673
 2023-07-02 10:34:51,345 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,345 [model] Posterior to be computed for parameters {'Omega_m': 0.2835587674577083, 'b1': 0.5691209196570699}
 2023-07-02 10:34:51,345 [prior] Evaluating prior at array([0.28355877, 0.56912092])
 2023-07-02 10:34:51,345 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,345 [model] Got input parameters: {'Omega_m': 0.2835587674577083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5691209196570699, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,345 [classy] Got parameters {'Omega_m': 0.2835587674577083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,345 [classy] Computing new state
 2023-07-02 10:34:51,345 [classy] Setting parameters: {'Omega_m': 0.2835587674577083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.890900636314}
 2023-07-02 10:34:51,391 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,393 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0554505
 2023-07-02 10:34:51,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5691209196570699, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,393 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,413 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.86163
 2023-07-02 10:34:51,413 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,413 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5367523790998252}
 2023-07-02 10:34:51,413 [prior] Evaluating prior at array([0.31091835, 0.53675238])
 2023-07-02 10:34:51,413 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,413 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5367523790998252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,413 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,413 [classy] Re-using computed results
 2023-07-02 10:34:51,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
 2023-07-02 10:34:51,413 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5367523790998252, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,413 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.498753
 2023-07-02 10:34:51,433 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,433 [mcmc] New sample, #876:
   Omega_m:0.3109184, b1:0.5204649
 2023-07-02 10:34:51,433 [model] Posterior to be computed for parameters {'Omega_m': 0.32983433562972986, 'b1': 0.503112378462756}
 2023-07-02 10:34:51,433 [prior] Evaluating prior at array([0.32983434, 0.50311238])
 2023-07-02 10:34:51,433 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,433 [model] Got input parameters: {'Omega_m': 0.32983433562972986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.503112378462756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,433 [classy] Got parameters {'Omega_m': 0.32983433562972986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,433 [classy] Computing new state
 2023-07-02 10:34:51,433 [classy] Setting parameters: {'Omega_m': 0.32983433562972986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.22238971413995}
 2023-07-02 10:34:51,479 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.017895
 2023-07-02 10:34:51,481 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.503112378462756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,481 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,501 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.683055
 2023-07-02 10:34:51,501 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,501 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5505698677772729}
 2023-07-02 10:34:51,501 [prior] Evaluating prior at array([0.31091835, 0.55056987])
 2023-07-02 10:34:51,502 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,502 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5505698677772729, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,502 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,502 [classy] Re-using computed results
 2023-07-02 10:34:51,502 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
 2023-07-02 10:34:51,502 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,502 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5505698677772729, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,502 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,521 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.3134
 2023-07-02 10:34:51,521 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,521 [model] Posterior to be computed for parameters {'Omega_m': 0.3316552063934932, 'b1': 0.49987415933934853}
 2023-07-02 10:34:51,521 [prior] Evaluating prior at array([0.33165521, 0.49987416])
 2023-07-02 10:34:51,521 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,522 [model] Got input parameters: {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49987415933934853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,522 [classy] Got parameters {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,522 [classy] Computing new state
 2023-07-02 10:34:51,522 [classy] Setting parameters: {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01416726445314}
 2023-07-02 10:34:51,568 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,570 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0217084
 2023-07-02 10:34:51,570 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49987415933934853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,570 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,590 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.9848
 2023-07-02 10:34:51,591 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,591 [mcmc] New sample, #877:
   Omega_m:0.3109184, b1:0.5367524
 2023-07-02 10:34:51,591 [model] Posterior to be computed for parameters {'Omega_m': 0.3316552063934932, 'b1': 0.5312188375611868}
 2023-07-02 10:34:51,591 [prior] Evaluating prior at array([0.33165521, 0.53121884])
 2023-07-02 10:34:51,591 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,591 [model] Got input parameters: {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5312188375611868, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,591 [classy] Got parameters {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,591 [classy] Re-using computed results
 2023-07-02 10:34:51,591 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01416726445314}
 2023-07-02 10:34:51,591 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5312188375611868, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,591 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,612 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.34238
 2023-07-02 10:34:51,612 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,612 [model] Posterior to be computed for parameters {'Omega_m': 0.2948252983944829, 'b1': 0.5653721149159651}
 2023-07-02 10:34:51,612 [prior] Evaluating prior at array([0.2948253 , 0.56537211])
 2023-07-02 10:34:51,612 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,612 [model] Got input parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5653721149159651, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,612 [classy] Got parameters {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,612 [classy] Computing new state
 2023-07-02 10:34:51,612 [classy] Setting parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43985515983607}
 2023-07-02 10:34:51,660 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0201984
 2023-07-02 10:34:51,662 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5653721149159651, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,662 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,681 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.80343
 2023-07-02 10:34:51,681 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,682 [mcmc] New sample, #878:
   Omega_m:0.3316552, b1:0.4998742
 2023-07-02 10:34:51,682 [model] Posterior to be computed for parameters {'Omega_m': 0.2948252983944829, 'b1': 0.5754975114682691}
 2023-07-02 10:34:51,682 [prior] Evaluating prior at array([0.2948253 , 0.57549751])
 2023-07-02 10:34:51,682 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,682 [model] Got input parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5754975114682691, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,682 [classy] Got parameters {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,682 [classy] Re-using computed results
 2023-07-02 10:34:51,682 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43985515983607}
 2023-07-02 10:34:51,682 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,682 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5754975114682691, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,682 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,703 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.68344
 2023-07-02 10:34:51,703 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,703 [mcmc] New sample, #879:
   Omega_m:0.2948253, b1:0.5653721
 2023-07-02 10:34:51,704 [model] Posterior to be computed for parameters {'Omega_m': 0.2770632919865319, 'b1': 0.6070852935146108}
 2023-07-02 10:34:51,704 [prior] Evaluating prior at array([0.27706329, 0.60708529])
 2023-07-02 10:34:51,704 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,704 [model] Got input parameters: {'Omega_m': 0.2770632919865319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6070852935146108, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,704 [classy] Got parameters {'Omega_m': 0.2770632919865319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,704 [classy] Computing new state
 2023-07-02 10:34:51,704 [classy] Setting parameters: {'Omega_m': 0.2770632919865319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.7502327164867}
 2023-07-02 10:34:51,752 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0844906
 2023-07-02 10:34:51,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6070852935146108, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,754 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,774 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.5364
 2023-07-02 10:34:51,774 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,774 [model] Posterior to be computed for parameters {'Omega_m': 0.2948252983944829, 'b1': 0.6087068627802504}
 2023-07-02 10:34:51,774 [prior] Evaluating prior at array([0.2948253 , 0.60870686])
 2023-07-02 10:34:51,774 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,774 [model] Got input parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6087068627802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,774 [classy] Got parameters {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,774 [classy] Re-using computed results
 2023-07-02 10:34:51,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43985515983607}
 2023-07-02 10:34:51,774 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6087068627802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,774 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.188
 2023-07-02 10:34:51,794 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,794 [model] Posterior to be computed for parameters {'Omega_m': 0.2967585881085531, 'b1': 0.5720593675605433}
 2023-07-02 10:34:51,794 [prior] Evaluating prior at array([0.29675859, 0.57205937])
 2023-07-02 10:34:51,794 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,794 [model] Got input parameters: {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5720593675605433, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,794 [classy] Got parameters {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,794 [classy] Computing new state
 2023-07-02 10:34:51,794 [classy] Setting parameters: {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19571116875585}
 2023-07-02 10:34:51,840 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159809
 2023-07-02 10:34:51,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5720593675605433, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,842 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,862 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.23095
 2023-07-02 10:34:51,862 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,862 [mcmc] New sample, #880:
   Omega_m:0.2948253, b1:0.5754975
 2023-07-02 10:34:51,862 [mcmc] Learn + convergence test @ 880 samples accepted.
 2023-07-02 10:34:51,862 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:34:51,867 [mcmc]  - Acceptance rate: 0.467
 2023-07-02 10:34:51,868 [mcmc]  - Condition number = 4.08571
 2023-07-02 10:34:51,868 [mcmc]  - Eigenvalues = array([0.01281207, 0.05234644])
 2023-07-02 10:34:51,868 [mcmc]  - Convergence of means: R-1 = 0.052346 after 704 accepted steps
 2023-07-02 10:34:51,868 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:34:51,868 [mcmc] array([[ 0.00010232, -0.00018647],
       [-0.00018647,  0.00051157]])
 2023-07-02 10:34:51,878 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:34:51,878 [model] Posterior to be computed for parameters {'Omega_m': 0.2967585881085531, 'b1': 0.5846613514000003}
 2023-07-02 10:34:51,878 [prior] Evaluating prior at array([0.29675859, 0.58466135])
 2023-07-02 10:34:51,878 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,879 [model] Got input parameters: {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5846613514000003, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,879 [classy] Got parameters {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,879 [classy] Re-using computed results
 2023-07-02 10:34:51,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19571116875585}
 2023-07-02 10:34:51,879 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,879 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5846613514000003, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,879 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.43016
 2023-07-02 10:34:51,899 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,899 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5328427642645573}
 2023-07-02 10:34:51,899 [prior] Evaluating prior at array([0.31827729, 0.53284276])
 2023-07-02 10:34:51,899 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,899 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5328427642645573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,899 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,899 [classy] Computing new state
 2023-07-02 10:34:51,899 [classy] Setting parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:51,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:51,946 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:51,948 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00223099
 2023-07-02 10:34:51,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5328427642645573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,948 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,968 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.27948
 2023-07-02 10:34:51,968 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,969 [mcmc] New sample, #881:
   Omega_m:0.2967586, b1:0.5720594
 2023-07-02 10:34:51,969 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5719230546284122}
 2023-07-02 10:34:51,969 [prior] Evaluating prior at array([0.31827729, 0.57192305])
 2023-07-02 10:34:51,969 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,969 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5719230546284122, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,969 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,969 [classy] Re-using computed results
 2023-07-02 10:34:51,969 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:51,969 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:51,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5719230546284122, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,969 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:51,989 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.6806
 2023-07-02 10:34:51,989 [model] Computed derived parameters: {}
 2023-07-02 10:34:51,990 [model] Posterior to be computed for parameters {'Omega_m': 0.2879182248381604, 'b1': 0.588170423541527}
 2023-07-02 10:34:51,990 [prior] Evaluating prior at array([0.28791822, 0.58817042])
 2023-07-02 10:34:51,990 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:51,990 [model] Got input parameters: {'Omega_m': 0.2879182248381604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.588170423541527, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:51,990 [classy] Got parameters {'Omega_m': 0.2879182248381604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:51,990 [classy] Computing new state
 2023-07-02 10:34:51,990 [classy] Setting parameters: {'Omega_m': 0.2879182248381604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.32360100871247}
 2023-07-02 10:34:52,038 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0395984
 2023-07-02 10:34:52,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.588170423541527, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,059 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.83372
 2023-07-02 10:34:52,059 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,060 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5387781227804908}
 2023-07-02 10:34:52,060 [prior] Evaluating prior at array([0.31827729, 0.53877812])
 2023-07-02 10:34:52,060 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,060 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5387781227804908, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,060 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,060 [classy] Re-using computed results
 2023-07-02 10:34:52,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:52,060 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5387781227804908, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,060 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,079 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.69368
 2023-07-02 10:34:52,079 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,080 [model] Posterior to be computed for parameters {'Omega_m': 0.3461076069084337, 'b1': 0.48212360585330116}
 2023-07-02 10:34:52,080 [prior] Evaluating prior at array([0.34610761, 0.48212361])
 2023-07-02 10:34:52,080 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,080 [model] Got input parameters: {'Omega_m': 0.3461076069084337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48212360585330116, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,080 [classy] Got parameters {'Omega_m': 0.3461076069084337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,080 [classy] Computing new state
 2023-07-02 10:34:52,080 [classy] Setting parameters: {'Omega_m': 0.3461076069084337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.39717723543535}
 2023-07-02 10:34:52,128 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,129 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0641302
 2023-07-02 10:34:52,130 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48212360585330116, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,130 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.948
 2023-07-02 10:34:52,150 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,150 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5118301076782446}
 2023-07-02 10:34:52,150 [prior] Evaluating prior at array([0.31827729, 0.51183011])
 2023-07-02 10:34:52,150 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,150 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5118301076782446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,150 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,151 [classy] Re-using computed results
 2023-07-02 10:34:52,151 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:52,151 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,151 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5118301076782446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,151 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,170 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03772
 2023-07-02 10:34:52,170 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,170 [mcmc] New sample, #882:
   Omega_m:0.3182773, b1:0.5328428
 2023-07-02 10:34:52,171 [model] Posterior to be computed for parameters {'Omega_m': 0.3534531305298964, 'b1': 0.44772415297193446}
 2023-07-02 10:34:52,171 [prior] Evaluating prior at array([0.35345313, 0.44772415])
 2023-07-02 10:34:52,171 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,171 [model] Got input parameters: {'Omega_m': 0.3534531305298964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44772415297193446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,171 [classy] Got parameters {'Omega_m': 0.3534531305298964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,171 [classy] Computing new state
 2023-07-02 10:34:52,171 [classy] Setting parameters: {'Omega_m': 0.3534531305298964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.59884333768574}
 2023-07-02 10:34:52,222 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,224 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0935062
 2023-07-02 10:34:52,224 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44772415297193446, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,224 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,245 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.86988
 2023-07-02 10:34:52,245 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,245 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5500257086953573}
 2023-07-02 10:34:52,245 [prior] Evaluating prior at array([0.31827729, 0.55002571])
 2023-07-02 10:34:52,245 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,245 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5500257086953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,246 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,246 [classy] Re-using computed results
 2023-07-02 10:34:52,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:52,246 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,246 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5500257086953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,246 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.97142
 2023-07-02 10:34:52,265 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,266 [model] Posterior to be computed for parameters {'Omega_m': 0.35557786077738746, 'b1': 0.4438519537291202}
 2023-07-02 10:34:52,266 [prior] Evaluating prior at array([0.35557786, 0.44385195])
 2023-07-02 10:34:52,266 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,266 [model] Got input parameters: {'Omega_m': 0.35557786077738746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4438519537291202, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,266 [classy] Got parameters {'Omega_m': 0.35557786077738746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,266 [classy] Computing new state
 2023-07-02 10:34:52,266 [classy] Setting parameters: {'Omega_m': 0.35557786077738746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.37075170847373}
 2023-07-02 10:34:52,312 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102932
 2023-07-02 10:34:52,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4438519537291202, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,314 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,334 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.59243
 2023-07-02 10:34:52,334 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,334 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.516352990443558}
 2023-07-02 10:34:52,334 [prior] Evaluating prior at array([0.31827729, 0.51635299])
 2023-07-02 10:34:52,334 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,334 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.516352990443558, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,334 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,334 [classy] Re-using computed results
 2023-07-02 10:34:52,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:52,334 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.516352990443558, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,334 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,354 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54148
 2023-07-02 10:34:52,354 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,354 [model] Posterior to be computed for parameters {'Omega_m': 0.32501277085589864, 'b1': 0.4995550803685114}
 2023-07-02 10:34:52,354 [prior] Evaluating prior at array([0.32501277, 0.49955508])
 2023-07-02 10:34:52,354 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,354 [model] Got input parameters: {'Omega_m': 0.32501277085589864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4995550803685114, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,354 [classy] Got parameters {'Omega_m': 0.32501277085589864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,354 [classy] Computing new state
 2023-07-02 10:34:52,354 [classy] Setting parameters: {'Omega_m': 0.32501277085589864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.77886749293197}
 2023-07-02 10:34:52,400 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,402 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00953545
 2023-07-02 10:34:52,403 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4995550803685114, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,403 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,422 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57091
 2023-07-02 10:34:52,422 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,423 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.529329728986742}
 2023-07-02 10:34:52,423 [prior] Evaluating prior at array([0.31827729, 0.52932973])
 2023-07-02 10:34:52,423 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,423 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.529329728986742, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,423 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,423 [classy] Re-using computed results
 2023-07-02 10:34:52,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:52,423 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.529329728986742, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,423 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.543121
 2023-07-02 10:34:52,443 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,443 [model] Posterior to be computed for parameters {'Omega_m': 0.33286101012784636, 'b1': 0.48525211357912873}
 2023-07-02 10:34:52,443 [prior] Evaluating prior at array([0.33286101, 0.48525211])
 2023-07-02 10:34:52,443 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,443 [model] Got input parameters: {'Omega_m': 0.33286101012784636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48525211357912873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,443 [classy] Got parameters {'Omega_m': 0.33286101012784636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,443 [classy] Computing new state
 2023-07-02 10:34:52,443 [classy] Setting parameters: {'Omega_m': 0.33286101012784636, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.87684153923635}
 2023-07-02 10:34:52,490 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244285
 2023-07-02 10:34:52,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48525211357912873, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,492 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,511 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.465894
 2023-07-02 10:34:52,511 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,511 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5282730126817755}
 2023-07-02 10:34:52,511 [prior] Evaluating prior at array([0.31827729, 0.52827301])
 2023-07-02 10:34:52,512 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,512 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282730126817755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,512 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,512 [classy] Re-using computed results
 2023-07-02 10:34:52,512 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
 2023-07-02 10:34:52,512 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282730126817755, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,512 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.336129
 2023-07-02 10:34:52,532 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,532 [model] Posterior to be computed for parameters {'Omega_m': 0.31513467306041426, 'b1': 0.5175573481148695}
 2023-07-02 10:34:52,532 [prior] Evaluating prior at array([0.31513467, 0.51755735])
 2023-07-02 10:34:52,532 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,532 [model] Got input parameters: {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5175573481148695, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,532 [classy] Got parameters {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,532 [classy] Computing new state
 2023-07-02 10:34:52,532 [classy] Setting parameters: {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,578 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94235968761083}
 2023-07-02 10:34:52,578 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000630508
 2023-07-02 10:34:52,580 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5175573481148695, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,580 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,600 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09083
 2023-07-02 10:34:52,600 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,600 [mcmc] New sample, #883:
   Omega_m:0.3182773, b1:0.5118301
 2023-07-02 10:34:52,600 [model] Posterior to be computed for parameters {'Omega_m': 0.31513467306041426, 'b1': 0.5200357271667242}
 2023-07-02 10:34:52,600 [prior] Evaluating prior at array([0.31513467, 0.52003573])
 2023-07-02 10:34:52,600 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,600 [model] Got input parameters: {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5200357271667242, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,600 [classy] Got parameters {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,600 [classy] Re-using computed results
 2023-07-02 10:34:52,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94235968761083}
 2023-07-02 10:34:52,600 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,601 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5200357271667242, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,601 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,620 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.83389
 2023-07-02 10:34:52,620 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,620 [model] Posterior to be computed for parameters {'Omega_m': 0.32928631502455363, 'b1': 0.49176679076631846}
 2023-07-02 10:34:52,620 [prior] Evaluating prior at array([0.32928632, 0.49176679])
 2023-07-02 10:34:52,620 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,621 [model] Got input parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49176679076631846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,621 [classy] Got parameters {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,621 [classy] Computing new state
 2023-07-02 10:34:52,621 [classy] Setting parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.28526770007363}
 2023-07-02 10:34:52,667 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0168169
 2023-07-02 10:34:52,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49176679076631846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,669 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,688 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.04037
 2023-07-02 10:34:52,688 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,688 [mcmc] New sample, #884:
   Omega_m:0.3151347, b1:0.5175573
 2023-07-02 10:34:52,688 [model] Posterior to be computed for parameters {'Omega_m': 0.32928631502455363, 'b1': 0.517138542474353}
 2023-07-02 10:34:52,688 [prior] Evaluating prior at array([0.32928632, 0.51713854])
 2023-07-02 10:34:52,688 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,688 [model] Got input parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.517138542474353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,688 [classy] Got parameters {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,688 [classy] Re-using computed results
 2023-07-02 10:34:52,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.28526770007363}
 2023-07-02 10:34:52,688 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.517138542474353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.32211
 2023-07-02 10:34:52,708 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,708 [model] Posterior to be computed for parameters {'Omega_m': 0.35305904080371037, 'b1': 0.44844235893767537}
 2023-07-02 10:34:52,708 [prior] Evaluating prior at array([0.35305904, 0.44844236])
 2023-07-02 10:34:52,708 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,708 [model] Got input parameters: {'Omega_m': 0.35305904080371037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44844235893767537, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,708 [classy] Got parameters {'Omega_m': 0.35305904080371037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,708 [classy] Computing new state
 2023-07-02 10:34:52,708 [classy] Setting parameters: {'Omega_m': 0.35305904080371037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.64128631289478}
 2023-07-02 10:34:52,755 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,757 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0918031
 2023-07-02 10:34:52,757 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44844235893767537, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,757 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,776 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.73904
 2023-07-02 10:34:52,777 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,777 [model] Posterior to be computed for parameters {'Omega_m': 0.32928631502455363, 'b1': 0.5646594716317532}
 2023-07-02 10:34:52,777 [prior] Evaluating prior at array([0.32928632, 0.56465947])
 2023-07-02 10:34:52,777 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,777 [model] Got input parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5646594716317532, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,777 [classy] Got parameters {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,777 [classy] Re-using computed results
 2023-07-02 10:34:52,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.28526770007363}
 2023-07-02 10:34:52,777 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5646594716317532, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,777 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,797 [fs_likelihood.fslikelihood] Computed log-likelihood = -22.4467
 2023-07-02 10:34:52,797 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,797 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.5396716580613085}
 2023-07-02 10:34:52,797 [prior] Evaluating prior at array([0.30300024, 0.53967166])
 2023-07-02 10:34:52,797 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,797 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5396716580613085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,797 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,797 [classy] Computing new state
 2023-07-02 10:34:52,797 [classy] Setting parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
 2023-07-02 10:34:52,843 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00585052
 2023-07-02 10:34:52,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5396716580613085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,845 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,865 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.21389
 2023-07-02 10:34:52,865 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,865 [mcmc] New sample, #885:
   Omega_m:0.3292863, b1:0.4917668
 2023-07-02 10:34:52,865 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.5140877743960656}
 2023-07-02 10:34:52,865 [prior] Evaluating prior at array([0.30300024, 0.51408777])
 2023-07-02 10:34:52,865 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,865 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5140877743960656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,865 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,865 [classy] Re-using computed results
 2023-07-02 10:34:52,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
 2023-07-02 10:34:52,866 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5140877743960656, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,866 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87577
 2023-07-02 10:34:52,885 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,885 [mcmc] New sample, #886:
   Omega_m:0.3030002, b1:0.5396717
 2023-07-02 10:34:52,885 [model] Posterior to be computed for parameters {'Omega_m': 0.2643787637607842, 'b1': 0.5844732035531925}
 2023-07-02 10:34:52,886 [prior] Evaluating prior at array([0.26437876, 0.5844732 ])
 2023-07-02 10:34:52,886 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,886 [model] Got input parameters: {'Omega_m': 0.2643787637607842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5844732035531925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,886 [classy] Got parameters {'Omega_m': 0.2643787637607842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,886 [classy] Computing new state
 2023-07-02 10:34:52,886 [classy] Setting parameters: {'Omega_m': 0.2643787637607842, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:52,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.47905080522912}
 2023-07-02 10:34:52,932 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:52,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.161101
 2023-07-02 10:34:52,934 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5844732035531925, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,934 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,954 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.1574
 2023-07-02 10:34:52,954 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,954 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.4963902373089941}
 2023-07-02 10:34:52,954 [prior] Evaluating prior at array([0.30300024, 0.49639024])
 2023-07-02 10:34:52,954 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,954 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4963902373089941, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,954 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,954 [classy] Re-using computed results
 2023-07-02 10:34:52,954 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
 2023-07-02 10:34:52,954 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:52,954 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4963902373089941, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,954 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:52,974 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.325885
 2023-07-02 10:34:52,974 [model] Computed derived parameters: {}
 2023-07-02 10:34:52,974 [model] Posterior to be computed for parameters {'Omega_m': 0.24727221154979387, 'b1': 0.6156489156685435}
 2023-07-02 10:34:52,974 [prior] Evaluating prior at array([0.24727221, 0.61564892])
 2023-07-02 10:34:52,974 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:52,974 [model] Got input parameters: {'Omega_m': 0.24727221154979387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6156489156685435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:52,974 [classy] Got parameters {'Omega_m': 0.24727221154979387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:52,974 [classy] Computing new state
 2023-07-02 10:34:52,975 [classy] Setting parameters: {'Omega_m': 0.24727221154979387, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,021 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.9243010727541}
 2023-07-02 10:34:53,021 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,023 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.310367
 2023-07-02 10:34:53,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6156489156685435, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,023 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,042 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.5804
 2023-07-02 10:34:53,042 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,043 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.5146332111412649}
 2023-07-02 10:34:53,043 [prior] Evaluating prior at array([0.30300024, 0.51463321])
 2023-07-02 10:34:53,043 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,043 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5146332111412649, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,043 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,043 [classy] Re-using computed results
 2023-07-02 10:34:53,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
 2023-07-02 10:34:53,043 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,043 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5146332111412649, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,043 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,062 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.89811
 2023-07-02 10:34:53,062 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,062 [mcmc] New sample, #887:
   Omega_m:0.3030002, b1:0.5140878
 2023-07-02 10:34:53,062 [model] Posterior to be computed for parameters {'Omega_m': 0.3296837857955315, 'b1': 0.46600397611995353}
 2023-07-02 10:34:53,062 [prior] Evaluating prior at array([0.32968379, 0.46600398])
 2023-07-02 10:34:53,063 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,063 [model] Got input parameters: {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46600397611995353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,063 [classy] Got parameters {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,063 [classy] Computing new state
 2023-07-02 10:34:53,063 [classy] Setting parameters: {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.23965231583597}
 2023-07-02 10:34:53,109 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0175957
 2023-07-02 10:34:53,111 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46600397611995353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,111 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,133 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65461
 2023-07-02 10:34:53,133 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,133 [mcmc] New sample, #888:
   Omega_m:0.3030002, b1:0.5146332
 2023-07-02 10:34:53,133 [model] Posterior to be computed for parameters {'Omega_m': 0.3296837857955315, 'b1': 0.5375794630807906}
 2023-07-02 10:34:53,133 [prior] Evaluating prior at array([0.32968379, 0.53757946])
 2023-07-02 10:34:53,134 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,134 [model] Got input parameters: {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375794630807906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,134 [classy] Got parameters {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,134 [classy] Re-using computed results
 2023-07-02 10:34:53,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.23965231583597}
 2023-07-02 10:34:53,134 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375794630807906, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,134 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,154 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.0594
 2023-07-02 10:34:53,154 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,154 [model] Posterior to be computed for parameters {'Omega_m': 0.31858624224638055, 'b1': 0.4862286139434434}
 2023-07-02 10:34:53,154 [prior] Evaluating prior at array([0.31858624, 0.48622861])
 2023-07-02 10:34:53,154 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,154 [model] Got input parameters: {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4862286139434434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,154 [classy] Got parameters {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,154 [classy] Computing new state
 2023-07-02 10:34:53,154 [classy] Setting parameters: {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53217150926403}
 2023-07-02 10:34:53,200 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00245144
 2023-07-02 10:34:53,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4862286139434434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,202 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,222 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70741
 2023-07-02 10:34:53,222 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,222 [mcmc] New sample, #889:
   Omega_m:0.3296838, b1:0.466004
 2023-07-02 10:34:53,222 [model] Posterior to be computed for parameters {'Omega_m': 0.31858624224638055, 'b1': 0.4379675114368804}
 2023-07-02 10:34:53,222 [prior] Evaluating prior at array([0.31858624, 0.43796751])
 2023-07-02 10:34:53,222 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,223 [model] Got input parameters: {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4379675114368804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,223 [classy] Got parameters {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,223 [classy] Re-using computed results
 2023-07-02 10:34:53,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53217150926403}
 2023-07-02 10:34:53,223 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4379675114368804, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,223 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.11633
 2023-07-02 10:34:53,243 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3056127811406604, 'b1': 0.5098720041241828}
 2023-07-02 10:34:53,243 [prior] Evaluating prior at array([0.30561278, 0.509872  ])
 2023-07-02 10:34:53,243 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,243 [model] Got input parameters: {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5098720041241828, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,243 [classy] Got parameters {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,243 [classy] Computing new state
 2023-07-02 10:34:53,243 [classy] Setting parameters: {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.09508473847453}
 2023-07-02 10:34:53,290 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,291 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00314795
 2023-07-02 10:34:53,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5098720041241828, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,292 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,311 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23957
 2023-07-02 10:34:53,311 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,311 [mcmc] New sample, #890:
   Omega_m:0.3185862, b1:0.4862286
 2023-07-02 10:34:53,311 [model] Posterior to be computed for parameters {'Omega_m': 0.3056127811406604, 'b1': 0.5066862696651205}
 2023-07-02 10:34:53,311 [prior] Evaluating prior at array([0.30561278, 0.50668627])
 2023-07-02 10:34:53,312 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,312 [model] Got input parameters: {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066862696651205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,312 [classy] Got parameters {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,312 [classy] Re-using computed results
 2023-07-02 10:34:53,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.09508473847453}
 2023-07-02 10:34:53,312 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066862696651205, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,312 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,331 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08655
 2023-07-02 10:34:53,332 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,332 [mcmc] New sample, #891:
   Omega_m:0.3056128, b1:0.509872
 2023-07-02 10:34:53,332 [model] Posterior to be computed for parameters {'Omega_m': 0.32905622959646474, 'b1': 0.4639619269083333}
 2023-07-02 10:34:53,332 [prior] Evaluating prior at array([0.32905623, 0.46396193])
 2023-07-02 10:34:53,332 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,332 [model] Got input parameters: {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4639619269083333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,332 [classy] Got parameters {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,332 [classy] Computing new state
 2023-07-02 10:34:53,332 [classy] Setting parameters: {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31169902973238}
 2023-07-02 10:34:53,378 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,380 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163738
 2023-07-02 10:34:53,380 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4639619269083333, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,380 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,400 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58684
 2023-07-02 10:34:53,400 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,400 [mcmc] New sample, #892:
   Omega_m:0.3056128, b1:0.5066863
 2023-07-02 10:34:53,400 [model] Posterior to be computed for parameters {'Omega_m': 0.32905622959646474, 'b1': 0.473784508892149}
 2023-07-02 10:34:53,400 [prior] Evaluating prior at array([0.32905623, 0.47378451])
 2023-07-02 10:34:53,400 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,400 [model] Got input parameters: {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.473784508892149, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,400 [classy] Got parameters {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,400 [classy] Re-using computed results
 2023-07-02 10:34:53,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31169902973238}
 2023-07-02 10:34:53,400 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,400 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.473784508892149, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,400 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,419 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90436
 2023-07-02 10:34:53,419 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,419 [mcmc] New sample, #893:
   Omega_m:0.3290562, b1:0.4639619
 2023-07-02 10:34:53,419 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5013697182948436}
 2023-07-02 10:34:53,419 [prior] Evaluating prior at array([0.31391984, 0.50136972])
 2023-07-02 10:34:53,420 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,420 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5013697182948436, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,420 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,420 [classy] Computing new state
 2023-07-02 10:34:53,420 [classy] Setting parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,466 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,466 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,468 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00032839
 2023-07-02 10:34:53,468 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5013697182948436, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,468 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,488 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91522
 2023-07-02 10:34:53,488 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,488 [mcmc] New sample, #894:
   Omega_m:0.3290562, b1:0.4737845
 2023-07-02 10:34:53,488 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5578296340790643}
 2023-07-02 10:34:53,488 [prior] Evaluating prior at array([0.31391984, 0.55782963])
 2023-07-02 10:34:53,488 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,488 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5578296340790643, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,488 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,488 [classy] Re-using computed results
 2023-07-02 10:34:53,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,488 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5578296340790643, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,488 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,508 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.85562
 2023-07-02 10:34:53,508 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,508 [model] Posterior to be computed for parameters {'Omega_m': 0.28452823166769897, 'b1': 0.5549342360480563}
 2023-07-02 10:34:53,508 [prior] Evaluating prior at array([0.28452823, 0.55493424])
 2023-07-02 10:34:53,508 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,508 [model] Got input parameters: {'Omega_m': 0.28452823166769897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5549342360480563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,508 [classy] Got parameters {'Omega_m': 0.28452823166769897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,508 [classy] Computing new state
 2023-07-02 10:34:53,508 [classy] Setting parameters: {'Omega_m': 0.28452823166769897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,554 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.76409211092061}
 2023-07-02 10:34:53,554 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,556 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0516772
 2023-07-02 10:34:53,556 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5549342360480563, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,556 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,576 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.08642
 2023-07-02 10:34:53,576 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,576 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.4759995916658736}
 2023-07-02 10:34:53,576 [prior] Evaluating prior at array([0.31391984, 0.47599959])
 2023-07-02 10:34:53,576 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,576 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4759995916658736, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,576 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,576 [classy] Re-using computed results
 2023-07-02 10:34:53,576 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,576 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4759995916658736, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,576 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,596 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10207
 2023-07-02 10:34:53,596 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,596 [model] Posterior to be computed for parameters {'Omega_m': 0.34631065426367624, 'b1': 0.4423393076905062}
 2023-07-02 10:34:53,596 [prior] Evaluating prior at array([0.34631065, 0.44233931])
 2023-07-02 10:34:53,597 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,597 [model] Got input parameters: {'Omega_m': 0.34631065426367624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4423393076905062, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,597 [classy] Got parameters {'Omega_m': 0.34631065426367624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,597 [classy] Computing new state
 2023-07-02 10:34:53,597 [classy] Setting parameters: {'Omega_m': 0.34631065426367624, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.37490245731038}
 2023-07-02 10:34:53,643 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0648738
 2023-07-02 10:34:53,645 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4423393076905062, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,645 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,664 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.84992
 2023-07-02 10:34:53,664 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,664 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.4987065745251715}
 2023-07-02 10:34:53,664 [prior] Evaluating prior at array([0.31391984, 0.49870657])
 2023-07-02 10:34:53,664 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,664 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4987065745251715, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,664 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,664 [classy] Re-using computed results
 2023-07-02 10:34:53,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,664 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4987065745251715, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,664 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,684 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88276
 2023-07-02 10:34:53,684 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,684 [model] Posterior to be computed for parameters {'Omega_m': 0.26310100910495493, 'b1': 0.5939841225364915}
 2023-07-02 10:34:53,684 [prior] Evaluating prior at array([0.26310101, 0.59398412])
 2023-07-02 10:34:53,685 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,685 [model] Got input parameters: {'Omega_m': 0.26310100910495493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5939841225364915, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,685 [classy] Got parameters {'Omega_m': 0.26310100910495493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,685 [classy] Computing new state
 2023-07-02 10:34:53,685 [classy] Setting parameters: {'Omega_m': 0.26310100910495493, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,731 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.65705904754364}
 2023-07-02 10:34:53,731 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,733 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.170358
 2023-07-02 10:34:53,733 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5939841225364915, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,733 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,753 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.0373
 2023-07-02 10:34:53,753 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,753 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.4195690469399737}
 2023-07-02 10:34:53,753 [prior] Evaluating prior at array([0.31391984, 0.41956905])
 2023-07-02 10:34:53,753 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,753 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4195690469399737, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,753 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,753 [classy] Re-using computed results
 2023-07-02 10:34:53,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,753 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,753 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4195690469399737, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,753 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,772 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.0344
 2023-07-02 10:34:53,772 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,772 [model] Posterior to be computed for parameters {'Omega_m': 0.37229384129555476, 'b1': 0.3949864367698106}
 2023-07-02 10:34:53,773 [prior] Evaluating prior at array([0.37229384, 0.39498644])
 2023-07-02 10:34:53,773 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,773 [model] Got input parameters: {'Omega_m': 0.37229384129555476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3949864367698106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,773 [classy] Got parameters {'Omega_m': 0.37229384129555476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,773 [classy] Computing new state
 2023-07-02 10:34:53,773 [classy] Setting parameters: {'Omega_m': 0.37229384129555476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.61907819088873}
 2023-07-02 10:34:53,819 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.190736
 2023-07-02 10:34:53,821 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3949864367698106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,821 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,841 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.4615
 2023-07-02 10:34:53,841 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,841 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5111506359698931}
 2023-07-02 10:34:53,841 [prior] Evaluating prior at array([0.31391984, 0.51115064])
 2023-07-02 10:34:53,842 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,842 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5111506359698931, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,842 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,842 [classy] Re-using computed results
 2023-07-02 10:34:53,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,842 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5111506359698931, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,842 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70519
 2023-07-02 10:34:53,861 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,861 [mcmc] New sample, #895:
   Omega_m:0.3139198, b1:0.5013697
 2023-07-02 10:34:53,862 [model] Posterior to be computed for parameters {'Omega_m': 0.320694595379495, 'b1': 0.49880402625385184}
 2023-07-02 10:34:53,862 [prior] Evaluating prior at array([0.3206946 , 0.49880403])
 2023-07-02 10:34:53,862 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,862 [model] Got input parameters: {'Omega_m': 0.320694595379495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49880402625385184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,862 [classy] Got parameters {'Omega_m': 0.320694595379495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,862 [classy] Computing new state
 2023-07-02 10:34:53,862 [classy] Setting parameters: {'Omega_m': 0.320694595379495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.28355388400675}
 2023-07-02 10:34:53,908 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,910 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00425293
 2023-07-02 10:34:53,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49880402625385184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,910 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,929 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54908
 2023-07-02 10:34:53,929 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5305763960350792}
 2023-07-02 10:34:53,930 [prior] Evaluating prior at array([0.31391984, 0.5305764 ])
 2023-07-02 10:34:53,930 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,930 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305763960350792, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,930 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,930 [classy] Re-using computed results
 2023-07-02 10:34:53,930 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
 2023-07-02 10:34:53,930 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:53,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305763960350792, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,930 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:53,950 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.703992
 2023-07-02 10:34:53,950 [model] Computed derived parameters: {}
 2023-07-02 10:34:53,950 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4943080725160212}
 2023-07-02 10:34:53,950 [prior] Evaluating prior at array([0.32316159, 0.49430807])
 2023-07-02 10:34:53,950 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:53,950 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943080725160212, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,950 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:53,950 [classy] Computing new state
 2023-07-02 10:34:53,950 [classy] Setting parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:53,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:53,996 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:53,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00701161
 2023-07-02 10:34:53,998 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943080725160212, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:53,998 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,018 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.3707
 2023-07-02 10:34:54,018 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,018 [mcmc] New sample, #896:
   Omega_m:0.3139198, b1:0.5111506
 2023-07-02 10:34:54,018 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4340575227027353}
 2023-07-02 10:34:54,018 [prior] Evaluating prior at array([0.32316159, 0.43405752])
 2023-07-02 10:34:54,018 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,018 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4340575227027353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,018 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,018 [classy] Re-using computed results
 2023-07-02 10:34:54,018 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,018 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,018 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4340575227027353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,018 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,038 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.25121
 2023-07-02 10:34:54,038 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,038 [model] Posterior to be computed for parameters {'Omega_m': 0.28731423267394973, 'b1': 0.5596378263778474}
 2023-07-02 10:34:54,038 [prior] Evaluating prior at array([0.28731423, 0.55963783])
 2023-07-02 10:34:54,039 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,039 [model] Got input parameters: {'Omega_m': 0.28731423267394973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5596378263778474, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,039 [classy] Got parameters {'Omega_m': 0.28731423267394973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,039 [classy] Computing new state
 2023-07-02 10:34:54,039 [classy] Setting parameters: {'Omega_m': 0.28731423267394973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,085 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.4017510319698}
 2023-07-02 10:34:54,085 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,087 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0416247
 2023-07-02 10:34:54,087 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5596378263778474, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,087 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,107 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.20178
 2023-07-02 10:34:54,107 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,107 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.5223480446800762}
 2023-07-02 10:34:54,107 [prior] Evaluating prior at array([0.32316159, 0.52234804])
 2023-07-02 10:34:54,107 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,107 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5223480446800762, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,107 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,107 [classy] Re-using computed results
 2023-07-02 10:34:54,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,107 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5223480446800762, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,107 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,128 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.23739
 2023-07-02 10:34:54,128 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,129 [model] Posterior to be computed for parameters {'Omega_m': 0.2809208083190558, 'b1': 0.5712894762638713}
 2023-07-02 10:34:54,129 [prior] Evaluating prior at array([0.28092081, 0.57128948])
 2023-07-02 10:34:54,129 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,129 [model] Got input parameters: {'Omega_m': 0.2809208083190558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5712894762638713, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,129 [classy] Got parameters {'Omega_m': 0.2809208083190558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,129 [classy] Computing new state
 2023-07-02 10:34:54,129 [classy] Setting parameters: {'Omega_m': 0.2809208083190558, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.23784758103838}
 2023-07-02 10:34:54,176 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,177 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0664483
 2023-07-02 10:34:54,177 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5712894762638713, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,177 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,198 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.9169
 2023-07-02 10:34:54,198 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,198 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.5244624795738022}
 2023-07-02 10:34:54,198 [prior] Evaluating prior at array([0.32316159, 0.52446248])
 2023-07-02 10:34:54,198 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,198 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5244624795738022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,198 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,198 [classy] Re-using computed results
 2023-07-02 10:34:54,198 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,198 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5244624795738022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,198 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,217 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.69773
 2023-07-02 10:34:54,217 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,218 [model] Posterior to be computed for parameters {'Omega_m': 0.2668085005144599, 'b1': 0.5970083493583949}
 2023-07-02 10:34:54,218 [prior] Evaluating prior at array([0.2668085 , 0.59700835])
 2023-07-02 10:34:54,218 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,218 [model] Got input parameters: {'Omega_m': 0.2668085005144599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5970083493583949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,218 [classy] Got parameters {'Omega_m': 0.2668085005144599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,218 [classy] Computing new state
 2023-07-02 10:34:54,218 [classy] Setting parameters: {'Omega_m': 0.2668085005144599, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.14253734802193}
 2023-07-02 10:34:54,264 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.144296
 2023-07-02 10:34:54,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5970083493583949, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,266 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,285 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.4201
 2023-07-02 10:34:54,285 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,286 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4991548333232292}
 2023-07-02 10:34:54,286 [prior] Evaluating prior at array([0.32316159, 0.49915483])
 2023-07-02 10:34:54,286 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,286 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4991548333232292, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,286 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,286 [classy] Re-using computed results
 2023-07-02 10:34:54,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,286 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4991548333232292, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,286 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,306 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07089
 2023-07-02 10:34:54,306 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,306 [mcmc] New sample, #897:
   Omega_m:0.3231616, b1:0.4943081
 2023-07-02 10:34:54,306 [model] Posterior to be computed for parameters {'Omega_m': 0.35100722015888947, 'b1': 0.4484077636904055}
 2023-07-02 10:34:54,306 [prior] Evaluating prior at array([0.35100722, 0.44840776])
 2023-07-02 10:34:54,307 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,307 [model] Got input parameters: {'Omega_m': 0.35100722015888947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4484077636904055, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,307 [classy] Got parameters {'Omega_m': 0.35100722015888947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,307 [classy] Computing new state
 2023-07-02 10:34:54,307 [classy] Setting parameters: {'Omega_m': 0.35100722015888947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.8629718663464}
 2023-07-02 10:34:54,353 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,355 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0831659
 2023-07-02 10:34:54,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4484077636904055, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,355 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,375 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75233
 2023-07-02 10:34:54,375 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,375 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4483250823189745}
 2023-07-02 10:34:54,375 [prior] Evaluating prior at array([0.32316159, 0.44832508])
 2023-07-02 10:34:54,375 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,375 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4483250823189745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,375 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,375 [classy] Re-using computed results
 2023-07-02 10:34:54,375 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,375 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,375 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4483250823189745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,375 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,395 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.0412
 2023-07-02 10:34:54,395 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,396 [model] Posterior to be computed for parameters {'Omega_m': 0.24839646289155248, 'b1': 0.6354099947097832}
 2023-07-02 10:34:54,396 [prior] Evaluating prior at array([0.24839646, 0.63540999])
 2023-07-02 10:34:54,396 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,396 [model] Got input parameters: {'Omega_m': 0.24839646289155248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6354099947097832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,396 [classy] Got parameters {'Omega_m': 0.24839646289155248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,396 [classy] Computing new state
 2023-07-02 10:34:54,396 [classy] Setting parameters: {'Omega_m': 0.24839646289155248, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.75936900976455}
 2023-07-02 10:34:54,442 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,444 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.298809
 2023-07-02 10:34:54,444 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6354099947097832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,444 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -30.8041
 2023-07-02 10:34:54,463 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,463 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.5188334423060758}
 2023-07-02 10:34:54,464 [prior] Evaluating prior at array([0.32316159, 0.51883344])
 2023-07-02 10:34:54,464 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,464 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5188334423060758, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,464 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,464 [classy] Re-using computed results
 2023-07-02 10:34:54,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,464 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,464 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5188334423060758, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,464 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,483 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.532012
 2023-07-02 10:34:54,483 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,483 [model] Posterior to be computed for parameters {'Omega_m': 0.3765601740626795, 'b1': 0.4018389680163371}
 2023-07-02 10:34:54,483 [prior] Evaluating prior at array([0.37656017, 0.40183897])
 2023-07-02 10:34:54,483 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,483 [model] Got input parameters: {'Omega_m': 0.3765601740626795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4018389680163371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,483 [classy] Got parameters {'Omega_m': 0.3765601740626795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,483 [classy] Computing new state
 2023-07-02 10:34:54,483 [classy] Setting parameters: {'Omega_m': 0.3765601740626795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.18373389293097}
 2023-07-02 10:34:54,530 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,532 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.216824
 2023-07-02 10:34:54,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4018389680163371, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,532 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.782
 2023-07-02 10:34:54,551 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,552 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4913492916866584}
 2023-07-02 10:34:54,552 [prior] Evaluating prior at array([0.32316159, 0.49134929])
 2023-07-02 10:34:54,552 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,552 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4913492916866584, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,552 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,552 [classy] Re-using computed results
 2023-07-02 10:34:54,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,552 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,552 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4913492916866584, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,552 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,571 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48919
 2023-07-02 10:34:54,571 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,571 [mcmc] New sample, #898:
   Omega_m:0.3231616, b1:0.4991548
 2023-07-02 10:34:54,572 [model] Posterior to be computed for parameters {'Omega_m': 0.35690214456083547, 'b1': 0.42985905979471195}
 2023-07-02 10:34:54,572 [prior] Evaluating prior at array([0.35690214, 0.42985906])
 2023-07-02 10:34:54,572 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,572 [model] Got input parameters: {'Omega_m': 0.35690214456083547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42985905979471195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,572 [classy] Got parameters {'Omega_m': 0.35690214456083547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,572 [classy] Computing new state
 2023-07-02 10:34:54,572 [classy] Setting parameters: {'Omega_m': 0.35690214456083547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.22922151754042}
 2023-07-02 10:34:54,618 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,620 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.109012
 2023-07-02 10:34:54,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42985905979471195, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,620 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,639 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.33931
 2023-07-02 10:34:54,639 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,640 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4841769850395403}
 2023-07-02 10:34:54,640 [prior] Evaluating prior at array([0.32316159, 0.48417699])
 2023-07-02 10:34:54,640 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,640 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4841769850395403, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,640 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,640 [classy] Re-using computed results
 2023-07-02 10:34:54,640 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,640 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,640 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4841769850395403, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,640 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,660 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5764
 2023-07-02 10:34:54,660 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,660 [mcmc] New sample, #899:
   Omega_m:0.3231616, b1:0.4913493
 2023-07-02 10:34:54,660 [model] Posterior to be computed for parameters {'Omega_m': 0.302682446325695, 'b1': 0.5214990492965492}
 2023-07-02 10:34:54,660 [prior] Evaluating prior at array([0.30268245, 0.52149905])
 2023-07-02 10:34:54,660 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,660 [model] Got input parameters: {'Omega_m': 0.302682446325695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5214990492965492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,660 [classy] Got parameters {'Omega_m': 0.302682446325695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,660 [classy] Computing new state
 2023-07-02 10:34:54,660 [classy] Setting parameters: {'Omega_m': 0.302682446325695, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4561925742721}
 2023-07-02 10:34:54,707 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,709 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0062402
 2023-07-02 10:34:54,709 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5214990492965492, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,709 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,728 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99544
 2023-07-02 10:34:54,728 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,729 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4803420982604379}
 2023-07-02 10:34:54,729 [prior] Evaluating prior at array([0.32316159, 0.4803421 ])
 2023-07-02 10:34:54,729 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,729 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4803420982604379, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,729 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,729 [classy] Re-using computed results
 2023-07-02 10:34:54,729 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,729 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,729 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4803420982604379, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,729 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,749 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50845
 2023-07-02 10:34:54,749 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,749 [mcmc] New sample, #900:
   Omega_m:0.3231616, b1:0.484177
 2023-07-02 10:34:54,749 [model] Posterior to be computed for parameters {'Omega_m': 0.3898986620957532, 'b1': 0.3587176020941959}
 2023-07-02 10:34:54,749 [prior] Evaluating prior at array([0.38989866, 0.3587176 ])
 2023-07-02 10:34:54,749 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,749 [model] Got input parameters: {'Omega_m': 0.3898986620957532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3587176020941959, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,749 [classy] Got parameters {'Omega_m': 0.3898986620957532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,749 [classy] Computing new state
 2023-07-02 10:34:54,749 [classy] Setting parameters: {'Omega_m': 0.3898986620957532, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.85194644592906}
 2023-07-02 10:34:54,795 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,797 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.307287
 2023-07-02 10:34:54,797 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3587176020941959, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,797 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,817 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.0417
 2023-07-02 10:34:54,817 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,817 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4372556356827902}
 2023-07-02 10:34:54,817 [prior] Evaluating prior at array([0.32316159, 0.43725564])
 2023-07-02 10:34:54,817 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,817 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4372556356827902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,817 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,817 [classy] Re-using computed results
 2023-07-02 10:34:54,818 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
 2023-07-02 10:34:54,818 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,818 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4372556356827902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,818 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,837 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.44835
 2023-07-02 10:34:54,837 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,837 [model] Posterior to be computed for parameters {'Omega_m': 0.3075160781289959, 'b1': 0.5088551452641338}
 2023-07-02 10:34:54,837 [prior] Evaluating prior at array([0.30751608, 0.50885515])
 2023-07-02 10:34:54,837 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,837 [model] Got input parameters: {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088551452641338, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,837 [classy] Got parameters {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,837 [classy] Computing new state
 2023-07-02 10:34:54,837 [classy] Setting parameters: {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,883 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8621621289191}
 2023-07-02 10:34:54,883 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,885 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173482
 2023-07-02 10:34:54,885 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088551452641338, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,885 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,905 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51579
 2023-07-02 10:34:54,906 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,906 [mcmc] New sample, #901:
   Omega_m:0.3231616, b1:0.4803421
 2023-07-02 10:34:54,906 [model] Posterior to be computed for parameters {'Omega_m': 0.3075160781289959, 'b1': 0.5375629126592832}
 2023-07-02 10:34:54,906 [prior] Evaluating prior at array([0.30751608, 0.53756291])
 2023-07-02 10:34:54,906 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,906 [model] Got input parameters: {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375629126592832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,906 [classy] Got parameters {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,906 [classy] Re-using computed results
 2023-07-02 10:34:54,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8621621289191}
 2023-07-02 10:34:54,906 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375629126592832, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,906 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05544
 2023-07-02 10:34:54,925 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,926 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.4906390920622441}
 2023-07-02 10:34:54,926 [prior] Evaluating prior at array([0.31751148, 0.49063909])
 2023-07-02 10:34:54,926 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,926 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906390920622441, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,926 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,926 [classy] Computing new state
 2023-07-02 10:34:54,926 [classy] Setting parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:54,972 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
 2023-07-02 10:34:54,972 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:54,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173304
 2023-07-02 10:34:54,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906390920622441, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,974 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:54,993 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82547
 2023-07-02 10:34:54,993 [model] Computed derived parameters: {}
 2023-07-02 10:34:54,993 [mcmc] New sample, #902:
   Omega_m:0.3075161, b1:0.5088551
 2023-07-02 10:34:54,993 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.5076868045154612}
 2023-07-02 10:34:54,993 [prior] Evaluating prior at array([0.31751148, 0.5076868 ])
 2023-07-02 10:34:54,993 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:54,994 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5076868045154612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,994 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:54,994 [classy] Re-using computed results
 2023-07-02 10:34:54,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
 2023-07-02 10:34:54,994 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:54,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5076868045154612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:54,994 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,014 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50963
 2023-07-02 10:34:55,014 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,014 [mcmc] New sample, #903:
   Omega_m:0.3175115, b1:0.4906391
 2023-07-02 10:34:55,014 [model] Posterior to be computed for parameters {'Omega_m': 0.3301572005833629, 'b1': 0.4846407081678777}
 2023-07-02 10:34:55,014 [prior] Evaluating prior at array([0.3301572 , 0.48464071])
 2023-07-02 10:34:55,014 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,014 [model] Got input parameters: {'Omega_m': 0.3301572005833629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4846407081678777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,014 [classy] Got parameters {'Omega_m': 0.3301572005833629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,014 [classy] Computing new state
 2023-07-02 10:34:55,014 [classy] Setting parameters: {'Omega_m': 0.3301572005833629, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1853929244177}
 2023-07-02 10:34:55,061 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185453
 2023-07-02 10:34:55,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4846407081678777, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,063 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,082 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36134
 2023-07-02 10:34:55,082 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,082 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.5479424325480224}
 2023-07-02 10:34:55,082 [prior] Evaluating prior at array([0.31751148, 0.54794243])
 2023-07-02 10:34:55,082 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,082 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5479424325480224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,082 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,082 [classy] Re-using computed results
 2023-07-02 10:34:55,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
 2023-07-02 10:34:55,082 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5479424325480224, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,082 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,102 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.84612
 2023-07-02 10:34:55,102 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,102 [model] Posterior to be computed for parameters {'Omega_m': 0.34114739825032037, 'b1': 0.464611702069516}
 2023-07-02 10:34:55,103 [prior] Evaluating prior at array([0.3411474, 0.4646117])
 2023-07-02 10:34:55,103 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,103 [model] Got input parameters: {'Omega_m': 0.34114739825032037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.464611702069516, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,103 [classy] Got parameters {'Omega_m': 0.34114739825032037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,103 [classy] Computing new state
 2023-07-02 10:34:55,103 [classy] Setting parameters: {'Omega_m': 0.34114739825032037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.94511168486792}
 2023-07-02 10:34:55,152 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,153 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0472034
 2023-07-02 10:34:55,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.464611702069516, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,154 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,173 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.841575
 2023-07-02 10:34:55,173 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,173 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.5122688047876915}
 2023-07-02 10:34:55,173 [prior] Evaluating prior at array([0.31751148, 0.5122688 ])
 2023-07-02 10:34:55,173 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,173 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122688047876915, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,173 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,173 [classy] Re-using computed results
 2023-07-02 10:34:55,173 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
 2023-07-02 10:34:55,173 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122688047876915, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,173 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,193 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15061
 2023-07-02 10:34:55,193 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,193 [mcmc] New sample, #904:
   Omega_m:0.3175115, b1:0.5076868
 2023-07-02 10:34:55,193 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.4910366978295503}
 2023-07-02 10:34:55,193 [prior] Evaluating prior at array([0.32916184, 0.4910367 ])
 2023-07-02 10:34:55,193 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,193 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4910366978295503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,193 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,193 [classy] Computing new state
 2023-07-02 10:34:55,193 [classy] Setting parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,239 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
 2023-07-02 10:34:55,239 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,241 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0165765
 2023-07-02 10:34:55,241 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4910366978295503, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,241 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14858
 2023-07-02 10:34:55,261 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,261 [mcmc] New sample, #905:
   Omega_m:0.3175115, b1:0.5122688
 2023-07-02 10:34:55,261 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.5443345915555996}
 2023-07-02 10:34:55,261 [prior] Evaluating prior at array([0.32916184, 0.54433459])
 2023-07-02 10:34:55,262 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,262 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5443345915555996, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,262 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,262 [classy] Re-using computed results
 2023-07-02 10:34:55,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
 2023-07-02 10:34:55,262 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,262 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5443345915555996, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,262 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,281 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.3177
 2023-07-02 10:34:55,281 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,282 [model] Posterior to be computed for parameters {'Omega_m': 0.2847884494375359, 'b1': 0.5719046602039826}
 2023-07-02 10:34:55,282 [prior] Evaluating prior at array([0.28478845, 0.57190466])
 2023-07-02 10:34:55,282 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,282 [model] Got input parameters: {'Omega_m': 0.2847884494375359, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5719046602039826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,282 [classy] Got parameters {'Omega_m': 0.2847884494375359, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,282 [classy] Computing new state
 2023-07-02 10:34:55,282 [classy] Setting parameters: {'Omega_m': 0.2847884494375359, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.73011776671558}
 2023-07-02 10:34:55,328 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0506887
 2023-07-02 10:34:55,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5719046602039826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,330 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,349 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.72246
 2023-07-02 10:34:55,349 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,350 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.48785865146903673}
 2023-07-02 10:34:55,350 [prior] Evaluating prior at array([0.32916184, 0.48785865])
 2023-07-02 10:34:55,350 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,350 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48785865146903673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,350 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,350 [classy] Re-using computed results
 2023-07-02 10:34:55,350 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
 2023-07-02 10:34:55,350 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48785865146903673, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,350 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,370 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41091
 2023-07-02 10:34:55,370 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,370 [mcmc] New sample, #906:
   Omega_m:0.3291618, b1:0.4910367
 2023-07-02 10:34:55,370 [model] Posterior to be computed for parameters {'Omega_m': 0.34790604443429046, 'b1': 0.4536984102193664}
 2023-07-02 10:34:55,370 [prior] Evaluating prior at array([0.34790604, 0.45369841])
 2023-07-02 10:34:55,371 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,371 [model] Got input parameters: {'Omega_m': 0.34790604443429046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4536984102193664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,371 [classy] Got parameters {'Omega_m': 0.34790604443429046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,371 [classy] Computing new state
 2023-07-02 10:34:55,371 [classy] Setting parameters: {'Omega_m': 0.34790604443429046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.20029672892326}
 2023-07-02 10:34:55,417 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0708538
 2023-07-02 10:34:55,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4536984102193664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,419 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.77364
 2023-07-02 10:34:55,439 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,439 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.4474653825408857}
 2023-07-02 10:34:55,439 [prior] Evaluating prior at array([0.32916184, 0.44746538])
 2023-07-02 10:34:55,439 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,439 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4474653825408857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,439 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,439 [classy] Re-using computed results
 2023-07-02 10:34:55,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
 2023-07-02 10:34:55,439 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4474653825408857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,439 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0731776
 2023-07-02 10:34:55,459 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,459 [model] Posterior to be computed for parameters {'Omega_m': 0.286397779034629, 'b1': 0.5657937027811537}
 2023-07-02 10:34:55,459 [prior] Evaluating prior at array([0.28639778, 0.5657937 ])
 2023-07-02 10:34:55,460 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,460 [model] Got input parameters: {'Omega_m': 0.286397779034629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5657937027811537, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,460 [classy] Got parameters {'Omega_m': 0.286397779034629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,460 [classy] Computing new state
 2023-07-02 10:34:55,460 [classy] Setting parameters: {'Omega_m': 0.286397779034629, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.52059627145061}
 2023-07-02 10:34:55,506 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,508 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0448025
 2023-07-02 10:34:55,508 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5657937027811537, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,508 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,527 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.82043
 2023-07-02 10:34:55,527 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,528 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.46087636653479624}
 2023-07-02 10:34:55,528 [prior] Evaluating prior at array([0.32916184, 0.46087637])
 2023-07-02 10:34:55,528 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,528 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46087636653479624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,528 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,528 [classy] Re-using computed results
 2023-07-02 10:34:55,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
 2023-07-02 10:34:55,528 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46087636653479624, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,528 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,547 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38021
 2023-07-02 10:34:55,547 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,547 [mcmc] New sample, #907:
   Omega_m:0.3291618, b1:0.4878587
 2023-07-02 10:34:55,547 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.4785802460503782}
 2023-07-02 10:34:55,547 [prior] Evaluating prior at array([0.31944747, 0.47858025])
 2023-07-02 10:34:55,548 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,548 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4785802460503782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,548 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,548 [classy] Computing new state
 2023-07-02 10:34:55,548 [classy] Setting parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,594 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
 2023-07-02 10:34:55,594 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,596 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00312485
 2023-07-02 10:34:55,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4785802460503782, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,596 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32589
 2023-07-02 10:34:55,617 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,617 [mcmc] New sample, #908:
   Omega_m:0.3291618, b1:0.4608764
 2023-07-02 10:34:55,617 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.48137026732973026}
 2023-07-02 10:34:55,617 [prior] Evaluating prior at array([0.31944747, 0.48137027])
 2023-07-02 10:34:55,617 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,617 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48137026732973026, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,617 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,617 [classy] Re-using computed results
 2023-07-02 10:34:55,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
 2023-07-02 10:34:55,617 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48137026732973026, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,617 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,636 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50826
 2023-07-02 10:34:55,636 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,636 [mcmc] New sample, #909:
   Omega_m:0.3194475, b1:0.4785802
 2023-07-02 10:34:55,636 [model] Posterior to be computed for parameters {'Omega_m': 0.4270028793938878, 'b1': 0.28535669286266263}
 2023-07-02 10:34:55,637 [prior] Evaluating prior at array([0.42700288, 0.28535669])
 2023-07-02 10:34:55,637 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,637 [model] Got input parameters: {'Omega_m': 0.4270028793938878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.28535669286266263, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,637 [classy] Got parameters {'Omega_m': 0.4270028793938878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,637 [classy] Computing new state
 2023-07-02 10:34:55,637 [classy] Setting parameters: {'Omega_m': 0.4270028793938878, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.36312836889343}
 2023-07-02 10:34:55,683 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,685 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.621731
 2023-07-02 10:34:55,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.28535669286266263, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,685 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,705 [fs_likelihood.fslikelihood] Computed log-likelihood = -41.4071
 2023-07-02 10:34:55,705 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.4502241680571882}
 2023-07-02 10:34:55,705 [prior] Evaluating prior at array([0.31944747, 0.45022417])
 2023-07-02 10:34:55,705 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,705 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4502241680571882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,705 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,705 [classy] Re-using computed results
 2023-07-02 10:34:55,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
 2023-07-02 10:34:55,705 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4502241680571882, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,705 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,725 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.76115
 2023-07-02 10:34:55,725 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,725 [model] Posterior to be computed for parameters {'Omega_m': 0.4178323817123093, 'b1': 0.3020693999090134}
 2023-07-02 10:34:55,725 [prior] Evaluating prior at array([0.41783238, 0.3020694 ])
 2023-07-02 10:34:55,725 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,725 [model] Got input parameters: {'Omega_m': 0.4178323817123093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3020693999090134, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,725 [classy] Got parameters {'Omega_m': 0.4178323817123093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,725 [classy] Computing new state
 2023-07-02 10:34:55,725 [classy] Setting parameters: {'Omega_m': 0.4178323817123093, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.19754578874188}
 2023-07-02 10:34:55,772 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.536191
 2023-07-02 10:34:55,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3020693999090134, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,774 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -35.9468
 2023-07-02 10:34:55,794 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,795 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.4774971435705008}
 2023-07-02 10:34:55,795 [prior] Evaluating prior at array([0.31944747, 0.47749714])
 2023-07-02 10:34:55,795 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,795 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4774971435705008, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,795 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,795 [classy] Re-using computed results
 2023-07-02 10:34:55,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
 2023-07-02 10:34:55,795 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,795 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4774971435705008, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,795 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,816 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.24418
 2023-07-02 10:34:55,816 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,816 [mcmc] New sample, #910:
   Omega_m:0.3194475, b1:0.4813703
 2023-07-02 10:34:55,816 [model] Posterior to be computed for parameters {'Omega_m': 0.3233776317108762, 'b1': 0.4703346508294152}
 2023-07-02 10:34:55,816 [prior] Evaluating prior at array([0.32337763, 0.47033465])
 2023-07-02 10:34:55,816 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,816 [model] Got input parameters: {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4703346508294152, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,817 [classy] Got parameters {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,817 [classy] Computing new state
 2023-07-02 10:34:55,817 [classy] Setting parameters: {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9692645057659}
 2023-07-02 10:34:55,864 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0072863
 2023-07-02 10:34:55,867 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4703346508294152, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,867 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,887 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.97551
 2023-07-02 10:34:55,887 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,887 [mcmc] New sample, #911:
   Omega_m:0.3194475, b1:0.4774971
 2023-07-02 10:34:55,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3233776317108762, 'b1': 0.47382944431498963}
 2023-07-02 10:34:55,887 [prior] Evaluating prior at array([0.32337763, 0.47382944])
 2023-07-02 10:34:55,888 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,888 [model] Got input parameters: {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47382944431498963, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,888 [classy] Got parameters {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,888 [classy] Re-using computed results
 2023-07-02 10:34:55,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9692645057659}
 2023-07-02 10:34:55,888 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,888 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47382944431498963, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,888 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,908 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21872
 2023-07-02 10:34:55,908 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,908 [mcmc] New sample, #912:
   Omega_m:0.3233776, b1:0.4703347
 2023-07-02 10:34:55,908 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.49243158763058675}
 2023-07-02 10:34:55,908 [prior] Evaluating prior at array([0.31317037, 0.49243159])
 2023-07-02 10:34:55,908 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,908 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49243158763058675, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,908 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,908 [classy] Computing new state
 2023-07-02 10:34:55,908 [classy] Setting parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:55,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
 2023-07-02 10:34:55,955 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:55,956 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000231222
 2023-07-02 10:34:55,956 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49243158763058675, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,957 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,976 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56746
 2023-07-02 10:34:55,976 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,976 [mcmc] New sample, #913:
   Omega_m:0.3233776, b1:0.4738294
 2023-07-02 10:34:55,976 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.5131003884334429}
 2023-07-02 10:34:55,976 [prior] Evaluating prior at array([0.31317037, 0.51310039])
 2023-07-02 10:34:55,977 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,977 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5131003884334429, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,977 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,977 [classy] Re-using computed results
 2023-07-02 10:34:55,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
 2023-07-02 10:34:55,977 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:55,977 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5131003884334429, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,977 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:55,996 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66196
 2023-07-02 10:34:55,996 [model] Computed derived parameters: {}
 2023-07-02 10:34:55,996 [mcmc] New sample, #914:
   Omega_m:0.3131704, b1:0.4924316
 2023-07-02 10:34:55,996 [model] Posterior to be computed for parameters {'Omega_m': 0.33702001684498883, 'b1': 0.4696357791888788}
 2023-07-02 10:34:55,996 [prior] Evaluating prior at array([0.33702002, 0.46963578])
 2023-07-02 10:34:55,996 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:55,997 [model] Got input parameters: {'Omega_m': 0.33702001684498883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4696357791888788, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:55,997 [classy] Got parameters {'Omega_m': 0.33702001684498883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:55,997 [classy] Computing new state
 2023-07-02 10:34:55,997 [classy] Setting parameters: {'Omega_m': 0.33702001684498883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.40661016458202}
 2023-07-02 10:34:56,043 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,045 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0349796
 2023-07-02 10:34:56,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4696357791888788, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,045 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,065 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.250856
 2023-07-02 10:34:56,065 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,065 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.49876108865180324}
 2023-07-02 10:34:56,065 [prior] Evaluating prior at array([0.31317037, 0.49876109])
 2023-07-02 10:34:56,065 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,065 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49876108865180324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,065 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,065 [classy] Re-using computed results
 2023-07-02 10:34:56,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
 2023-07-02 10:34:56,066 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,066 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49876108865180324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,066 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,085 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83903
 2023-07-02 10:34:56,085 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,085 [mcmc] New sample, #915:
   Omega_m:0.3131704, b1:0.5131004
 2023-07-02 10:34:56,085 [model] Posterior to be computed for parameters {'Omega_m': 0.299357160852926, 'b1': 0.5239348783884269}
 2023-07-02 10:34:56,085 [prior] Evaluating prior at array([0.29935716, 0.52393488])
 2023-07-02 10:34:56,085 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,085 [model] Got input parameters: {'Omega_m': 0.299357160852926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239348783884269, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,085 [classy] Got parameters {'Omega_m': 0.299357160852926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,085 [classy] Computing new state
 2023-07-02 10:34:56,085 [classy] Setting parameters: {'Omega_m': 0.299357160852926, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.86972364516754}
 2023-07-02 10:34:56,133 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,135 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111238
 2023-07-02 10:34:56,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239348783884269, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,135 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,155 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35865
 2023-07-02 10:34:56,155 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.5134732519716683}
 2023-07-02 10:34:56,156 [prior] Evaluating prior at array([0.31317037, 0.51347325])
 2023-07-02 10:34:56,156 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,156 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5134732519716683, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,156 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,156 [classy] Re-using computed results
 2023-07-02 10:34:56,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
 2023-07-02 10:34:56,156 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5134732519716683, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,156 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,176 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64238
 2023-07-02 10:34:56,176 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,176 [mcmc] New sample, #916:
   Omega_m:0.3131704, b1:0.4987611
 2023-07-02 10:34:56,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3455157443127441, 'b1': 0.45452566576725506}
 2023-07-02 10:34:56,176 [prior] Evaluating prior at array([0.34551574, 0.45452567])
 2023-07-02 10:34:56,176 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,176 [model] Got input parameters: {'Omega_m': 0.3455157443127441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45452566576725506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,176 [classy] Got parameters {'Omega_m': 0.3455157443127441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,177 [classy] Computing new state
 2023-07-02 10:34:56,177 [classy] Setting parameters: {'Omega_m': 0.3455157443127441, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.46217280870752}
 2023-07-02 10:34:56,223 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,225 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0619852
 2023-07-02 10:34:56,225 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45452566576725506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,225 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,244 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86472
 2023-07-02 10:34:56,245 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,245 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.5745134283309952}
 2023-07-02 10:34:56,245 [prior] Evaluating prior at array([0.31317037, 0.57451343])
 2023-07-02 10:34:56,245 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,245 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5745134283309952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,245 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,245 [classy] Re-using computed results
 2023-07-02 10:34:56,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
 2023-07-02 10:34:56,245 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5745134283309952, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,245 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.5864
 2023-07-02 10:34:56,265 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,265 [model] Posterior to be computed for parameters {'Omega_m': 0.31671288668477177, 'b1': 0.5070172249332341}
 2023-07-02 10:34:56,265 [prior] Evaluating prior at array([0.31671289, 0.50701722])
 2023-07-02 10:34:56,265 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,266 [model] Got input parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070172249332341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,266 [classy] Got parameters {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,266 [classy] Computing new state
 2023-07-02 10:34:56,266 [classy] Setting parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,311 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.75431042843647}
 2023-07-02 10:34:56,311 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,313 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00128759
 2023-07-02 10:34:56,313 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070172249332341, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,313 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,333 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65304
 2023-07-02 10:34:56,333 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,333 [mcmc] New sample, #917:
   Omega_m:0.3131704, b1:0.5134733
 2023-07-02 10:34:56,333 [model] Posterior to be computed for parameters {'Omega_m': 0.31671288668477177, 'b1': 0.5432245468325416}
 2023-07-02 10:34:56,334 [prior] Evaluating prior at array([0.31671289, 0.54322455])
 2023-07-02 10:34:56,334 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,334 [model] Got input parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5432245468325416, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,334 [classy] Got parameters {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,334 [classy] Re-using computed results
 2023-07-02 10:34:56,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.75431042843647}
 2023-07-02 10:34:56,334 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5432245468325416, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,334 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,353 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.06484
 2023-07-02 10:34:56,353 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,353 [model] Posterior to be computed for parameters {'Omega_m': 0.36311208312968063, 'b1': 0.42245734560110565}
 2023-07-02 10:34:56,353 [prior] Evaluating prior at array([0.36311208, 0.42245735])
 2023-07-02 10:34:56,353 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,353 [model] Got input parameters: {'Omega_m': 0.36311208312968063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42245734560110565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,353 [classy] Got parameters {'Omega_m': 0.36311208312968063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,353 [classy] Computing new state
 2023-07-02 10:34:56,353 [classy] Setting parameters: {'Omega_m': 0.36311208312968063, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.57198232053008}
 2023-07-02 10:34:56,400 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.139576
 2023-07-02 10:34:56,401 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42245734560110565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,402 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,422 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.82122
 2023-07-02 10:34:56,422 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,422 [model] Posterior to be computed for parameters {'Omega_m': 0.31671288668477177, 'b1': 0.4504389790432229}
 2023-07-02 10:34:56,422 [prior] Evaluating prior at array([0.31671289, 0.45043898])
 2023-07-02 10:34:56,422 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,422 [model] Got input parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4504389790432229, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,422 [classy] Got parameters {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,423 [classy] Re-using computed results
 2023-07-02 10:34:56,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.75431042843647}
 2023-07-02 10:34:56,423 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4504389790432229, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,423 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.72716
 2023-07-02 10:34:56,442 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,442 [model] Posterior to be computed for parameters {'Omega_m': 0.3075183982714138, 'b1': 0.523773653714869}
 2023-07-02 10:34:56,442 [prior] Evaluating prior at array([0.3075184 , 0.52377365])
 2023-07-02 10:34:56,442 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,442 [model] Got input parameters: {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523773653714869, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,442 [classy] Got parameters {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,442 [classy] Computing new state
 2023-07-02 10:34:56,442 [classy] Setting parameters: {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86187867552863}
 2023-07-02 10:34:56,489 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173337
 2023-07-02 10:34:56,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523773653714869, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,491 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,510 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32318
 2023-07-02 10:34:56,510 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,511 [mcmc] New sample, #918:
   Omega_m:0.3167129, b1:0.5070172
 2023-07-02 10:34:56,511 [model] Posterior to be computed for parameters {'Omega_m': 0.3075183982714138, 'b1': 0.5509308600416843}
 2023-07-02 10:34:56,511 [prior] Evaluating prior at array([0.3075184 , 0.55093086])
 2023-07-02 10:34:56,511 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,511 [model] Got input parameters: {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5509308600416843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,511 [classy] Got parameters {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,511 [classy] Re-using computed results
 2023-07-02 10:34:56,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86187867552863}
 2023-07-02 10:34:56,511 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5509308600416843, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,511 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.21539
 2023-07-02 10:34:56,531 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3210362825164551, 'b1': 0.4991380835290022}
 2023-07-02 10:34:56,531 [prior] Evaluating prior at array([0.32103628, 0.49913808])
 2023-07-02 10:34:56,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,531 [model] Got input parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4991380835290022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,531 [classy] Got parameters {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,531 [classy] Computing new state
 2023-07-02 10:34:56,531 [classy] Setting parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,577 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2433976362402}
 2023-07-02 10:34:56,578 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,579 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00459343
 2023-07-02 10:34:56,579 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4991380835290022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,579 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,599 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47937
 2023-07-02 10:34:56,599 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,599 [mcmc] New sample, #919:
   Omega_m:0.3075184, b1:0.5237737
 2023-07-02 10:34:56,599 [model] Posterior to be computed for parameters {'Omega_m': 0.3210362825164551, 'b1': 0.4716483679978067}
 2023-07-02 10:34:56,599 [prior] Evaluating prior at array([0.32103628, 0.47164837])
 2023-07-02 10:34:56,599 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,599 [model] Got input parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4716483679978067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,599 [classy] Got parameters {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,599 [classy] Re-using computed results
 2023-07-02 10:34:56,599 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2433976362402}
 2023-07-02 10:34:56,599 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,599 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4716483679978067, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,599 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,619 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9008
 2023-07-02 10:34:56,619 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,619 [mcmc] New sample, #920:
   Omega_m:0.3210363, b1:0.4991381
 2023-07-02 10:34:56,620 [model] Posterior to be computed for parameters {'Omega_m': 0.2874320088290671, 'b1': 0.5328902330681043}
 2023-07-02 10:34:56,620 [prior] Evaluating prior at array([0.28743201, 0.53289023])
 2023-07-02 10:34:56,620 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,620 [model] Got input parameters: {'Omega_m': 0.2874320088290671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5328902330681043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,620 [classy] Got parameters {'Omega_m': 0.2874320088290671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,620 [classy] Computing new state
 2023-07-02 10:34:56,620 [classy] Setting parameters: {'Omega_m': 0.2874320088290671, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.38649934654646}
 2023-07-02 10:34:56,666 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0412253
 2023-07-02 10:34:56,668 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5328902330681043, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,668 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,688 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.7265
 2023-07-02 10:34:56,688 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,688 [model] Posterior to be computed for parameters {'Omega_m': 0.3210362825164551, 'b1': 0.6537912007354751}
 2023-07-02 10:34:56,688 [prior] Evaluating prior at array([0.32103628, 0.6537912 ])
 2023-07-02 10:34:56,689 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,689 [model] Got input parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6537912007354751, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,689 [classy] Got parameters {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,689 [classy] Re-using computed results
 2023-07-02 10:34:56,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2433976362402}
 2023-07-02 10:34:56,689 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6537912007354751, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,689 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -83.3729
 2023-07-02 10:34:56,708 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,708 [model] Posterior to be computed for parameters {'Omega_m': 0.32177666221248546, 'b1': 0.4702990683858917}
 2023-07-02 10:34:56,708 [prior] Evaluating prior at array([0.32177666, 0.47029907])
 2023-07-02 10:34:56,708 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,708 [model] Got input parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4702990683858917, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,709 [classy] Got parameters {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,709 [classy] Computing new state
 2023-07-02 10:34:56,709 [classy] Setting parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,755 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1565201693537}
 2023-07-02 10:34:56,755 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,757 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00537722
 2023-07-02 10:34:56,757 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4702990683858917, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,757 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,777 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84991
 2023-07-02 10:34:56,777 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,777 [mcmc] New sample, #921:
   Omega_m:0.3210363, b1:0.4716484
 2023-07-02 10:34:56,777 [model] Posterior to be computed for parameters {'Omega_m': 0.32177666221248546, 'b1': 0.4928257359088519}
 2023-07-02 10:34:56,777 [prior] Evaluating prior at array([0.32177666, 0.49282574])
 2023-07-02 10:34:56,777 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,777 [model] Got input parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4928257359088519, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,777 [classy] Got parameters {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,777 [classy] Re-using computed results
 2023-07-02 10:34:56,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1565201693537}
 2023-07-02 10:34:56,777 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4928257359088519, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,777 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,797 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62746
 2023-07-02 10:34:56,797 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,797 [mcmc] New sample, #922:
   Omega_m:0.3217767, b1:0.4702991
 2023-07-02 10:34:56,797 [model] Posterior to be computed for parameters {'Omega_m': 0.34726388892606674, 'b1': 0.44637672427629144}
 2023-07-02 10:34:56,797 [prior] Evaluating prior at array([0.34726389, 0.44637672])
 2023-07-02 10:34:56,797 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,797 [model] Got input parameters: {'Omega_m': 0.34726388892606674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44637672427629144, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,797 [classy] Got parameters {'Omega_m': 0.34726388892606674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,797 [classy] Computing new state
 2023-07-02 10:34:56,797 [classy] Setting parameters: {'Omega_m': 0.34726388892606674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.27048819684398}
 2023-07-02 10:34:56,844 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,846 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684177
 2023-07-02 10:34:56,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44637672427629144, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,846 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.17388
 2023-07-02 10:34:56,865 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,866 [model] Posterior to be computed for parameters {'Omega_m': 0.32177666221248546, 'b1': 0.525821282634184}
 2023-07-02 10:34:56,866 [prior] Evaluating prior at array([0.32177666, 0.52582128])
 2023-07-02 10:34:56,866 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,866 [model] Got input parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.525821282634184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,866 [classy] Got parameters {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,866 [classy] Re-using computed results
 2023-07-02 10:34:56,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1565201693537}
 2023-07-02 10:34:56,866 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.525821282634184, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,866 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,886 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33012
 2023-07-02 10:34:56,886 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,886 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.5122673267513558}
 2023-07-02 10:34:56,886 [prior] Evaluating prior at array([0.31110879, 0.51226733])
 2023-07-02 10:34:56,886 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,886 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122673267513558, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,886 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,886 [classy] Computing new state
 2023-07-02 10:34:56,886 [classy] Setting parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:56,933 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
 2023-07-02 10:34:56,933 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:56,935 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000318744
 2023-07-02 10:34:56,935 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122673267513558, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,935 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,955 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76781
 2023-07-02 10:34:56,955 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,955 [mcmc] New sample, #923:
   Omega_m:0.3217767, b1:0.4928257
 2023-07-02 10:34:56,955 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.5083165022283158}
 2023-07-02 10:34:56,955 [prior] Evaluating prior at array([0.31110879, 0.5083165 ])
 2023-07-02 10:34:56,955 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,955 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083165022283158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,955 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,955 [classy] Re-using computed results
 2023-07-02 10:34:56,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
 2023-07-02 10:34:56,955 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:56,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083165022283158, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,955 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:56,975 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82919
 2023-07-02 10:34:56,975 [model] Computed derived parameters: {}
 2023-07-02 10:34:56,975 [mcmc] New sample, #924:
   Omega_m:0.3111088, b1:0.5122673
 2023-07-02 10:34:56,976 [model] Posterior to be computed for parameters {'Omega_m': 0.3273160466727496, 'b1': 0.4787797003170091}
 2023-07-02 10:34:56,976 [prior] Evaluating prior at array([0.32731605, 0.4787797 ])
 2023-07-02 10:34:56,976 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:56,976 [model] Got input parameters: {'Omega_m': 0.3273160466727496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4787797003170091, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:56,976 [classy] Got parameters {'Omega_m': 0.3273160466727496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:56,976 [classy] Computing new state
 2023-07-02 10:34:56,976 [classy] Setting parameters: {'Omega_m': 0.3273160466727496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,028 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.51211724486345}
 2023-07-02 10:34:57,028 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,030 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132101
 2023-07-02 10:34:57,030 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4787797003170091, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,030 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,049 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13993
 2023-07-02 10:34:57,049 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,050 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.48023407527945655}
 2023-07-02 10:34:57,050 [prior] Evaluating prior at array([0.31110879, 0.48023408])
 2023-07-02 10:34:57,050 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,050 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48023407527945655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,050 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,050 [classy] Re-using computed results
 2023-07-02 10:34:57,050 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
 2023-07-02 10:34:57,050 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,050 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48023407527945655, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,050 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,069 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.900694
 2023-07-02 10:34:57,069 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,070 [model] Posterior to be computed for parameters {'Omega_m': 0.30596232428952824, 'b1': 0.5176956369358876}
 2023-07-02 10:34:57,070 [prior] Evaluating prior at array([0.30596232, 0.51769564])
 2023-07-02 10:34:57,070 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,070 [model] Got input parameters: {'Omega_m': 0.30596232428952824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5176956369358876, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,070 [classy] Got parameters {'Omega_m': 0.30596232428952824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,070 [classy] Computing new state
 2023-07-02 10:34:57,070 [classy] Setting parameters: {'Omega_m': 0.30596232428952824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.05221140572525}
 2023-07-02 10:34:57,117 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00285355
 2023-07-02 10:34:57,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5176956369358876, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,118 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42649
 2023-07-02 10:34:57,141 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,141 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.465672419384173}
 2023-07-02 10:34:57,141 [prior] Evaluating prior at array([0.31110879, 0.46567242])
 2023-07-02 10:34:57,141 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,141 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.465672419384173, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,141 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,141 [classy] Re-using computed results
 2023-07-02 10:34:57,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
 2023-07-02 10:34:57,141 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,142 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.465672419384173, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,142 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,161 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.65561
 2023-07-02 10:34:57,161 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,161 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.5056362229936037}
 2023-07-02 10:34:57,161 [prior] Evaluating prior at array([0.31257949, 0.50563622])
 2023-07-02 10:34:57,161 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,161 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5056362229936037, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,161 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,161 [classy] Computing new state
 2023-07-02 10:34:57,161 [classy] Setting parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,207 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
 2023-07-02 10:34:57,207 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,209 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202923
 2023-07-02 10:34:57,209 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5056362229936037, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,209 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,229 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8858
 2023-07-02 10:34:57,229 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,229 [mcmc] New sample, #925:
   Omega_m:0.3111088, b1:0.5083165
 2023-07-02 10:34:57,230 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.49739319626336265}
 2023-07-02 10:34:57,230 [prior] Evaluating prior at array([0.31257949, 0.4973932 ])
 2023-07-02 10:34:57,230 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,230 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49739319626336265, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,230 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,230 [classy] Re-using computed results
 2023-07-02 10:34:57,230 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
 2023-07-02 10:34:57,230 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49739319626336265, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,230 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,249 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74371
 2023-07-02 10:34:57,249 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,249 [mcmc] New sample, #926:
   Omega_m:0.3125795, b1:0.5056362
 2023-07-02 10:34:57,249 [model] Posterior to be computed for parameters {'Omega_m': 0.323987510682703, 'b1': 0.47660273988179913}
 2023-07-02 10:34:57,250 [prior] Evaluating prior at array([0.32398751, 0.47660274])
 2023-07-02 10:34:57,250 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,250 [model] Got input parameters: {'Omega_m': 0.323987510682703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47660273988179913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,250 [classy] Got parameters {'Omega_m': 0.323987510682703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,250 [classy] Computing new state
 2023-07-02 10:34:57,250 [classy] Setting parameters: {'Omega_m': 0.323987510682703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8981486757012}
 2023-07-02 10:34:57,296 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,298 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00809002
 2023-07-02 10:34:57,298 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47660273988179913, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,298 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,317 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35832
 2023-07-02 10:34:57,317 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,317 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.5345294591771685}
 2023-07-02 10:34:57,317 [prior] Evaluating prior at array([0.31257949, 0.53452946])
 2023-07-02 10:34:57,318 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,318 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5345294591771685, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,318 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,318 [classy] Re-using computed results
 2023-07-02 10:34:57,318 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
 2023-07-02 10:34:57,318 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,318 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5345294591771685, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,318 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,338 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.429543
 2023-07-02 10:34:57,338 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,338 [model] Posterior to be computed for parameters {'Omega_m': 0.2956572121328211, 'b1': 0.5282330871802822}
 2023-07-02 10:34:57,338 [prior] Evaluating prior at array([0.29565721, 0.52823309])
 2023-07-02 10:34:57,338 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,338 [model] Got input parameters: {'Omega_m': 0.2956572121328211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282330871802822, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,338 [classy] Got parameters {'Omega_m': 0.2956572121328211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,338 [classy] Computing new state
 2023-07-02 10:34:57,338 [classy] Setting parameters: {'Omega_m': 0.2956572121328211, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3346270775292}
 2023-07-02 10:34:57,385 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0183198
 2023-07-02 10:34:57,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282330871802822, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,387 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,406 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.46046
 2023-07-02 10:34:57,406 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,406 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.49649976779902005}
 2023-07-02 10:34:57,406 [prior] Evaluating prior at array([0.31257949, 0.49649977])
 2023-07-02 10:34:57,406 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,406 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49649976779902005, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,406 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,406 [classy] Re-using computed results
 2023-07-02 10:34:57,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
 2023-07-02 10:34:57,407 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,407 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49649976779902005, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,407 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,426 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70667
 2023-07-02 10:34:57,426 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,427 [mcmc] New sample, #927:
   Omega_m:0.3125795, b1:0.4973932
 2023-07-02 10:34:57,427 [model] Posterior to be computed for parameters {'Omega_m': 0.319789746535691, 'b1': 0.4833594962683414}
 2023-07-02 10:34:57,427 [prior] Evaluating prior at array([0.31978975, 0.4833595 ])
 2023-07-02 10:34:57,427 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,427 [model] Got input parameters: {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4833594962683414, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,427 [classy] Got parameters {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,427 [classy] Computing new state
 2023-07-02 10:34:57,427 [classy] Setting parameters: {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,473 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.39007672916026}
 2023-07-02 10:34:57,473 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,475 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00341644
 2023-07-02 10:34:57,475 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4833594962683414, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,475 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,495 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62536
 2023-07-02 10:34:57,495 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,495 [mcmc] New sample, #928:
   Omega_m:0.3125795, b1:0.4964998
 2023-07-02 10:34:57,495 [model] Posterior to be computed for parameters {'Omega_m': 0.319789746535691, 'b1': 0.5118434622868515}
 2023-07-02 10:34:57,495 [prior] Evaluating prior at array([0.31978975, 0.51184346])
 2023-07-02 10:34:57,495 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,495 [model] Got input parameters: {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5118434622868515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,495 [classy] Got parameters {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,495 [classy] Re-using computed results
 2023-07-02 10:34:57,496 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.39007672916026}
 2023-07-02 10:34:57,496 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5118434622868515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,496 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,515 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.68377
 2023-07-02 10:34:57,515 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,515 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.4966207322793239}
 2023-07-02 10:34:57,515 [prior] Evaluating prior at array([0.31251312, 0.49662073])
 2023-07-02 10:34:57,515 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,515 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4966207322793239, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,515 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,515 [classy] Computing new state
 2023-07-02 10:34:57,515 [classy] Setting parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
 2023-07-02 10:34:57,562 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,563 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202426
 2023-07-02 10:34:57,563 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4966207322793239, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,564 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,583 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.7047
 2023-07-02 10:34:57,583 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,584 [mcmc] New sample, #929:
   Omega_m:0.3197897, b1:0.4833595
 2023-07-02 10:34:57,584 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.6164771075552855}
 2023-07-02 10:34:57,584 [prior] Evaluating prior at array([0.31251312, 0.61647711])
 2023-07-02 10:34:57,584 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,584 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6164771075552855, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,584 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,584 [classy] Re-using computed results
 2023-07-02 10:34:57,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
 2023-07-02 10:34:57,584 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6164771075552855, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,584 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,604 [fs_likelihood.fslikelihood] Computed log-likelihood = -34.5128
 2023-07-02 10:34:57,604 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,604 [model] Posterior to be computed for parameters {'Omega_m': 0.28254430332141295, 'b1': 0.551237184357411}
 2023-07-02 10:34:57,604 [prior] Evaluating prior at array([0.2825443 , 0.55123718])
 2023-07-02 10:34:57,604 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,604 [model] Got input parameters: {'Omega_m': 0.28254430332141295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.551237184357411, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,604 [classy] Got parameters {'Omega_m': 0.28254430332141295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,604 [classy] Computing new state
 2023-07-02 10:34:57,604 [classy] Setting parameters: {'Omega_m': 0.28254430332141295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.02399761996173}
 2023-07-02 10:34:57,650 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.059553
 2023-07-02 10:34:57,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.551237184357411, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,652 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,672 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.10833
 2023-07-02 10:34:57,672 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,672 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.47333212420387244}
 2023-07-02 10:34:57,672 [prior] Evaluating prior at array([0.31251312, 0.47333212])
 2023-07-02 10:34:57,672 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,672 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47333212420387244, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,672 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,672 [classy] Re-using computed results
 2023-07-02 10:34:57,672 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
 2023-07-02 10:34:57,672 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,672 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47333212420387244, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,672 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.295426
 2023-07-02 10:34:57,692 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,692 [mcmc] New sample, #930:
   Omega_m:0.3125131, b1:0.4966207
 2023-07-02 10:34:57,692 [model] Posterior to be computed for parameters {'Omega_m': 0.24658207735023285, 'b1': 0.5934876744050994}
 2023-07-02 10:34:57,692 [prior] Evaluating prior at array([0.24658208, 0.59348767])
 2023-07-02 10:34:57,692 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,692 [model] Got input parameters: {'Omega_m': 0.24658207735023285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5934876744050994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,693 [classy] Got parameters {'Omega_m': 0.24658207735023285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,693 [classy] Computing new state
 2023-07-02 10:34:57,693 [classy] Setting parameters: {'Omega_m': 0.24658207735023285, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,738 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.02585195259576}
 2023-07-02 10:34:57,738 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,740 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.31759
 2023-07-02 10:34:57,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5934876744050994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,740 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,760 [fs_likelihood.fslikelihood] Computed log-likelihood = -34.3861
 2023-07-02 10:34:57,760 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,760 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.4687440869847858}
 2023-07-02 10:34:57,760 [prior] Evaluating prior at array([0.31251312, 0.46874409])
 2023-07-02 10:34:57,760 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,760 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4687440869847858, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,760 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,760 [classy] Re-using computed results
 2023-07-02 10:34:57,760 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
 2023-07-02 10:34:57,760 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4687440869847858, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,761 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,779 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.497538
 2023-07-02 10:34:57,780 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,780 [model] Posterior to be computed for parameters {'Omega_m': 0.3151508786660436, 'b1': 0.4685249593266609}
 2023-07-02 10:34:57,780 [prior] Evaluating prior at array([0.31515088, 0.46852496])
 2023-07-02 10:34:57,780 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,780 [model] Got input parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4685249593266609, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,780 [classy] Got parameters {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,780 [classy] Computing new state
 2023-07-02 10:34:57,780 [classy] Setting parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94042574594374}
 2023-07-02 10:34:57,827 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,829 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000635729
 2023-07-02 10:34:57,829 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4685249593266609, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,829 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,848 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.326878
 2023-07-02 10:34:57,849 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,849 [mcmc] New sample, #931:
   Omega_m:0.3125131, b1:0.4733321
 2023-07-02 10:34:57,849 [model] Posterior to be computed for parameters {'Omega_m': 0.3151508786660436, 'b1': 0.4288110351036298}
 2023-07-02 10:34:57,849 [prior] Evaluating prior at array([0.31515088, 0.42881104])
 2023-07-02 10:34:57,849 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,849 [model] Got input parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4288110351036298, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,849 [classy] Got parameters {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,849 [classy] Re-using computed results
 2023-07-02 10:34:57,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94042574594374}
 2023-07-02 10:34:57,849 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,849 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4288110351036298, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,849 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,868 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.8119
 2023-07-02 10:34:57,868 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,869 [model] Posterior to be computed for parameters {'Omega_m': 0.29069197469304864, 'b1': 0.5130999116323167}
 2023-07-02 10:34:57,869 [prior] Evaluating prior at array([0.29069197, 0.51309991])
 2023-07-02 10:34:57,869 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,869 [model] Got input parameters: {'Omega_m': 0.29069197469304864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5130999116323167, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,869 [classy] Got parameters {'Omega_m': 0.29069197469304864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,869 [classy] Computing new state
 2023-07-02 10:34:57,869 [classy] Setting parameters: {'Omega_m': 0.29069197469304864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:57,915 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.96652688626705}
 2023-07-02 10:34:57,915 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:57,917 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0309818
 2023-07-02 10:34:57,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5130999116323167, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,917 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,937 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.31883
 2023-07-02 10:34:57,937 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,937 [model] Posterior to be computed for parameters {'Omega_m': 0.3151508786660436, 'b1': 0.5026235491902697}
 2023-07-02 10:34:57,937 [prior] Evaluating prior at array([0.31515088, 0.50262355])
 2023-07-02 10:34:57,938 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,938 [model] Got input parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5026235491902697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,938 [classy] Got parameters {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,938 [classy] Re-using computed results
 2023-07-02 10:34:57,938 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94042574594374}
 2023-07-02 10:34:57,938 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:57,938 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5026235491902697, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,938 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:57,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90916
 2023-07-02 10:34:57,957 [model] Computed derived parameters: {}
 2023-07-02 10:34:57,957 [mcmc] New sample, #932:
   Omega_m:0.3151509, b1:0.468525
 2023-07-02 10:34:57,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5046945678181406}
 2023-07-02 10:34:57,957 [prior] Evaluating prior at array([0.31401448, 0.50469457])
 2023-07-02 10:34:57,958 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:57,958 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5046945678181406, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:57,958 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:57,958 [classy] Computing new state
 2023-07-02 10:34:57,958 [classy] Setting parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
 2023-07-02 10:34:58,004 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,005 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000345525
 2023-07-02 10:34:58,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5046945678181406, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,006 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90125
 2023-07-02 10:34:58,026 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,026 [mcmc] New sample, #933:
   Omega_m:0.3151509, b1:0.5026235
 2023-07-02 10:34:58,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5115241929976359}
 2023-07-02 10:34:58,026 [prior] Evaluating prior at array([0.31401448, 0.51152419])
 2023-07-02 10:34:58,026 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,026 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5115241929976359, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,026 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,026 [classy] Re-using computed results
 2023-07-02 10:34:58,026 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
 2023-07-02 10:34:58,026 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,026 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5115241929976359, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,026 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,046 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67934
 2023-07-02 10:34:58,046 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,046 [mcmc] New sample, #934:
   Omega_m:0.3140145, b1:0.5046946
 2023-07-02 10:34:58,046 [model] Posterior to be computed for parameters {'Omega_m': 0.26682044852420705, 'b1': 0.5975326165582943}
 2023-07-02 10:34:58,046 [prior] Evaluating prior at array([0.26682045, 0.59753262])
 2023-07-02 10:34:58,046 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,046 [model] Got input parameters: {'Omega_m': 0.26682044852420705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5975326165582943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,046 [classy] Got parameters {'Omega_m': 0.26682044852420705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,046 [classy] Computing new state
 2023-07-02 10:34:58,046 [classy] Setting parameters: {'Omega_m': 0.26682044852420705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.1408912535893}
 2023-07-02 10:34:58,093 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,095 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.144217
 2023-07-02 10:34:58,095 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5975326165582943, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,095 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,114 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.4391
 2023-07-02 10:34:58,114 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,114 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.48782023886073606}
 2023-07-02 10:34:58,114 [prior] Evaluating prior at array([0.31401448, 0.48782024])
 2023-07-02 10:34:58,114 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,114 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48782023886073606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,114 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,114 [classy] Re-using computed results
 2023-07-02 10:34:58,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
 2023-07-02 10:34:58,115 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,115 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48782023886073606, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,115 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,137 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37468
 2023-07-02 10:34:58,137 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,137 [mcmc] New sample, #935:
   Omega_m:0.3140145, b1:0.5115242
 2023-07-02 10:34:58,138 [model] Posterior to be computed for parameters {'Omega_m': 0.3517070067979696, 'b1': 0.4191277694205491}
 2023-07-02 10:34:58,138 [prior] Evaluating prior at array([0.35170701, 0.41912777])
 2023-07-02 10:34:58,138 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,138 [model] Got input parameters: {'Omega_m': 0.3517070067979696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4191277694205491, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,138 [classy] Got parameters {'Omega_m': 0.3517070067979696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,138 [classy] Computing new state
 2023-07-02 10:34:58,138 [classy] Setting parameters: {'Omega_m': 0.3517070067979696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.78723074502435}
 2023-07-02 10:34:58,184 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,186 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0860681
 2023-07-02 10:34:58,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4191277694205491, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,186 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,206 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.10164
 2023-07-02 10:34:58,206 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,206 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5183199381294669}
 2023-07-02 10:34:58,206 [prior] Evaluating prior at array([0.31401448, 0.51831994])
 2023-07-02 10:34:58,206 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,206 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183199381294669, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,206 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,206 [classy] Re-using computed results
 2023-07-02 10:34:58,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
 2023-07-02 10:34:58,206 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183199381294669, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,206 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,226 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20204
 2023-07-02 10:34:58,226 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,226 [mcmc] New sample, #936:
   Omega_m:0.3140145, b1:0.4878202
 2023-07-02 10:34:58,226 [model] Posterior to be computed for parameters {'Omega_m': 0.2892358367216956, 'b1': 0.5634775999013308}
 2023-07-02 10:34:58,226 [prior] Evaluating prior at array([0.28923584, 0.5634776 ])
 2023-07-02 10:34:58,227 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,227 [model] Got input parameters: {'Omega_m': 0.2892358367216956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5634775999013308, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,227 [classy] Got parameters {'Omega_m': 0.2892358367216956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,227 [classy] Computing new state
 2023-07-02 10:34:58,227 [classy] Setting parameters: {'Omega_m': 0.2892358367216956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.15361071583703}
 2023-07-02 10:34:58,273 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.035365
 2023-07-02 10:34:58,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5634775999013308, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,275 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,295 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.01219
 2023-07-02 10:34:58,295 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,295 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5664622128634488}
 2023-07-02 10:34:58,295 [prior] Evaluating prior at array([0.31401448, 0.56646221])
 2023-07-02 10:34:58,295 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,295 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5664622128634488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,295 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,295 [classy] Re-using computed results
 2023-07-02 10:34:58,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
 2023-07-02 10:34:58,295 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,296 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5664622128634488, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,296 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,315 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.96109
 2023-07-02 10:34:58,315 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,315 [model] Posterior to be computed for parameters {'Omega_m': 0.30684652847888955, 'b1': 0.531383122323217}
 2023-07-02 10:34:58,315 [prior] Evaluating prior at array([0.30684653, 0.53138312])
 2023-07-02 10:34:58,315 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,315 [model] Got input parameters: {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.531383122323217, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,315 [classy] Got parameters {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,315 [classy] Computing new state
 2023-07-02 10:34:58,315 [classy] Setting parameters: {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.94395169602592}
 2023-07-02 10:34:58,362 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,364 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00217899
 2023-07-02 10:34:58,364 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.531383122323217, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,364 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,383 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.80536
 2023-07-02 10:34:58,383 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,383 [mcmc] New sample, #937:
   Omega_m:0.3140145, b1:0.5183199
 2023-07-02 10:34:58,383 [model] Posterior to be computed for parameters {'Omega_m': 0.30684652847888955, 'b1': 0.6498374805237729}
 2023-07-02 10:34:58,383 [prior] Evaluating prior at array([0.30684653, 0.64983748])
 2023-07-02 10:34:58,383 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,383 [model] Got input parameters: {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6498374805237729, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,383 [classy] Got parameters {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,383 [classy] Re-using computed results
 2023-07-02 10:34:58,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.94395169602592}
 2023-07-02 10:34:58,383 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,383 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6498374805237729, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,383 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,403 [fs_likelihood.fslikelihood] Computed log-likelihood = -52.8192
 2023-07-02 10:34:58,403 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,403 [model] Posterior to be computed for parameters {'Omega_m': 0.32372898396592137, 'b1': 0.5006158136585412}
 2023-07-02 10:34:58,403 [prior] Evaluating prior at array([0.32372898, 0.50061581])
 2023-07-02 10:34:58,403 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,403 [model] Got input parameters: {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5006158136585412, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,403 [classy] Got parameters {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,403 [classy] Computing new state
 2023-07-02 10:34:58,403 [classy] Setting parameters: {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9282812801224}
 2023-07-02 10:34:58,450 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00774416
 2023-07-02 10:34:58,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5006158136585412, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,452 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.815
 2023-07-02 10:34:58,471 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,471 [mcmc] New sample, #938:
   Omega_m:0.3068465, b1:0.5313831
 2023-07-02 10:34:58,472 [model] Posterior to be computed for parameters {'Omega_m': 0.32372898396592137, 'b1': 0.4807382068057356}
 2023-07-02 10:34:58,472 [prior] Evaluating prior at array([0.32372898, 0.48073821])
 2023-07-02 10:34:58,472 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,472 [model] Got input parameters: {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4807382068057356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,472 [classy] Got parameters {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,472 [classy] Re-using computed results
 2023-07-02 10:34:58,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9282812801224}
 2023-07-02 10:34:58,472 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4807382068057356, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,472 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,491 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49294
 2023-07-02 10:34:58,491 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,491 [mcmc] New sample, #939:
   Omega_m:0.323729, b1:0.5006158
 2023-07-02 10:34:58,491 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.49128099403827785}
 2023-07-02 10:34:58,491 [prior] Evaluating prior at array([0.31794401, 0.49128099])
 2023-07-02 10:34:58,491 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,492 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49128099403827785, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,492 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,492 [classy] Computing new state
 2023-07-02 10:34:58,492 [classy] Setting parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
 2023-07-02 10:34:58,538 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,540 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00200583
 2023-07-02 10:34:58,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49128099403827785, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,540 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,559 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8473
 2023-07-02 10:34:58,559 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,559 [mcmc] New sample, #940:
   Omega_m:0.323729, b1:0.4807382
 2023-07-02 10:34:58,559 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.4948832141926568}
 2023-07-02 10:34:58,559 [prior] Evaluating prior at array([0.31794401, 0.49488321])
 2023-07-02 10:34:58,560 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,560 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4948832141926568, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,560 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,560 [classy] Re-using computed results
 2023-07-02 10:34:58,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
 2023-07-02 10:34:58,560 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,560 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4948832141926568, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,560 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,579 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8846
 2023-07-02 10:34:58,579 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,579 [mcmc] New sample, #941:
   Omega_m:0.317944, b1:0.491281
 2023-07-02 10:34:58,579 [model] Posterior to be computed for parameters {'Omega_m': 0.3681249788020542, 'b1': 0.403431267883824}
 2023-07-02 10:34:58,579 [prior] Evaluating prior at array([0.36812498, 0.40343127])
 2023-07-02 10:34:58,579 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,579 [model] Got input parameters: {'Omega_m': 0.3681249788020542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.403431267883824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,580 [classy] Got parameters {'Omega_m': 0.3681249788020542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,580 [classy] Computing new state
 2023-07-02 10:34:58,580 [classy] Setting parameters: {'Omega_m': 0.3681249788020542, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,626 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.04899917801617}
 2023-07-02 10:34:58,626 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,628 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.166646
 2023-07-02 10:34:58,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.403431267883824, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,628 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,647 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.65207
 2023-07-02 10:34:58,647 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.5088235760025143}
 2023-07-02 10:34:58,648 [prior] Evaluating prior at array([0.31794401, 0.50882358])
 2023-07-02 10:34:58,648 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,648 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088235760025143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,648 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,648 [classy] Re-using computed results
 2023-07-02 10:34:58,648 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
 2023-07-02 10:34:58,648 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,648 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088235760025143, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,648 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,667 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36111
 2023-07-02 10:34:58,667 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,667 [model] Posterior to be computed for parameters {'Omega_m': 0.32265933531056656, 'b1': 0.48628980040092334}
 2023-07-02 10:34:58,668 [prior] Evaluating prior at array([0.32265934, 0.4862898 ])
 2023-07-02 10:34:58,668 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,668 [model] Got input parameters: {'Omega_m': 0.32265933531056656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48628980040092334, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,668 [classy] Got parameters {'Omega_m': 0.32265933531056656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,668 [classy] Computing new state
 2023-07-02 10:34:58,668 [classy] Setting parameters: {'Omega_m': 0.32265933531056656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.05317654327308}
 2023-07-02 10:34:58,714 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00639369
 2023-07-02 10:34:58,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48628980040092334, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,716 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,735 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62287
 2023-07-02 10:34:58,735 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,735 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.5657738994267227}
 2023-07-02 10:34:58,736 [prior] Evaluating prior at array([0.31794401, 0.5657739 ])
 2023-07-02 10:34:58,736 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,736 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5657738994267227, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,736 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,736 [classy] Re-using computed results
 2023-07-02 10:34:58,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
 2023-07-02 10:34:58,736 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5657738994267227, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,736 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,756 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.6429
 2023-07-02 10:34:58,756 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,756 [model] Posterior to be computed for parameters {'Omega_m': 0.32174623527477, 'b1': 0.48795387294443815}
 2023-07-02 10:34:58,756 [prior] Evaluating prior at array([0.32174624, 0.48795387])
 2023-07-02 10:34:58,756 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,756 [model] Got input parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48795387294443815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,756 [classy] Got parameters {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,756 [classy] Computing new state
 2023-07-02 10:34:58,756 [classy] Setting parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,802 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1600867707077}
 2023-07-02 10:34:58,802 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,804 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00534378
 2023-07-02 10:34:58,804 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48795387294443815, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,804 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,824 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69172
 2023-07-02 10:34:58,824 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,824 [mcmc] New sample, #942:
   Omega_m:0.317944, b1:0.4948832
 2023-07-02 10:34:58,824 [model] Posterior to be computed for parameters {'Omega_m': 0.32174623527477, 'b1': 0.44707805225816194}
 2023-07-02 10:34:58,824 [prior] Evaluating prior at array([0.32174624, 0.44707805])
 2023-07-02 10:34:58,824 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,824 [model] Got input parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44707805225816194, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,824 [classy] Got parameters {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,824 [classy] Re-using computed results
 2023-07-02 10:34:58,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1600867707077}
 2023-07-02 10:34:58,824 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44707805225816194, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,824 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,844 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.68886
 2023-07-02 10:34:58,844 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,844 [model] Posterior to be computed for parameters {'Omega_m': 0.2925722466695439, 'b1': 0.5411217970705355}
 2023-07-02 10:34:58,844 [prior] Evaluating prior at array([0.29257225, 0.5411218 ])
 2023-07-02 10:34:58,844 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,844 [model] Got input parameters: {'Omega_m': 0.2925722466695439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5411217970705355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,844 [classy] Got parameters {'Omega_m': 0.2925722466695439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,844 [classy] Computing new state
 2023-07-02 10:34:58,844 [classy] Setting parameters: {'Omega_m': 0.2925722466695439, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.72613986876638}
 2023-07-02 10:34:58,890 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0257746
 2023-07-02 10:34:58,892 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5411217970705355, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,892 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,912 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.236634
 2023-07-02 10:34:58,912 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,912 [model] Posterior to be computed for parameters {'Omega_m': 0.32174623527477, 'b1': 0.5087246277457994}
 2023-07-02 10:34:58,912 [prior] Evaluating prior at array([0.32174624, 0.50872463])
 2023-07-02 10:34:58,912 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,912 [model] Got input parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5087246277457994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,913 [classy] Got parameters {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,913 [classy] Re-using computed results
 2023-07-02 10:34:58,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1600867707077}
 2023-07-02 10:34:58,913 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:58,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5087246277457994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,913 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,932 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51426
 2023-07-02 10:34:58,932 [model] Computed derived parameters: {}
 2023-07-02 10:34:58,932 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.4904455827308601}
 2023-07-02 10:34:58,932 [prior] Evaluating prior at array([0.320379  , 0.49044558])
 2023-07-02 10:34:58,932 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:58,932 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904455827308601, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,932 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:58,932 [classy] Computing new state
 2023-07-02 10:34:58,932 [classy] Setting parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:58,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
 2023-07-02 10:34:58,978 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:58,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00395044
 2023-07-02 10:34:58,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904455827308601, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:58,980 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:58,999 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77867
 2023-07-02 10:34:59,000 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,000 [mcmc] New sample, #943:
   Omega_m:0.3217462, b1:0.4879539
 2023-07-02 10:34:59,000 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.5214293341228836}
 2023-07-02 10:34:59,000 [prior] Evaluating prior at array([0.320379  , 0.52142933])
 2023-07-02 10:34:59,000 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,000 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5214293341228836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,000 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,000 [classy] Re-using computed results
 2023-07-02 10:34:59,000 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
 2023-07-02 10:34:59,000 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,000 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5214293341228836, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,000 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,020 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.120101
 2023-07-02 10:34:59,020 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,020 [model] Posterior to be computed for parameters {'Omega_m': 0.2947676002700546, 'b1': 0.5371208908097784}
 2023-07-02 10:34:59,020 [prior] Evaluating prior at array([0.2947676 , 0.53712089])
 2023-07-02 10:34:59,020 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,020 [model] Got input parameters: {'Omega_m': 0.2947676002700546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5371208908097784, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,020 [classy] Got parameters {'Omega_m': 0.2947676002700546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,020 [classy] Computing new state
 2023-07-02 10:34:59,020 [classy] Setting parameters: {'Omega_m': 0.2947676002700546, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,066 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.447163414346}
 2023-07-02 10:34:59,066 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,068 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0203323
 2023-07-02 10:34:59,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5371208908097784, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,068 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,087 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.371203
 2023-07-02 10:34:59,088 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,088 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.45439008736062547}
 2023-07-02 10:34:59,088 [prior] Evaluating prior at array([0.320379  , 0.45439009])
 2023-07-02 10:34:59,088 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,088 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45439008736062547, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,088 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,088 [classy] Re-using computed results
 2023-07-02 10:34:59,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
 2023-07-02 10:34:59,088 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,088 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45439008736062547, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,088 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,108 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.643495
 2023-07-02 10:34:59,108 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,108 [model] Posterior to be computed for parameters {'Omega_m': 0.2964650666802012, 'b1': 0.5340273554511918}
 2023-07-02 10:34:59,108 [prior] Evaluating prior at array([0.29646507, 0.53402736])
 2023-07-02 10:34:59,108 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,108 [model] Got input parameters: {'Omega_m': 0.2964650666802012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5340273554511918, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,108 [classy] Got parameters {'Omega_m': 0.2964650666802012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,108 [classy] Computing new state
 2023-07-02 10:34:59,108 [classy] Setting parameters: {'Omega_m': 0.2964650666802012, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.23268840315893}
 2023-07-02 10:34:59,156 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0165878
 2023-07-02 10:34:59,158 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5340273554511918, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,158 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,177 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.793555
 2023-07-02 10:34:59,177 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,178 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.4905019962733187}
 2023-07-02 10:34:59,178 [prior] Evaluating prior at array([0.320379, 0.490502])
 2023-07-02 10:34:59,178 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,178 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4905019962733187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,178 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,178 [classy] Re-using computed results
 2023-07-02 10:34:59,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
 2023-07-02 10:34:59,178 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,178 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4905019962733187, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,178 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,197 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77871
 2023-07-02 10:34:59,197 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,197 [mcmc] New sample, #944:
   Omega_m:0.320379, b1:0.4904456
 2023-07-02 10:34:59,198 [model] Posterior to be computed for parameters {'Omega_m': 0.33257414615640135, 'b1': 0.4682770387644515}
 2023-07-02 10:34:59,198 [prior] Evaluating prior at array([0.33257415, 0.46827704])
 2023-07-02 10:34:59,198 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,198 [model] Got input parameters: {'Omega_m': 0.33257414615640135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4682770387644515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,198 [classy] Got parameters {'Omega_m': 0.33257414615640135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,198 [classy] Computing new state
 2023-07-02 10:34:59,198 [classy] Setting parameters: {'Omega_m': 0.33257414615640135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,244 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.90947196724966}
 2023-07-02 10:34:59,244 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,246 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0237673
 2023-07-02 10:34:59,246 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4682770387644515, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,246 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,266 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34827
 2023-07-02 10:34:59,266 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,266 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.550886413726468}
 2023-07-02 10:34:59,266 [prior] Evaluating prior at array([0.320379  , 0.55088641])
 2023-07-02 10:34:59,267 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,267 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.550886413726468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,267 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,267 [classy] Re-using computed results
 2023-07-02 10:34:59,267 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
 2023-07-02 10:34:59,267 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.550886413726468, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,267 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,286 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.68463
 2023-07-02 10:34:59,286 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,286 [model] Posterior to be computed for parameters {'Omega_m': 0.35068514710965604, 'b1': 0.43527077631743627}
 2023-07-02 10:34:59,286 [prior] Evaluating prior at array([0.35068515, 0.43527078])
 2023-07-02 10:34:59,287 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,287 [model] Got input parameters: {'Omega_m': 0.35068514710965604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43527077631743627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,287 [classy] Got parameters {'Omega_m': 0.35068514710965604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,287 [classy] Computing new state
 2023-07-02 10:34:59,287 [classy] Setting parameters: {'Omega_m': 0.35068514710965604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.89787727301976}
 2023-07-02 10:34:59,333 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,335 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0818454
 2023-07-02 10:34:59,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43527077631743627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,335 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,354 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.16649
 2023-07-02 10:34:59,354 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,355 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.48286486428411823}
 2023-07-02 10:34:59,355 [prior] Evaluating prior at array([0.320379  , 0.48286486])
 2023-07-02 10:34:59,355 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,355 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48286486428411823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,355 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,355 [classy] Re-using computed results
 2023-07-02 10:34:59,355 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
 2023-07-02 10:34:59,355 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48286486428411823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,355 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,375 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61846
 2023-07-02 10:34:59,375 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,375 [mcmc] New sample, #945:
   Omega_m:0.320379, b1:0.490502
 2023-07-02 10:34:59,375 [model] Posterior to be computed for parameters {'Omega_m': 0.3234756058436151, 'b1': 0.4772214756362809}
 2023-07-02 10:34:59,375 [prior] Evaluating prior at array([0.32347561, 0.47722148])
 2023-07-02 10:34:59,375 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,375 [model] Got input parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4772214756362809, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,375 [classy] Got parameters {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,375 [classy] Computing new state
 2023-07-02 10:34:59,375 [classy] Setting parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95783234985123}
 2023-07-02 10:34:59,421 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,424 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00741257
 2023-07-02 10:34:59,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4772214756362809, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,424 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,443 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39233
 2023-07-02 10:34:59,443 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,443 [mcmc] New sample, #946:
   Omega_m:0.320379, b1:0.4828649
 2023-07-02 10:34:59,443 [model] Posterior to be computed for parameters {'Omega_m': 0.3234756058436151, 'b1': 0.5048033044830001}
 2023-07-02 10:34:59,443 [prior] Evaluating prior at array([0.32347561, 0.5048033 ])
 2023-07-02 10:34:59,444 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,444 [model] Got input parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5048033044830001, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,444 [classy] Got parameters {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,444 [classy] Re-using computed results
 2023-07-02 10:34:59,444 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95783234985123}
 2023-07-02 10:34:59,444 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,444 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5048033044830001, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,444 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,463 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.4638
 2023-07-02 10:34:59,463 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,463 [model] Posterior to be computed for parameters {'Omega_m': 0.3004175666242476, 'b1': 0.5192434321229679}
 2023-07-02 10:34:59,463 [prior] Evaluating prior at array([0.30041757, 0.51924343])
 2023-07-02 10:34:59,464 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,464 [model] Got input parameters: {'Omega_m': 0.3004175666242476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5192434321229679, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,464 [classy] Got parameters {'Omega_m': 0.3004175666242476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,464 [classy] Computing new state
 2023-07-02 10:34:59,464 [classy] Setting parameters: {'Omega_m': 0.3004175666242476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73740313994543}
 2023-07-02 10:34:59,510 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0094054
 2023-07-02 10:34:59,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5192434321229679, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,512 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,531 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46916
 2023-07-02 10:34:59,531 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3234756058436151, 'b1': 0.5187277456752967}
 2023-07-02 10:34:59,531 [prior] Evaluating prior at array([0.32347561, 0.51872775])
 2023-07-02 10:34:59,531 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,531 [model] Got input parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187277456752967, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,531 [classy] Got parameters {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,531 [classy] Re-using computed results
 2023-07-02 10:34:59,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95783234985123}
 2023-07-02 10:34:59,532 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187277456752967, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,532 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.648973
 2023-07-02 10:34:59,551 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,551 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5116768239683916}
 2023-07-02 10:34:59,551 [prior] Evaluating prior at array([0.30456947, 0.51167682])
 2023-07-02 10:34:59,551 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,551 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5116768239683916, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,551 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,551 [classy] Computing new state
 2023-07-02 10:34:59,551 [classy] Setting parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
 2023-07-02 10:34:59,598 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00412055
 2023-07-02 10:34:59,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5116768239683916, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,600 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,620 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.10986
 2023-07-02 10:34:59,620 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,620 [mcmc] New sample, #947:
   Omega_m:0.3234756, b1:0.4772215
 2023-07-02 10:34:59,620 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5028672693299461}
 2023-07-02 10:34:59,620 [prior] Evaluating prior at array([0.30456947, 0.50286727])
 2023-07-02 10:34:59,620 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,620 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5028672693299461, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,620 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,620 [classy] Re-using computed results
 2023-07-02 10:34:59,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
 2023-07-02 10:34:59,620 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5028672693299461, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,620 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,641 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.55545
 2023-07-02 10:34:59,641 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,641 [mcmc] New sample, #948:
   Omega_m:0.3045695, b1:0.5116768
 2023-07-02 10:34:59,642 [model] Posterior to be computed for parameters {'Omega_m': 0.18885511485918938, 'b1': 0.7137500592733739}
 2023-07-02 10:34:59,642 [prior] Evaluating prior at array([0.18885511, 0.71375006])
 2023-07-02 10:34:59,642 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,642 [model] Got input parameters: {'Omega_m': 0.18885511485918938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7137500592733739, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,642 [classy] Got parameters {'Omega_m': 0.18885511485918938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,642 [classy] Computing new state
 2023-07-02 10:34:59,642 [classy] Setting parameters: {'Omega_m': 0.18885511485918938, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.45557729054994}
 2023-07-02 10:34:59,688 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,691 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.33302
 2023-07-02 10:34:59,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7137500592733739, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,691 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,711 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.682
 2023-07-02 10:34:59,711 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,711 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5194528022366278}
 2023-07-02 10:34:59,711 [prior] Evaluating prior at array([0.30456947, 0.5194528 ])
 2023-07-02 10:34:59,711 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,711 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5194528022366278, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,711 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,711 [classy] Re-using computed results
 2023-07-02 10:34:59,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
 2023-07-02 10:34:59,712 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,712 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5194528022366278, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,712 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,732 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26327
 2023-07-02 10:34:59,732 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,732 [mcmc] New sample, #949:
   Omega_m:0.3045695, b1:0.5028673
 2023-07-02 10:34:59,732 [model] Posterior to be computed for parameters {'Omega_m': 0.3032972267396811, 'b1': 0.5217713946811106}
 2023-07-02 10:34:59,732 [prior] Evaluating prior at array([0.30329723, 0.52177139])
 2023-07-02 10:34:59,733 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,733 [model] Got input parameters: {'Omega_m': 0.3032972267396811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5217713946811106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,733 [classy] Got parameters {'Omega_m': 0.3032972267396811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,733 [classy] Computing new state
 2023-07-02 10:34:59,733 [classy] Setting parameters: {'Omega_m': 0.3032972267396811, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.38017906821975}
 2023-07-02 10:34:59,779 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00549835
 2023-07-02 10:34:59,781 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5217713946811106, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,781 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,801 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09037
 2023-07-02 10:34:59,801 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,801 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.4985005612742212}
 2023-07-02 10:34:59,801 [prior] Evaluating prior at array([0.30456947, 0.49850056])
 2023-07-02 10:34:59,801 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,801 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4985005612742212, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,801 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,801 [classy] Re-using computed results
 2023-07-02 10:34:59,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
 2023-07-02 10:34:59,801 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,801 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4985005612742212, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,801 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,821 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.13392
 2023-07-02 10:34:59,821 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,821 [mcmc] New sample, #950:
   Omega_m:0.3045695, b1:0.5194528
 2023-07-02 10:34:59,821 [model] Posterior to be computed for parameters {'Omega_m': 0.374046193561705, 'b1': 0.3718832118119013}
 2023-07-02 10:34:59,821 [prior] Evaluating prior at array([0.37404619, 0.37188321])
 2023-07-02 10:34:59,821 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,821 [model] Got input parameters: {'Omega_m': 0.374046193561705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3718832118119013, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,822 [classy] Got parameters {'Omega_m': 0.374046193561705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,822 [classy] Computing new state
 2023-07-02 10:34:59,822 [classy] Setting parameters: {'Omega_m': 0.374046193561705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.43969895255898}
 2023-07-02 10:34:59,868 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,870 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.201278
 2023-07-02 10:34:59,870 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3718832118119013, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,870 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,889 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.6095
 2023-07-02 10:34:59,889 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,889 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5023366746563164}
 2023-07-02 10:34:59,889 [prior] Evaluating prior at array([0.30456947, 0.50233667])
 2023-07-02 10:34:59,890 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,890 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5023366746563164, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,890 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,890 [classy] Re-using computed results
 2023-07-02 10:34:59,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
 2023-07-02 10:34:59,890 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,890 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5023366746563164, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,890 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,909 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.50937
 2023-07-02 10:34:59,909 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,909 [mcmc] New sample, #951:
   Omega_m:0.3045695, b1:0.4985006
 2023-07-02 10:34:59,909 [model] Posterior to be computed for parameters {'Omega_m': 0.28333107173276495, 'b1': 0.541042441609651}
 2023-07-02 10:34:59,909 [prior] Evaluating prior at array([0.28333107, 0.54104244])
 2023-07-02 10:34:59,909 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,909 [model] Got input parameters: {'Omega_m': 0.28333107173276495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.541042441609651, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,909 [classy] Got parameters {'Omega_m': 0.28333107173276495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,909 [classy] Computing new state
 2023-07-02 10:34:59,910 [classy] Setting parameters: {'Omega_m': 0.28333107173276495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:34:59,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.92073736057338}
 2023-07-02 10:34:59,958 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:34:59,961 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563575
 2023-07-02 10:34:59,961 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.541042441609651, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,961 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:34:59,986 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.3133
 2023-07-02 10:34:59,987 [model] Computed derived parameters: {}
 2023-07-02 10:34:59,987 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.4845369682538885}
 2023-07-02 10:34:59,987 [prior] Evaluating prior at array([0.30456947, 0.48453697])
 2023-07-02 10:34:59,987 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:34:59,987 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4845369682538885, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,987 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:34:59,987 [classy] Re-using computed results
 2023-07-02 10:34:59,987 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
 2023-07-02 10:34:59,987 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:34:59,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4845369682538885, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:34:59,987 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,007 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.848771
 2023-07-02 10:35:00,007 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,007 [model] Posterior to be computed for parameters {'Omega_m': 0.3252451223500369, 'b1': 0.4646564837897688}
 2023-07-02 10:35:00,007 [prior] Evaluating prior at array([0.32524512, 0.46465648])
 2023-07-02 10:35:00,007 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,008 [model] Got input parameters: {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4646564837897688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,008 [classy] Got parameters {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,008 [classy] Computing new state
 2023-07-02 10:35:00,008 [classy] Setting parameters: {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7518816123588}
 2023-07-02 10:35:00,065 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,068 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0098794
 2023-07-02 10:35:00,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4646564837897688, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,068 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,092 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59947
 2023-07-02 10:35:00,092 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,092 [mcmc] New sample, #952:
   Omega_m:0.3045695, b1:0.5023367
 2023-07-02 10:35:00,092 [model] Posterior to be computed for parameters {'Omega_m': 0.3252451223500369, 'b1': 0.4179342487131231}
 2023-07-02 10:35:00,092 [prior] Evaluating prior at array([0.32524512, 0.41793425])
 2023-07-02 10:35:00,092 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,092 [model] Got input parameters: {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4179342487131231, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,092 [classy] Got parameters {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,092 [classy] Re-using computed results
 2023-07-02 10:35:00,092 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7518816123588}
 2023-07-02 10:35:00,092 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4179342487131231, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,092 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,116 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.00712
 2023-07-02 10:35:00,116 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,116 [model] Posterior to be computed for parameters {'Omega_m': 0.34225051421036184, 'b1': 0.4336651306224357}
 2023-07-02 10:35:00,116 [prior] Evaluating prior at array([0.34225051, 0.43366513])
 2023-07-02 10:35:00,116 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,116 [model] Got input parameters: {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4336651306224357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,116 [classy] Got parameters {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,116 [classy] Computing new state
 2023-07-02 10:35:00,116 [classy] Setting parameters: {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,174 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8226264233208}
 2023-07-02 10:35:00,174 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,176 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0507595
 2023-07-02 10:35:00,176 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4336651306224357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,176 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,197 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.56126
 2023-07-02 10:35:00,197 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,197 [mcmc] New sample, #953:
   Omega_m:0.3252451, b1:0.4646565
 2023-07-02 10:35:00,197 [model] Posterior to be computed for parameters {'Omega_m': 0.34225051421036184, 'b1': 0.41610957698224155}
 2023-07-02 10:35:00,197 [prior] Evaluating prior at array([0.34225051, 0.41610958])
 2023-07-02 10:35:00,197 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,197 [model] Got input parameters: {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41610957698224155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,197 [classy] Got parameters {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,197 [classy] Re-using computed results
 2023-07-02 10:35:00,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8226264233208}
 2023-07-02 10:35:00,197 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41610957698224155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,198 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,217 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.99086
 2023-07-02 10:35:00,217 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,217 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.43063747467616165}
 2023-07-02 10:35:00,217 [prior] Evaluating prior at array([0.34391183, 0.43063747])
 2023-07-02 10:35:00,218 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,218 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43063747467616165, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,218 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,218 [classy] Computing new state
 2023-07-02 10:35:00,218 [classy] Setting parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,265 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,267 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563416
 2023-07-02 10:35:00,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43063747467616165, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,267 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.00108
 2023-07-02 10:35:00,287 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,287 [mcmc] New sample, #954:
   Omega_m:0.3422505, b1:0.4336651
 2023-07-02 10:35:00,287 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.44631008503555586}
 2023-07-02 10:35:00,287 [prior] Evaluating prior at array([0.34391183, 0.44631009])
 2023-07-02 10:35:00,287 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,287 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44631008503555586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,287 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,287 [classy] Re-using computed results
 2023-07-02 10:35:00,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,287 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44631008503555586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,287 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,306 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.18739
 2023-07-02 10:35:00,306 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,307 [mcmc] New sample, #955:
   Omega_m:0.3439118, b1:0.4306375
 2023-07-02 10:35:00,307 [model] Posterior to be computed for parameters {'Omega_m': 0.3572801093990901, 'b1': 0.42194716414116035}
 2023-07-02 10:35:00,307 [prior] Evaluating prior at array([0.35728011, 0.42194716])
 2023-07-02 10:35:00,307 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,307 [model] Got input parameters: {'Omega_m': 0.3572801093990901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42194716414116035, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,307 [classy] Got parameters {'Omega_m': 0.3572801093990901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,307 [classy] Computing new state
 2023-07-02 10:35:00,307 [classy] Setting parameters: {'Omega_m': 0.3572801093990901, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.18891788405568}
 2023-07-02 10:35:00,354 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,355 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.110776
 2023-07-02 10:35:00,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42194716414116035, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,356 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,375 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.41395
 2023-07-02 10:35:00,375 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,375 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.453027820860188}
 2023-07-02 10:35:00,376 [prior] Evaluating prior at array([0.34391183, 0.45302782])
 2023-07-02 10:35:00,376 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,376 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.453027820860188, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,376 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,376 [classy] Re-using computed results
 2023-07-02 10:35:00,376 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,376 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,376 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.453027820860188, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,376 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,395 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.24829
 2023-07-02 10:35:00,396 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,396 [mcmc] New sample, #956:
   Omega_m:0.3439118, b1:0.4463101
 2023-07-02 10:35:00,396 [model] Posterior to be computed for parameters {'Omega_m': 0.37981271141340484, 'b1': 0.38760052270590584}
 2023-07-02 10:35:00,396 [prior] Evaluating prior at array([0.37981271, 0.38760052])
 2023-07-02 10:35:00,396 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,396 [model] Got input parameters: {'Omega_m': 0.37981271141340484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38760052270590584, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,396 [classy] Got parameters {'Omega_m': 0.37981271141340484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,396 [classy] Computing new state
 2023-07-02 10:35:00,396 [classy] Setting parameters: {'Omega_m': 0.37981271141340484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,444 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.85495459780157}
 2023-07-02 10:35:00,444 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,446 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.237658
 2023-07-02 10:35:00,446 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38760052270590584, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,446 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.9264
 2023-07-02 10:35:00,471 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,471 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.3967952562619351}
 2023-07-02 10:35:00,471 [prior] Evaluating prior at array([0.34391183, 0.39679526])
 2023-07-02 10:35:00,472 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,472 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3967952562619351, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,472 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,472 [classy] Re-using computed results
 2023-07-02 10:35:00,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,472 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3967952562619351, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,472 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,492 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.06345
 2023-07-02 10:35:00,492 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,492 [model] Posterior to be computed for parameters {'Omega_m': 0.3620342826907217, 'b1': 0.42000069130128004}
 2023-07-02 10:35:00,492 [prior] Evaluating prior at array([0.36203428, 0.42000069])
 2023-07-02 10:35:00,492 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,492 [model] Got input parameters: {'Omega_m': 0.3620342826907217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42000069130128004, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,492 [classy] Got parameters {'Omega_m': 0.3620342826907217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,492 [classy] Computing new state
 2023-07-02 10:35:00,492 [classy] Setting parameters: {'Omega_m': 0.3620342826907217, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.68529669951477}
 2023-07-02 10:35:00,539 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.134033
 2023-07-02 10:35:00,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42000069130128004, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,541 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,560 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.23591
 2023-07-02 10:35:00,560 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,560 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.4967319317580447}
 2023-07-02 10:35:00,560 [prior] Evaluating prior at array([0.34391183, 0.49673193])
 2023-07-02 10:35:00,560 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,560 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4967319317580447, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,561 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,561 [classy] Re-using computed results
 2023-07-02 10:35:00,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,561 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4967319317580447, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,561 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,580 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.06149
 2023-07-02 10:35:00,580 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3633015772324064, 'b1': 0.4176911195471579}
 2023-07-02 10:35:00,581 [prior] Evaluating prior at array([0.36330158, 0.41769112])
 2023-07-02 10:35:00,581 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,581 [model] Got input parameters: {'Omega_m': 0.3633015772324064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4176911195471579, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,581 [classy] Got parameters {'Omega_m': 0.3633015772324064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,581 [classy] Computing new state
 2023-07-02 10:35:00,581 [classy] Setting parameters: {'Omega_m': 0.3633015772324064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.55209103885187}
 2023-07-02 10:35:00,628 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140561
 2023-07-02 10:35:00,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4176911195471579, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,630 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,650 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.73111
 2023-07-02 10:35:00,651 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,651 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.4473157840079476}
 2023-07-02 10:35:00,651 [prior] Evaluating prior at array([0.34391183, 0.44731578])
 2023-07-02 10:35:00,651 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,651 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4473157840079476, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,651 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,651 [classy] Re-using computed results
 2023-07-02 10:35:00,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,651 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,651 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4473157840079476, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,651 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,671 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.18059
 2023-07-02 10:35:00,671 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,671 [mcmc] New sample, #957:
   Omega_m:0.3439118, b1:0.4530278
 2023-07-02 10:35:00,671 [model] Posterior to be computed for parameters {'Omega_m': 0.3690627822716684, 'b1': 0.40147961631932905}
 2023-07-02 10:35:00,671 [prior] Evaluating prior at array([0.36906278, 0.40147962])
 2023-07-02 10:35:00,671 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,671 [model] Got input parameters: {'Omega_m': 0.3690627822716684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40147961631932905, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,671 [classy] Got parameters {'Omega_m': 0.3690627822716684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,671 [classy] Computing new state
 2023-07-02 10:35:00,671 [classy] Setting parameters: {'Omega_m': 0.3690627822716684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.9518939290794}
 2023-07-02 10:35:00,718 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,720 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.171942
 2023-07-02 10:35:00,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40147961631932905, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,720 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,740 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.0515
 2023-07-02 10:35:00,740 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,740 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.4403018250061556}
 2023-07-02 10:35:00,740 [prior] Evaluating prior at array([0.34391183, 0.44030183])
 2023-07-02 10:35:00,740 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,740 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4403018250061556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,741 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,741 [classy] Re-using computed results
 2023-07-02 10:35:00,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,741 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4403018250061556, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,741 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,760 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.34324
 2023-07-02 10:35:00,760 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,760 [mcmc] New sample, #958:
   Omega_m:0.3439118, b1:0.4473158
 2023-07-02 10:35:00,760 [model] Posterior to be computed for parameters {'Omega_m': 0.28184214164034893, 'b1': 0.5534202817971291}
 2023-07-02 10:35:00,761 [prior] Evaluating prior at array([0.28184214, 0.55342028])
 2023-07-02 10:35:00,761 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,761 [model] Got input parameters: {'Omega_m': 0.28184214164034893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5534202817971291, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,761 [classy] Got parameters {'Omega_m': 0.28184214164034893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,761 [classy] Computing new state
 2023-07-02 10:35:00,761 [classy] Setting parameters: {'Omega_m': 0.28184214164034893, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.11635617958532}
 2023-07-02 10:35:00,807 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,809 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0624849
 2023-07-02 10:35:00,809 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5534202817971291, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,809 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.39263
 2023-07-02 10:35:00,829 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,829 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.41762693273368745}
 2023-07-02 10:35:00,829 [prior] Evaluating prior at array([0.34391183, 0.41762693])
 2023-07-02 10:35:00,829 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,829 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41762693273368745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,829 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,829 [classy] Re-using computed results
 2023-07-02 10:35:00,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
 2023-07-02 10:35:00,829 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,829 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41762693273368745, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,829 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,850 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.65642
 2023-07-02 10:35:00,851 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,851 [model] Posterior to be computed for parameters {'Omega_m': 0.32260084639624564, 'b1': 0.47913987567016814}
 2023-07-02 10:35:00,851 [prior] Evaluating prior at array([0.32260085, 0.47913988])
 2023-07-02 10:35:00,851 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,851 [model] Got input parameters: {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47913987567016814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,851 [classy] Got parameters {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,851 [classy] Computing new state
 2023-07-02 10:35:00,851 [classy] Setting parameters: {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06001653484864}
 2023-07-02 10:35:00,898 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00632359
 2023-07-02 10:35:00,900 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47913987567016814, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,900 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,920 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4794
 2023-07-02 10:35:00,920 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,920 [mcmc] New sample, #959:
   Omega_m:0.3439118, b1:0.4403018
 2023-07-02 10:35:00,920 [model] Posterior to be computed for parameters {'Omega_m': 0.32260084639624564, 'b1': 0.5162728903924283}
 2023-07-02 10:35:00,920 [prior] Evaluating prior at array([0.32260085, 0.51627289])
 2023-07-02 10:35:00,920 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,920 [model] Got input parameters: {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5162728903924283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,920 [classy] Got parameters {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,920 [classy] Re-using computed results
 2023-07-02 10:35:00,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06001653484864}
 2023-07-02 10:35:00,920 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:00,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5162728903924283, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,920 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:00,941 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.157369
 2023-07-02 10:35:00,941 [model] Computed derived parameters: {}
 2023-07-02 10:35:00,941 [model] Posterior to be computed for parameters {'Omega_m': 0.3266058985391776, 'b1': 0.4718408974146434}
 2023-07-02 10:35:00,941 [prior] Evaluating prior at array([0.3266059, 0.4718409])
 2023-07-02 10:35:00,941 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:00,941 [model] Got input parameters: {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4718408974146434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,941 [classy] Got parameters {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:00,941 [classy] Computing new state
 2023-07-02 10:35:00,941 [classy] Setting parameters: {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:00,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5941816974159}
 2023-07-02 10:35:00,988 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:00,989 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0120145
 2023-07-02 10:35:00,989 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4718408974146434, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:00,989 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,009 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07841
 2023-07-02 10:35:01,009 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,009 [mcmc] New sample, #960:
   Omega_m:0.3226008, b1:0.4791399
 2023-07-02 10:35:01,009 [mcmc] Learn + convergence test @ 960 samples accepted.
 2023-07-02 10:35:01,009 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:35:01,014 [mcmc]  - Acceptance rate: 0.456
 2023-07-02 10:35:01,015 [mcmc]  - Condition number = 26.81
 2023-07-02 10:35:01,015 [mcmc]  - Eigenvalues = array([0.00179519, 0.04812897])
 2023-07-02 10:35:01,015 [mcmc]  - Convergence of means: R-1 = 0.048129 after 768 accepted steps
 2023-07-02 10:35:01,015 [mcmc]  - Updated covariance matrix of proposal pdf.
 2023-07-02 10:35:01,015 [mcmc] array([[ 0.00010512, -0.0001918 ],
       [-0.0001918 ,  0.00052479]])
 2023-07-02 10:35:01,025 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:35:01,025 [model] Posterior to be computed for parameters {'Omega_m': 0.3266058985391776, 'b1': 0.48684714590634703}
 2023-07-02 10:35:01,025 [prior] Evaluating prior at array([0.3266059 , 0.48684715])
 2023-07-02 10:35:01,025 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,025 [model] Got input parameters: {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48684714590634703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,025 [classy] Got parameters {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,025 [classy] Re-using computed results
 2023-07-02 10:35:01,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5941816974159}
 2023-07-02 10:35:01,025 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48684714590634703, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,025 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,048 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07221
 2023-07-02 10:35:01,048 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,048 [mcmc] New sample, #961:
   Omega_m:0.3266059, b1:0.4718409
 2023-07-02 10:35:01,048 [model] Posterior to be computed for parameters {'Omega_m': 0.3153990271038461, 'b1': 0.5072960797137092}
 2023-07-02 10:35:01,048 [prior] Evaluating prior at array([0.31539903, 0.50729608])
 2023-07-02 10:35:01,048 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,048 [model] Got input parameters: {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5072960797137092, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,048 [classy] Got parameters {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,048 [classy] Computing new state
 2023-07-02 10:35:01,048 [classy] Setting parameters: {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9108019604391}
 2023-07-02 10:35:01,096 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000719795
 2023-07-02 10:35:01,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5072960797137092, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,098 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.7665
 2023-07-02 10:35:01,117 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,117 [mcmc] New sample, #962:
   Omega_m:0.3266059, b1:0.4868471
 2023-07-02 10:35:01,118 [model] Posterior to be computed for parameters {'Omega_m': 0.3153990271038461, 'b1': 0.4971942161608111}
 2023-07-02 10:35:01,118 [prior] Evaluating prior at array([0.31539903, 0.49719422])
 2023-07-02 10:35:01,118 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,118 [model] Got input parameters: {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4971942161608111, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,118 [classy] Got parameters {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,118 [classy] Re-using computed results
 2023-07-02 10:35:01,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9108019604391}
 2023-07-02 10:35:01,118 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4971942161608111, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,118 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91061
 2023-07-02 10:35:01,141 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,141 [mcmc] New sample, #963:
   Omega_m:0.315399, b1:0.5072961
 2023-07-02 10:35:01,141 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.46788569445147027}
 2023-07-02 10:35:01,141 [prior] Evaluating prior at array([0.33146132, 0.46788569])
 2023-07-02 10:35:01,141 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,141 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46788569445147027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,142 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,142 [classy] Computing new state
 2023-07-02 10:35:01,142 [classy] Setting parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,188 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
 2023-07-02 10:35:01,188 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,190 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0212855
 2023-07-02 10:35:01,190 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46788569445147027, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,190 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,209 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51873
 2023-07-02 10:35:01,209 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,209 [mcmc] New sample, #964:
   Omega_m:0.315399, b1:0.4971942
 2023-07-02 10:35:01,209 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.48839232369723584}
 2023-07-02 10:35:01,210 [prior] Evaluating prior at array([0.33146132, 0.48839232])
 2023-07-02 10:35:01,210 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,210 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48839232369723584, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,210 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,210 [classy] Re-using computed results
 2023-07-02 10:35:01,210 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
 2023-07-02 10:35:01,210 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,210 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48839232369723584, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,210 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,229 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.646335
 2023-07-02 10:35:01,229 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,229 [model] Posterior to be computed for parameters {'Omega_m': 0.36292155635551965, 'b1': 0.4104808938358857}
 2023-07-02 10:35:01,229 [prior] Evaluating prior at array([0.36292156, 0.41048089])
 2023-07-02 10:35:01,229 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,229 [model] Got input parameters: {'Omega_m': 0.36292155635551965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4104808938358857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,230 [classy] Got parameters {'Omega_m': 0.36292155635551965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,230 [classy] Computing new state
 2023-07-02 10:35:01,230 [classy] Setting parameters: {'Omega_m': 0.36292155635551965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.59198852385637}
 2023-07-02 10:35:01,276 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138589
 2023-07-02 10:35:01,278 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4104808938358857, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,278 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,298 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.56235
 2023-07-02 10:35:01,298 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,298 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.4513028752252615}
 2023-07-02 10:35:01,298 [prior] Evaluating prior at array([0.33146132, 0.45130288])
 2023-07-02 10:35:01,298 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,298 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4513028752252615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,298 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,298 [classy] Re-using computed results
 2023-07-02 10:35:01,299 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
 2023-07-02 10:35:01,299 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,299 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4513028752252615, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,299 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,318 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.547978
 2023-07-02 10:35:01,318 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,318 [mcmc] New sample, #965:
   Omega_m:0.3314613, b1:0.4678857
 2023-07-02 10:35:01,318 [model] Posterior to be computed for parameters {'Omega_m': 0.3450222149474701, 'b1': 0.4265586123664174}
 2023-07-02 10:35:01,318 [prior] Evaluating prior at array([0.34502221, 0.42655861])
 2023-07-02 10:35:01,318 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,318 [model] Got input parameters: {'Omega_m': 0.3450222149474701, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4265586123664174, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,318 [classy] Got parameters {'Omega_m': 0.3450222149474701, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,319 [classy] Computing new state
 2023-07-02 10:35:01,319 [classy] Setting parameters: {'Omega_m': 0.3450222149474701, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.5164492143454}
 2023-07-02 10:35:01,365 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,367 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0602224
 2023-07-02 10:35:01,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4265586123664174, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,367 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,386 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.51079
 2023-07-02 10:35:01,386 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,387 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.400922548011895}
 2023-07-02 10:35:01,387 [prior] Evaluating prior at array([0.33146132, 0.40092255])
 2023-07-02 10:35:01,387 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,387 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.400922548011895, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,387 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,387 [classy] Re-using computed results
 2023-07-02 10:35:01,387 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
 2023-07-02 10:35:01,387 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.400922548011895, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,387 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,406 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.8001
 2023-07-02 10:35:01,407 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.4564564802774982}
 2023-07-02 10:35:01,407 [prior] Evaluating prior at array([0.32863693, 0.45645648])
 2023-07-02 10:35:01,407 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,407 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4564564802774982, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,407 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,407 [classy] Computing new state
 2023-07-02 10:35:01,407 [classy] Setting parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,453 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
 2023-07-02 10:35:01,453 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,455 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0155813
 2023-07-02 10:35:01,455 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4564564802774982, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,455 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,475 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.98364
 2023-07-02 10:35:01,475 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,475 [mcmc] New sample, #966:
   Omega_m:0.3314613, b1:0.4513029
 2023-07-02 10:35:01,475 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.438528350959547}
 2023-07-02 10:35:01,475 [prior] Evaluating prior at array([0.32863693, 0.43852835])
 2023-07-02 10:35:01,475 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,475 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.438528350959547, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,475 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,475 [classy] Re-using computed results
 2023-07-02 10:35:01,475 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
 2023-07-02 10:35:01,475 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,475 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.438528350959547, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,475 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,495 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.6493
 2023-07-02 10:35:01,495 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,495 [model] Posterior to be computed for parameters {'Omega_m': 0.3591332009334993, 'b1': 0.400810604097561}
 2023-07-02 10:35:01,495 [prior] Evaluating prior at array([0.3591332, 0.4008106])
 2023-07-02 10:35:01,495 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,496 [model] Got input parameters: {'Omega_m': 0.3591332009334993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.400810604097561, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,496 [classy] Got parameters {'Omega_m': 0.3591332009334993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,496 [classy] Computing new state
 2023-07-02 10:35:01,496 [classy] Setting parameters: {'Omega_m': 0.3591332009334993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99187113692795}
 2023-07-02 10:35:01,542 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,544 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119608
 2023-07-02 10:35:01,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.400810604097561, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,544 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,563 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.16797
 2023-07-02 10:35:01,563 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,564 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.4336426791470887}
 2023-07-02 10:35:01,564 [prior] Evaluating prior at array([0.32863693, 0.43364268])
 2023-07-02 10:35:01,564 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,564 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4336426791470887, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,564 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,564 [classy] Re-using computed results
 2023-07-02 10:35:01,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
 2023-07-02 10:35:01,564 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4336426791470887, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,564 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,583 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.64156
 2023-07-02 10:35:01,584 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,584 [model] Posterior to be computed for parameters {'Omega_m': 0.28338798370664986, 'b1': 0.5390212494354664}
 2023-07-02 10:35:01,584 [prior] Evaluating prior at array([0.28338798, 0.53902125])
 2023-07-02 10:35:01,584 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,584 [model] Got input parameters: {'Omega_m': 0.28338798370664986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5390212494354664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,584 [classy] Got parameters {'Omega_m': 0.28338798370664986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,584 [classy] Computing new state
 2023-07-02 10:35:01,584 [classy] Setting parameters: {'Omega_m': 0.28338798370664986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.9132783609878}
 2023-07-02 10:35:01,630 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,632 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0561301
 2023-07-02 10:35:01,632 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5390212494354664, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,632 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,652 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.46071
 2023-07-02 10:35:01,652 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,652 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.5927311807633766}
 2023-07-02 10:35:01,652 [prior] Evaluating prior at array([0.32863693, 0.59273118])
 2023-07-02 10:35:01,652 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,652 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5927311807633766, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,652 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,653 [classy] Re-using computed results
 2023-07-02 10:35:01,653 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
 2023-07-02 10:35:01,653 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5927311807633766, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,653 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,672 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.0882
 2023-07-02 10:35:01,672 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,672 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.5000074251423157}
 2023-07-02 10:35:01,672 [prior] Evaluating prior at array([0.30476919, 0.50000743])
 2023-07-02 10:35:01,672 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,672 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5000074251423157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,673 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,673 [classy] Computing new state
 2023-07-02 10:35:01,673 [classy] Setting parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,719 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
 2023-07-02 10:35:01,719 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,721 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00392345
 2023-07-02 10:35:01,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5000074251423157, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,721 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,740 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35121
 2023-07-02 10:35:01,741 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,741 [mcmc] New sample, #967:
   Omega_m:0.3286369, b1:0.4564565
 2023-07-02 10:35:01,741 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.5380503268177612}
 2023-07-02 10:35:01,741 [prior] Evaluating prior at array([0.30476919, 0.53805033])
 2023-07-02 10:35:01,741 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,741 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5380503268177612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,741 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,741 [classy] Re-using computed results
 2023-07-02 10:35:01,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
 2023-07-02 10:35:01,741 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5380503268177612, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,741 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,760 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29392
 2023-07-02 10:35:01,761 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,761 [mcmc] New sample, #968:
   Omega_m:0.3047692, b1:0.5000074
 2023-07-02 10:35:01,761 [model] Posterior to be computed for parameters {'Omega_m': 0.27107614815609765, 'b1': 0.5995292888322783}
 2023-07-02 10:35:01,761 [prior] Evaluating prior at array([0.27107615, 0.59952929])
 2023-07-02 10:35:01,761 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,761 [model] Got input parameters: {'Omega_m': 0.27107614815609765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5995292888322783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,761 [classy] Got parameters {'Omega_m': 0.27107614815609765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,761 [classy] Computing new state
 2023-07-02 10:35:01,761 [classy] Setting parameters: {'Omega_m': 0.27107614815609765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,808 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.55767162907225}
 2023-07-02 10:35:01,808 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,810 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.117261
 2023-07-02 10:35:01,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5995292888322783, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,810 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2484
 2023-07-02 10:35:01,829 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,829 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.4943399187940602}
 2023-07-02 10:35:01,829 [prior] Evaluating prior at array([0.30476919, 0.49433992])
 2023-07-02 10:35:01,829 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,829 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943399187940602, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,829 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,829 [classy] Re-using computed results
 2023-07-02 10:35:01,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
 2023-07-02 10:35:01,830 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,830 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943399187940602, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,830 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,850 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.7145
 2023-07-02 10:35:01,850 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,850 [mcmc] New sample, #969:
   Omega_m:0.3047692, b1:0.5380503
 2023-07-02 10:35:01,850 [model] Posterior to be computed for parameters {'Omega_m': 0.29491750115761656, 'b1': 0.5123160841342982}
 2023-07-02 10:35:01,850 [prior] Evaluating prior at array([0.2949175 , 0.51231608])
 2023-07-02 10:35:01,850 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,850 [model] Got input parameters: {'Omega_m': 0.29491750115761656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123160841342982, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,850 [classy] Got parameters {'Omega_m': 0.29491750115761656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,850 [classy] Computing new state
 2023-07-02 10:35:01,850 [classy] Setting parameters: {'Omega_m': 0.29491750115761656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,896 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.42818080980723}
 2023-07-02 10:35:01,896 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,898 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0199854
 2023-07-02 10:35:01,898 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123160841342982, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,898 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,917 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.13525
 2023-07-02 10:35:01,917 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,918 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.4904441388603413}
 2023-07-02 10:35:01,918 [prior] Evaluating prior at array([0.30476919, 0.49044414])
 2023-07-02 10:35:01,918 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,918 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904441388603413, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,918 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,918 [classy] Re-using computed results
 2023-07-02 10:35:01,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
 2023-07-02 10:35:01,918 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:01,918 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904441388603413, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,918 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:01,939 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.184428
 2023-07-02 10:35:01,939 [model] Computed derived parameters: {}
 2023-07-02 10:35:01,939 [mcmc] New sample, #970:
   Omega_m:0.3047692, b1:0.4943399
 2023-07-02 10:35:01,939 [model] Posterior to be computed for parameters {'Omega_m': 0.310503411314279, 'b1': 0.47998103397603825}
 2023-07-02 10:35:01,939 [prior] Evaluating prior at array([0.31050341, 0.47998103])
 2023-07-02 10:35:01,939 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:01,939 [model] Got input parameters: {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47998103397603825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,939 [classy] Got parameters {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:01,939 [classy] Computing new state
 2023-07-02 10:35:01,939 [classy] Setting parameters: {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:01,986 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.49912258242392}
 2023-07-02 10:35:01,986 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:01,988 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000444125
 2023-07-02 10:35:01,988 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47998103397603825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:01,988 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,008 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.677234
 2023-07-02 10:35:02,008 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,008 [mcmc] New sample, #971:
   Omega_m:0.3047692, b1:0.4904441
 2023-07-02 10:35:02,008 [model] Posterior to be computed for parameters {'Omega_m': 0.310503411314279, 'b1': 0.4771775577013586}
 2023-07-02 10:35:02,008 [prior] Evaluating prior at array([0.31050341, 0.47717756])
 2023-07-02 10:35:02,008 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,008 [model] Got input parameters: {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4771775577013586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,008 [classy] Got parameters {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,008 [classy] Re-using computed results
 2023-07-02 10:35:02,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.49912258242392}
 2023-07-02 10:35:02,008 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4771775577013586, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,008 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,029 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.246691
 2023-07-02 10:35:02,029 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,029 [mcmc] New sample, #972:
   Omega_m:0.3105034, b1:0.479981
 2023-07-02 10:35:02,029 [model] Posterior to be computed for parameters {'Omega_m': 0.31409531122027234, 'b1': 0.4706234963074924}
 2023-07-02 10:35:02,029 [prior] Evaluating prior at array([0.31409531, 0.4706235 ])
 2023-07-02 10:35:02,030 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,030 [model] Got input parameters: {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4706234963074924, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,030 [classy] Got parameters {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,030 [classy] Computing new state
 2023-07-02 10:35:02,030 [classy] Setting parameters: {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0666718619617}
 2023-07-02 10:35:02,076 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000361015
 2023-07-02 10:35:02,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4706234963074924, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,078 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,098 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.352086
 2023-07-02 10:35:02,098 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,098 [mcmc] New sample, #973:
   Omega_m:0.3105034, b1:0.4771776
 2023-07-02 10:35:02,098 [model] Posterior to be computed for parameters {'Omega_m': 0.31409531122027234, 'b1': 0.4604213161642931}
 2023-07-02 10:35:02,098 [prior] Evaluating prior at array([0.31409531, 0.46042132])
 2023-07-02 10:35:02,098 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,098 [model] Got input parameters: {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4604213161642931, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,098 [classy] Got parameters {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,098 [classy] Re-using computed results
 2023-07-02 10:35:02,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0666718619617}
 2023-07-02 10:35:02,098 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4604213161642931, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,098 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,118 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.54354
 2023-07-02 10:35:02,118 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,118 [model] Posterior to be computed for parameters {'Omega_m': 0.32189574023786205, 'b1': 0.4563902236613161}
 2023-07-02 10:35:02,118 [prior] Evaluating prior at array([0.32189574, 0.45639022])
 2023-07-02 10:35:02,118 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,118 [model] Got input parameters: {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4563902236613161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,118 [classy] Got parameters {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,118 [classy] Computing new state
 2023-07-02 10:35:02,118 [classy] Setting parameters: {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.142562631618}
 2023-07-02 10:35:02,167 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,169 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00550918
 2023-07-02 10:35:02,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4563902236613161, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,169 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,188 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0823556
 2023-07-02 10:35:02,188 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,188 [mcmc] New sample, #974:
   Omega_m:0.3140953, b1:0.4706235
 2023-07-02 10:35:02,188 [model] Posterior to be computed for parameters {'Omega_m': 0.32189574023786205, 'b1': 0.4776534157242988}
 2023-07-02 10:35:02,188 [prior] Evaluating prior at array([0.32189574, 0.47765342])
 2023-07-02 10:35:02,188 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,188 [model] Got input parameters: {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4776534157242988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,188 [classy] Got parameters {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,188 [classy] Re-using computed results
 2023-07-02 10:35:02,189 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.142562631618}
 2023-07-02 10:35:02,189 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,189 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4776534157242988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,189 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,208 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40273
 2023-07-02 10:35:02,208 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,208 [mcmc] New sample, #975:
   Omega_m:0.3218957, b1:0.4563902
 2023-07-02 10:35:02,209 [model] Posterior to be computed for parameters {'Omega_m': 0.31716025012163707, 'b1': 0.486294161225029}
 2023-07-02 10:35:02,209 [prior] Evaluating prior at array([0.31716025, 0.48629416])
 2023-07-02 10:35:02,209 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,209 [model] Got input parameters: {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.486294161225029, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,209 [classy] Got parameters {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,209 [classy] Computing new state
 2023-07-02 10:35:02,209 [classy] Setting parameters: {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.70115488036203}
 2023-07-02 10:35:02,256 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,258 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00152786
 2023-07-02 10:35:02,258 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.486294161225029, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,258 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,277 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63059
 2023-07-02 10:35:02,277 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,277 [mcmc] New sample, #976:
   Omega_m:0.3218957, b1:0.4776534
 2023-07-02 10:35:02,278 [model] Posterior to be computed for parameters {'Omega_m': 0.31716025012163707, 'b1': 0.4534801701469038}
 2023-07-02 10:35:02,278 [prior] Evaluating prior at array([0.31716025, 0.45348017])
 2023-07-02 10:35:02,278 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,278 [model] Got input parameters: {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4534801701469038, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,278 [classy] Got parameters {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,278 [classy] Re-using computed results
 2023-07-02 10:35:02,278 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.70115488036203}
 2023-07-02 10:35:02,278 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,278 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4534801701469038, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,278 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,298 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86582
 2023-07-02 10:35:02,298 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,298 [model] Posterior to be computed for parameters {'Omega_m': 0.3185608664488573, 'b1': 0.4837384871700433}
 2023-07-02 10:35:02,298 [prior] Evaluating prior at array([0.31856087, 0.48373849])
 2023-07-02 10:35:02,298 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,298 [model] Got input parameters: {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4837384871700433, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,298 [classy] Got parameters {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,298 [classy] Computing new state
 2023-07-02 10:35:02,298 [classy] Setting parameters: {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53517351555683}
 2023-07-02 10:35:02,345 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0024329
 2023-07-02 10:35:02,347 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4837384871700433, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,347 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58818
 2023-07-02 10:35:02,366 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,366 [mcmc] New sample, #977:
   Omega_m:0.3171603, b1:0.4862942
 2023-07-02 10:35:02,367 [model] Posterior to be computed for parameters {'Omega_m': 0.3185608664488573, 'b1': 0.4934481613740825}
 2023-07-02 10:35:02,367 [prior] Evaluating prior at array([0.31856087, 0.49344816])
 2023-07-02 10:35:02,367 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,367 [model] Got input parameters: {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4934481613740825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,367 [classy] Got parameters {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,367 [classy] Re-using computed results
 2023-07-02 10:35:02,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53517351555683}
 2023-07-02 10:35:02,367 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4934481613740825, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,367 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,386 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8633
 2023-07-02 10:35:02,386 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,386 [mcmc] New sample, #978:
   Omega_m:0.3185609, b1:0.4837385
 2023-07-02 10:35:02,386 [model] Posterior to be computed for parameters {'Omega_m': 0.31346895603323616, 'b1': 0.5027392592190872}
 2023-07-02 10:35:02,386 [prior] Evaluating prior at array([0.31346896, 0.50273926])
 2023-07-02 10:35:02,386 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,386 [model] Got input parameters: {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5027392592190872, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,386 [classy] Got parameters {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,386 [classy] Computing new state
 2023-07-02 10:35:02,386 [classy] Setting parameters: {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14176664238337}
 2023-07-02 10:35:02,432 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000261749
 2023-07-02 10:35:02,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5027392592190872, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,434 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,455 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90952
 2023-07-02 10:35:02,455 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,455 [mcmc] New sample, #979:
   Omega_m:0.3185609, b1:0.4934482
 2023-07-02 10:35:02,455 [model] Posterior to be computed for parameters {'Omega_m': 0.31346895603323616, 'b1': 0.502907825432902}
 2023-07-02 10:35:02,455 [prior] Evaluating prior at array([0.31346896, 0.50290783])
 2023-07-02 10:35:02,455 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,455 [model] Got input parameters: {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.502907825432902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,455 [classy] Got parameters {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,455 [classy] Re-using computed results
 2023-07-02 10:35:02,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14176664238337}
 2023-07-02 10:35:02,456 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,456 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.502907825432902, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,456 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,475 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.9098
 2023-07-02 10:35:02,475 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,475 [mcmc] New sample, #980:
   Omega_m:0.313469, b1:0.5027393
 2023-07-02 10:35:02,475 [model] Posterior to be computed for parameters {'Omega_m': 0.3227621946066772, 'b1': 0.48595065575883956}
 2023-07-02 10:35:02,475 [prior] Evaluating prior at array([0.32276219, 0.48595066])
 2023-07-02 10:35:02,475 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,475 [model] Got input parameters: {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48595065575883956, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,476 [classy] Got parameters {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,476 [classy] Computing new state
 2023-07-02 10:35:02,476 [classy] Setting parameters: {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,522 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.0411500758586}
 2023-07-02 10:35:02,522 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,524 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00651792
 2023-07-02 10:35:02,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48595065575883956, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,524 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,543 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61438
 2023-07-02 10:35:02,543 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,543 [mcmc] New sample, #981:
   Omega_m:0.313469, b1:0.5029078
 2023-07-02 10:35:02,543 [model] Posterior to be computed for parameters {'Omega_m': 0.3227621946066772, 'b1': 0.4175192027778834}
 2023-07-02 10:35:02,543 [prior] Evaluating prior at array([0.32276219, 0.4175192 ])
 2023-07-02 10:35:02,544 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,544 [model] Got input parameters: {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4175192027778834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,544 [classy] Got parameters {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,544 [classy] Re-using computed results
 2023-07-02 10:35:02,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.0411500758586}
 2023-07-02 10:35:02,544 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4175192027778834, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,544 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,563 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.35049
 2023-07-02 10:35:02,564 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,564 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.4529393803407596}
 2023-07-02 10:35:02,564 [prior] Evaluating prior at array([0.34085375, 0.45293938])
 2023-07-02 10:35:02,564 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,564 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4529393803407596, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,564 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,564 [classy] Computing new state
 2023-07-02 10:35:02,564 [classy] Setting parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
 2023-07-02 10:35:02,611 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0462772
 2023-07-02 10:35:02,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4529393803407596, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,613 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.395324
 2023-07-02 10:35:02,632 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,632 [mcmc] New sample, #982:
   Omega_m:0.3227622, b1:0.4859507
 2023-07-02 10:35:02,632 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.46187149143738443}
 2023-07-02 10:35:02,632 [prior] Evaluating prior at array([0.34085375, 0.46187149])
 2023-07-02 10:35:02,632 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,632 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46187149143738443, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,632 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,632 [classy] Re-using computed results
 2023-07-02 10:35:02,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
 2023-07-02 10:35:02,632 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46187149143738443, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,633 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,652 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.586998
 2023-07-02 10:35:02,652 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,653 [mcmc] New sample, #983:
   Omega_m:0.3408538, b1:0.4529394
 2023-07-02 10:35:02,653 [model] Posterior to be computed for parameters {'Omega_m': 0.367095807045219, 'b1': 0.4139881914667562}
 2023-07-02 10:35:02,653 [prior] Evaluating prior at array([0.36709581, 0.41398819])
 2023-07-02 10:35:02,653 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,653 [model] Got input parameters: {'Omega_m': 0.367095807045219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4139881914667562, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,653 [classy] Got parameters {'Omega_m': 0.367095807045219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,653 [classy] Computing new state
 2023-07-02 10:35:02,653 [classy] Setting parameters: {'Omega_m': 0.367095807045219, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,699 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.1558293143217}
 2023-07-02 10:35:02,699 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,701 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.160918
 2023-07-02 10:35:02,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4139881914667562, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,721 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.37164
 2023-07-02 10:35:02,721 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,721 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.4385645891204837}
 2023-07-02 10:35:02,721 [prior] Evaluating prior at array([0.34085375, 0.43856459])
 2023-07-02 10:35:02,721 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,721 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4385645891204837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,721 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,721 [classy] Re-using computed results
 2023-07-02 10:35:02,721 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
 2023-07-02 10:35:02,721 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4385645891204837, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,721 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,741 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.00366
 2023-07-02 10:35:02,741 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,741 [mcmc] New sample, #984:
   Omega_m:0.3408538, b1:0.4618715
 2023-07-02 10:35:02,741 [model] Posterior to be computed for parameters {'Omega_m': 0.2846843302929721, 'b1': 0.5410557128057475}
 2023-07-02 10:35:02,741 [prior] Evaluating prior at array([0.28468433, 0.54105571])
 2023-07-02 10:35:02,742 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,742 [model] Got input parameters: {'Omega_m': 0.2846843302929721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5410557128057475, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,742 [classy] Got parameters {'Omega_m': 0.2846843302929721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,742 [classy] Computing new state
 2023-07-02 10:35:02,742 [classy] Setting parameters: {'Omega_m': 0.2846843302929721, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,788 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.74371084777152}
 2023-07-02 10:35:02,788 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,790 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0510832
 2023-07-02 10:35:02,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5410557128057475, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,790 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,810 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.54432
 2023-07-02 10:35:02,810 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,810 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.45410750670821226}
 2023-07-02 10:35:02,810 [prior] Evaluating prior at array([0.34085375, 0.45410751])
 2023-07-02 10:35:02,810 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,810 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45410750670821226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,810 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,810 [classy] Re-using computed results
 2023-07-02 10:35:02,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
 2023-07-02 10:35:02,810 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45410750670821226, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,810 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.395178
 2023-07-02 10:35:02,830 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,830 [mcmc] New sample, #985:
   Omega_m:0.3408538, b1:0.4385646
 2023-07-02 10:35:02,830 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.47810507449125156}
 2023-07-02 10:35:02,830 [prior] Evaluating prior at array([0.32770208, 0.47810507])
 2023-07-02 10:35:02,830 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,830 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47810507449125156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,830 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,830 [classy] Computing new state
 2023-07-02 10:35:02,830 [classy] Setting parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,876 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
 2023-07-02 10:35:02,877 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,878 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0138833
 2023-07-02 10:35:02,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47810507449125156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,878 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,898 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09039
 2023-07-02 10:35:02,898 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,898 [mcmc] New sample, #986:
   Omega_m:0.3408538, b1:0.4541075
 2023-07-02 10:35:02,898 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.4667542630605031}
 2023-07-02 10:35:02,898 [prior] Evaluating prior at array([0.32770208, 0.46675426])
 2023-07-02 10:35:02,898 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,898 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4667542630605031, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,898 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,898 [classy] Re-using computed results
 2023-07-02 10:35:02,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
 2023-07-02 10:35:02,898 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,898 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4667542630605031, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,898 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,918 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7914
 2023-07-02 10:35:02,918 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,919 [mcmc] New sample, #987:
   Omega_m:0.3277021, b1:0.4781051
 2023-07-02 10:35:02,919 [model] Posterior to be computed for parameters {'Omega_m': 0.35112491290267633, 'b1': 0.42401513741120384}
 2023-07-02 10:35:02,919 [prior] Evaluating prior at array([0.35112491, 0.42401514])
 2023-07-02 10:35:02,919 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,919 [model] Got input parameters: {'Omega_m': 0.35112491290267633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42401513741120384, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,919 [classy] Got parameters {'Omega_m': 0.35112491290267633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,919 [classy] Computing new state
 2023-07-02 10:35:02,919 [classy] Setting parameters: {'Omega_m': 0.35112491290267633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:02,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.85022522430765}
 2023-07-02 10:35:02,966 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:02,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0836507
 2023-07-02 10:35:02,968 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42401513741120384, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,968 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:02,987 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.64199
 2023-07-02 10:35:02,987 [model] Computed derived parameters: {}
 2023-07-02 10:35:02,987 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.47743843239691075}
 2023-07-02 10:35:02,987 [prior] Evaluating prior at array([0.32770208, 0.47743843])
 2023-07-02 10:35:02,987 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:02,987 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47743843239691075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,987 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:02,987 [classy] Re-using computed results
 2023-07-02 10:35:02,987 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
 2023-07-02 10:35:02,987 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:02,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47743843239691075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:02,987 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09207
 2023-07-02 10:35:03,007 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,007 [mcmc] New sample, #988:
   Omega_m:0.3277021, b1:0.4667543
 2023-07-02 10:35:03,007 [model] Posterior to be computed for parameters {'Omega_m': 0.33670705802433165, 'b1': 0.4610072519893069}
 2023-07-02 10:35:03,007 [prior] Evaluating prior at array([0.33670706, 0.46100725])
 2023-07-02 10:35:03,008 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,008 [model] Got input parameters: {'Omega_m': 0.33670705802433165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4610072519893069, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,008 [classy] Got parameters {'Omega_m': 0.33670705802433165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,008 [classy] Computing new state
 2023-07-02 10:35:03,008 [classy] Setting parameters: {'Omega_m': 0.33670705802433165, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.44181171040762}
 2023-07-02 10:35:03,055 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0341233
 2023-07-02 10:35:03,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4610072519893069, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,057 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,076 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.550712
 2023-07-02 10:35:03,076 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,076 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.48775256192960637}
 2023-07-02 10:35:03,076 [prior] Evaluating prior at array([0.32770208, 0.48775256])
 2023-07-02 10:35:03,076 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,077 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48775256192960637, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,077 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,077 [classy] Re-using computed results
 2023-07-02 10:35:03,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
 2023-07-02 10:35:03,077 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,077 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48775256192960637, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,077 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,096 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79163
 2023-07-02 10:35:03,096 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,096 [mcmc] New sample, #989:
   Omega_m:0.3277021, b1:0.4774384
 2023-07-02 10:35:03,096 [model] Posterior to be computed for parameters {'Omega_m': 0.31456368313019656, 'b1': 0.5117259145885833}
 2023-07-02 10:35:03,096 [prior] Evaluating prior at array([0.31456368, 0.51172591])
 2023-07-02 10:35:03,097 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,097 [model] Got input parameters: {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117259145885833, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,097 [classy] Got parameters {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,097 [classy] Computing new state
 2023-07-02 10:35:03,097 [classy] Setting parameters: {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.01060811295588}
 2023-07-02 10:35:03,146 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000466308
 2023-07-02 10:35:03,148 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117259145885833, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,148 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,168 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61931
 2023-07-02 10:35:03,168 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,168 [mcmc] New sample, #990:
   Omega_m:0.3277021, b1:0.4877526
 2023-07-02 10:35:03,168 [model] Posterior to be computed for parameters {'Omega_m': 0.31456368313019656, 'b1': 0.5281136515955757}
 2023-07-02 10:35:03,168 [prior] Evaluating prior at array([0.31456368, 0.52811365])
 2023-07-02 10:35:03,168 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,168 [model] Got input parameters: {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5281136515955757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,168 [classy] Got parameters {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,168 [classy] Re-using computed results
 2023-07-02 10:35:03,168 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.01060811295588}
 2023-07-02 10:35:03,168 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5281136515955757, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,169 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,188 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.910226
 2023-07-02 10:35:03,188 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,188 [mcmc] New sample, #991:
   Omega_m:0.3145637, b1:0.5117259
 2023-07-02 10:35:03,188 [model] Posterior to be computed for parameters {'Omega_m': 0.3101625911788141, 'b1': 0.5361442280604936}
 2023-07-02 10:35:03,188 [prior] Evaluating prior at array([0.31016259, 0.53614423])
 2023-07-02 10:35:03,188 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,188 [model] Got input parameters: {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5361442280604936, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,188 [classy] Got parameters {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,188 [classy] Computing new state
 2023-07-02 10:35:03,188 [classy] Setting parameters: {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5403840185025}
 2023-07-02 10:35:03,235 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000534768
 2023-07-02 10:35:03,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5361442280604936, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,237 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,257 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.770154
 2023-07-02 10:35:03,257 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,257 [mcmc] New sample, #992:
   Omega_m:0.3145637, b1:0.5281137
 2023-07-02 10:35:03,257 [model] Posterior to be computed for parameters {'Omega_m': 0.3101625911788141, 'b1': 0.5365392479393729}
 2023-07-02 10:35:03,257 [prior] Evaluating prior at array([0.31016259, 0.53653925])
 2023-07-02 10:35:03,257 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,257 [model] Got input parameters: {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5365392479393729, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,257 [classy] Got parameters {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,257 [classy] Re-using computed results
 2023-07-02 10:35:03,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5403840185025}
 2023-07-02 10:35:03,257 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5365392479393729, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,257 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,278 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.710084
 2023-07-02 10:35:03,278 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,278 [model] Posterior to be computed for parameters {'Omega_m': 0.3076013212864909, 'b1': 0.5408177213537051}
 2023-07-02 10:35:03,278 [prior] Evaluating prior at array([0.30760132, 0.54081772])
 2023-07-02 10:35:03,278 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,278 [model] Got input parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5408177213537051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,278 [classy] Got parameters {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,278 [classy] Computing new state
 2023-07-02 10:35:03,278 [classy] Setting parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85175933230164}
 2023-07-02 10:35:03,324 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00168236
 2023-07-02 10:35:03,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5408177213537051, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,326 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,345 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.582909
 2023-07-02 10:35:03,345 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,346 [mcmc] New sample, #993:
   Omega_m:0.3101626, b1:0.5361442
 2023-07-02 10:35:03,346 [model] Posterior to be computed for parameters {'Omega_m': 0.3076013212864909, 'b1': 0.5497473454981044}
 2023-07-02 10:35:03,346 [prior] Evaluating prior at array([0.30760132, 0.54974735])
 2023-07-02 10:35:03,346 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,346 [model] Got input parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5497473454981044, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,346 [classy] Got parameters {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,346 [classy] Re-using computed results
 2023-07-02 10:35:03,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85175933230164}
 2023-07-02 10:35:03,346 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,346 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5497473454981044, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,346 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,366 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.995334
 2023-07-02 10:35:03,366 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,366 [model] Posterior to be computed for parameters {'Omega_m': 0.24893763972576813, 'b1': 0.6478600612300617}
 2023-07-02 10:35:03,366 [prior] Evaluating prior at array([0.24893764, 0.64786006])
 2023-07-02 10:35:03,366 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,366 [model] Got input parameters: {'Omega_m': 0.24893763972576813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6478600612300617, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,366 [classy] Got parameters {'Omega_m': 0.24893763972576813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,366 [classy] Computing new state
 2023-07-02 10:35:03,366 [classy] Setting parameters: {'Omega_m': 0.24893763972576813, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.6801957274664}
 2023-07-02 10:35:03,413 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,415 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.293336
 2023-07-02 10:35:03,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6478600612300617, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,415 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,434 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.7179
 2023-07-02 10:35:03,434 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,434 [model] Posterior to be computed for parameters {'Omega_m': 0.3076013212864909, 'b1': 0.5780279312929958}
 2023-07-02 10:35:03,435 [prior] Evaluating prior at array([0.30760132, 0.57802793])
 2023-07-02 10:35:03,435 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,435 [model] Got input parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5780279312929958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,435 [classy] Got parameters {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,435 [classy] Re-using computed results
 2023-07-02 10:35:03,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85175933230164}
 2023-07-02 10:35:03,435 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,435 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5780279312929958, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,435 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,455 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.17917
 2023-07-02 10:35:03,455 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,455 [model] Posterior to be computed for parameters {'Omega_m': 0.3077178453565464, 'b1': 0.5406051024252845}
 2023-07-02 10:35:03,455 [prior] Evaluating prior at array([0.30771785, 0.5406051 ])
 2023-07-02 10:35:03,455 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,455 [model] Got input parameters: {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5406051024252845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,455 [classy] Got parameters {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,455 [classy] Computing new state
 2023-07-02 10:35:03,455 [classy] Setting parameters: {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,501 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.83754230007477}
 2023-07-02 10:35:03,501 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,503 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00161214
 2023-07-02 10:35:03,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5406051024252845, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,503 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,523 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.593166
 2023-07-02 10:35:03,523 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,523 [mcmc] New sample, #994:
   Omega_m:0.3076013, b1:0.5408177
 2023-07-02 10:35:03,523 [model] Posterior to be computed for parameters {'Omega_m': 0.3077178453565464, 'b1': 0.5239924924041647}
 2023-07-02 10:35:03,523 [prior] Evaluating prior at array([0.30771785, 0.52399249])
 2023-07-02 10:35:03,524 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,524 [model] Got input parameters: {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239924924041647, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,524 [classy] Got parameters {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,524 [classy] Re-using computed results
 2023-07-02 10:35:03,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.83754230007477}
 2023-07-02 10:35:03,524 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239924924041647, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,524 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,543 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30895
 2023-07-02 10:35:03,543 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,543 [mcmc] New sample, #995:
   Omega_m:0.3077178, b1:0.5406051
 2023-07-02 10:35:03,543 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.518316967695296}
 2023-07-02 10:35:03,543 [prior] Evaluating prior at array([0.31082827, 0.51831697])
 2023-07-02 10:35:03,544 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,544 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.518316967695296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,544 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,544 [classy] Computing new state
 2023-07-02 10:35:03,544 [classy] Setting parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:03,590 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,592 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000371185
 2023-07-02 10:35:03,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.518316967695296, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,592 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,611 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5246
 2023-07-02 10:35:03,611 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,611 [mcmc] New sample, #996:
   Omega_m:0.3077178, b1:0.5239925
 2023-07-02 10:35:03,612 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.5119271911587223}
 2023-07-02 10:35:03,612 [prior] Evaluating prior at array([0.31082827, 0.51192719])
 2023-07-02 10:35:03,612 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,612 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119271911587223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,612 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,612 [classy] Re-using computed results
 2023-07-02 10:35:03,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:03,612 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119271911587223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,612 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,632 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77448
 2023-07-02 10:35:03,632 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,632 [mcmc] New sample, #997:
   Omega_m:0.3108283, b1:0.518317
 2023-07-02 10:35:03,632 [model] Posterior to be computed for parameters {'Omega_m': 0.28588954734311267, 'b1': 0.5574323350239988}
 2023-07-02 10:35:03,632 [prior] Evaluating prior at array([0.28588955, 0.55743234])
 2023-07-02 10:35:03,632 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,632 [model] Got input parameters: {'Omega_m': 0.28588954734311267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5574323350239988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,632 [classy] Got parameters {'Omega_m': 0.28588954734311267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,632 [classy] Computing new state
 2023-07-02 10:35:03,632 [classy] Setting parameters: {'Omega_m': 0.28588954734311267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.58665502891463}
 2023-07-02 10:35:03,679 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0466194
 2023-07-02 10:35:03,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5574323350239988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,681 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.58025
 2023-07-02 10:35:03,701 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,701 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.4796578899091886}
 2023-07-02 10:35:03,701 [prior] Evaluating prior at array([0.31082827, 0.47965789])
 2023-07-02 10:35:03,701 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,701 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4796578899091886, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,701 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,701 [classy] Re-using computed results
 2023-07-02 10:35:03,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:03,701 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4796578899091886, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,701 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,721 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.732556
 2023-07-02 10:35:03,721 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,721 [model] Posterior to be computed for parameters {'Omega_m': 0.3413536603187373, 'b1': 0.4562281781397764}
 2023-07-02 10:35:03,722 [prior] Evaluating prior at array([0.34135366, 0.45622818])
 2023-07-02 10:35:03,722 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,722 [model] Got input parameters: {'Omega_m': 0.3413536603187373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4562281781397764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,722 [classy] Got parameters {'Omega_m': 0.3413536603187373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,722 [classy] Computing new state
 2023-07-02 10:35:03,722 [classy] Setting parameters: {'Omega_m': 0.3413536603187373, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,768 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9221811814771}
 2023-07-02 10:35:03,769 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,770 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0478592
 2023-07-02 10:35:03,770 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4562281781397764, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,770 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,790 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.553151
 2023-07-02 10:35:03,790 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,790 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.5147991718995647}
 2023-07-02 10:35:03,790 [prior] Evaluating prior at array([0.31082827, 0.51479917])
 2023-07-02 10:35:03,790 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,790 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5147991718995647, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,790 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,790 [classy] Re-using computed results
 2023-07-02 10:35:03,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:03,790 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5147991718995647, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,790 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,810 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68988
 2023-07-02 10:35:03,810 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,810 [model] Posterior to be computed for parameters {'Omega_m': 0.29489076528820196, 'b1': 0.541008009019466}
 2023-07-02 10:35:03,810 [prior] Evaluating prior at array([0.29489077, 0.54100801])
 2023-07-02 10:35:03,810 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,810 [model] Got input parameters: {'Omega_m': 0.29489076528820196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.541008009019466, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,810 [classy] Got parameters {'Omega_m': 0.29489076528820196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,810 [classy] Computing new state
 2023-07-02 10:35:03,810 [classy] Setting parameters: {'Omega_m': 0.29489076528820196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,857 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43156561611605}
 2023-07-02 10:35:03,857 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,859 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.020047
 2023-07-02 10:35:03,859 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.541008009019466, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,859 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,879 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.357507
 2023-07-02 10:35:03,879 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,880 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.4368721328544044}
 2023-07-02 10:35:03,880 [prior] Evaluating prior at array([0.31082827, 0.43687213])
 2023-07-02 10:35:03,880 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,880 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4368721328544044, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,880 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,880 [classy] Re-using computed results
 2023-07-02 10:35:03,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:03,880 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4368721328544044, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,880 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.7971
 2023-07-02 10:35:03,899 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,899 [model] Posterior to be computed for parameters {'Omega_m': 0.3440624305046478, 'b1': 0.4512855442788749}
 2023-07-02 10:35:03,899 [prior] Evaluating prior at array([0.34406243, 0.45128554])
 2023-07-02 10:35:03,899 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,899 [model] Got input parameters: {'Omega_m': 0.3440624305046478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4512855442788749, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,900 [classy] Got parameters {'Omega_m': 0.3440624305046478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,900 [classy] Computing new state
 2023-07-02 10:35:03,900 [classy] Setting parameters: {'Omega_m': 0.3440624305046478, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:03,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6222139155358}
 2023-07-02 10:35:03,946 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:03,948 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.056861
 2023-07-02 10:35:03,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4512855442788749, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,948 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,967 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25399
 2023-07-02 10:35:03,967 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,967 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.4853467433505858}
 2023-07-02 10:35:03,967 [prior] Evaluating prior at array([0.31082827, 0.48534674])
 2023-07-02 10:35:03,968 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,968 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853467433505858, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,968 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,968 [classy] Re-using computed results
 2023-07-02 10:35:03,968 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:03,968 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:03,968 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853467433505858, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,968 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:03,987 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.47977
 2023-07-02 10:35:03,988 [model] Computed derived parameters: {}
 2023-07-02 10:35:03,988 [model] Posterior to be computed for parameters {'Omega_m': 0.3022977632282667, 'b1': 0.5274926214769506}
 2023-07-02 10:35:03,988 [prior] Evaluating prior at array([0.30229776, 0.52749262])
 2023-07-02 10:35:03,988 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:03,988 [model] Got input parameters: {'Omega_m': 0.3022977632282667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5274926214769506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:03,988 [classy] Got parameters {'Omega_m': 0.3022977632282667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:03,988 [classy] Computing new state
 2023-07-02 10:35:03,988 [classy] Setting parameters: {'Omega_m': 0.3022977632282667, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.50382617666912}
 2023-07-02 10:35:04,034 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,036 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00672978
 2023-07-02 10:35:04,036 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5274926214769506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,036 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,056 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.89543
 2023-07-02 10:35:04,056 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,056 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.523169870564672}
 2023-07-02 10:35:04,056 [prior] Evaluating prior at array([0.31082827, 0.52316987])
 2023-07-02 10:35:04,056 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,056 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523169870564672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,056 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,056 [classy] Re-using computed results
 2023-07-02 10:35:04,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:04,056 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,056 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523169870564672, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,056 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,076 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18394
 2023-07-02 10:35:04,076 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,076 [mcmc] New sample, #998:
   Omega_m:0.3108283, b1:0.5119272
 2023-07-02 10:35:04,076 [model] Posterior to be computed for parameters {'Omega_m': 0.2773582852648978, 'b1': 0.5842418222172383}
 2023-07-02 10:35:04,076 [prior] Evaluating prior at array([0.27735829, 0.58424182])
 2023-07-02 10:35:04,076 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,076 [model] Got input parameters: {'Omega_m': 0.2773582852648978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5842418222172383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,077 [classy] Got parameters {'Omega_m': 0.2773582852648978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,077 [classy] Computing new state
 2023-07-02 10:35:04,077 [classy] Setting parameters: {'Omega_m': 0.2773582852648978, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.71083648073787}
 2023-07-02 10:35:04,125 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0830274
 2023-07-02 10:35:04,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5842418222172383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,128 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,155 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.14995
 2023-07-02 10:35:04,155 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,155 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.5571576484082378}
 2023-07-02 10:35:04,155 [prior] Evaluating prior at array([0.31082827, 0.55715765])
 2023-07-02 10:35:04,155 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,155 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5571576484082378, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,155 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,155 [classy] Re-using computed results
 2023-07-02 10:35:04,155 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
 2023-07-02 10:35:04,156 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5571576484082378, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,156 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,176 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.01744
 2023-07-02 10:35:04,176 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3215494132819417, 'b1': 0.5036072350438499}
 2023-07-02 10:35:04,176 [prior] Evaluating prior at array([0.32154941, 0.50360724])
 2023-07-02 10:35:04,176 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,176 [model] Got input parameters: {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5036072350438499, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,176 [classy] Got parameters {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,176 [classy] Computing new state
 2023-07-02 10:35:04,176 [classy] Setting parameters: {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.18316640592158}
 2023-07-02 10:35:04,223 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,225 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00512997
 2023-07-02 10:35:04,225 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5036072350438499, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,225 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,244 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07382
 2023-07-02 10:35:04,244 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,245 [mcmc] New sample, #999:
   Omega_m:0.3108283, b1:0.5231699
 2023-07-02 10:35:04,245 [model] Posterior to be computed for parameters {'Omega_m': 0.3215494132819417, 'b1': 0.47818708822531564}
 2023-07-02 10:35:04,245 [prior] Evaluating prior at array([0.32154941, 0.47818709])
 2023-07-02 10:35:04,245 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,245 [model] Got input parameters: {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47818708822531564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,245 [classy] Got parameters {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,245 [classy] Re-using computed results
 2023-07-02 10:35:04,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.18316640592158}
 2023-07-02 10:35:04,245 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47818708822531564, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,245 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,264 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42205
 2023-07-02 10:35:04,265 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,265 [mcmc] New sample, #1000:
   Omega_m:0.3215494, b1:0.5036072
 2023-07-02 10:35:04,265 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.49173933312049223}
 2023-07-02 10:35:04,265 [prior] Evaluating prior at array([0.31412222, 0.49173933])
 2023-07-02 10:35:04,265 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,265 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49173933312049223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,265 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,265 [classy] Computing new state
 2023-07-02 10:35:04,265 [classy] Setting parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,311 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
 2023-07-02 10:35:04,312 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,313 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00036635
 2023-07-02 10:35:04,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49173933312049223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,314 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,334 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64274
 2023-07-02 10:35:04,334 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,334 [mcmc] New sample, #1001:
   Omega_m:0.3215494, b1:0.4781871
 2023-07-02 10:35:04,334 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.49338388832287833}
 2023-07-02 10:35:04,334 [prior] Evaluating prior at array([0.31412222, 0.49338389])
 2023-07-02 10:35:04,334 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,334 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49338388832287833, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,334 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,335 [classy] Re-using computed results
 2023-07-02 10:35:04,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
 2023-07-02 10:35:04,335 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49338388832287833, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,335 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,354 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72468
 2023-07-02 10:35:04,354 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,354 [mcmc] New sample, #1002:
   Omega_m:0.3141222, b1:0.4917393
 2023-07-02 10:35:04,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3010405833900486, 'b1': 0.5172536578896144}
 2023-07-02 10:35:04,354 [prior] Evaluating prior at array([0.30104058, 0.51725366])
 2023-07-02 10:35:04,354 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,355 [model] Got input parameters: {'Omega_m': 0.3010405833900486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5172536578896144, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,355 [classy] Got parameters {'Omega_m': 0.3010405833900486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,355 [classy] Computing new state
 2023-07-02 10:35:04,355 [classy] Setting parameters: {'Omega_m': 0.3010405833900486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,401 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.65986318959216}
 2023-07-02 10:35:04,401 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,403 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00846654
 2023-07-02 10:35:04,403 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5172536578896144, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,403 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,422 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54384
 2023-07-02 10:35:04,422 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,423 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.5694340122727565}
 2023-07-02 10:35:04,423 [prior] Evaluating prior at array([0.31412222, 0.56943401])
 2023-07-02 10:35:04,423 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,423 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5694340122727565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,423 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,423 [classy] Re-using computed results
 2023-07-02 10:35:04,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
 2023-07-02 10:35:04,423 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5694340122727565, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,423 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,443 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2007
 2023-07-02 10:35:04,443 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,443 [model] Posterior to be computed for parameters {'Omega_m': 0.25930471155066126, 'b1': 0.5934081926820386}
 2023-07-02 10:35:04,443 [prior] Evaluating prior at array([0.25930471, 0.59340819])
 2023-07-02 10:35:04,444 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,444 [model] Got input parameters: {'Omega_m': 0.25930471155066126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5934081926820386, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,444 [classy] Got parameters {'Omega_m': 0.25930471155066126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,444 [classy] Computing new state
 2023-07-02 10:35:04,444 [classy] Setting parameters: {'Omega_m': 0.25930471155066126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.19022817291906}
 2023-07-02 10:35:04,491 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.199603
 2023-07-02 10:35:04,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5934081926820386, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,492 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,512 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.3826
 2023-07-02 10:35:04,512 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.5547022422761454}
 2023-07-02 10:35:04,512 [prior] Evaluating prior at array([0.31412222, 0.55470224])
 2023-07-02 10:35:04,512 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,512 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5547022422761454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,512 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,512 [classy] Re-using computed results
 2023-07-02 10:35:04,512 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
 2023-07-02 10:35:04,512 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5547022422761454, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,513 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,533 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.98243
 2023-07-02 10:35:04,533 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,533 [model] Posterior to be computed for parameters {'Omega_m': 0.2658269187344302, 'b1': 0.5815072635290267}
 2023-07-02 10:35:04,533 [prior] Evaluating prior at array([0.26582692, 0.58150726])
 2023-07-02 10:35:04,533 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,533 [model] Got input parameters: {'Omega_m': 0.2658269187344302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5815072635290267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,533 [classy] Got parameters {'Omega_m': 0.2658269187344302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,533 [classy] Computing new state
 2023-07-02 10:35:04,533 [classy] Setting parameters: {'Omega_m': 0.2658269187344302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.27817366360225}
 2023-07-02 10:35:04,580 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.15096
 2023-07-02 10:35:04,582 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5815072635290267, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,582 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,602 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.0625
 2023-07-02 10:35:04,602 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,602 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.4904875004253085}
 2023-07-02 10:35:04,602 [prior] Evaluating prior at array([0.31412222, 0.4904875 ])
 2023-07-02 10:35:04,603 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,603 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904875004253085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,603 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,603 [classy] Re-using computed results
 2023-07-02 10:35:04,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
 2023-07-02 10:35:04,603 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904875004253085, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,603 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57089
 2023-07-02 10:35:04,622 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,622 [mcmc] New sample, #1003:
   Omega_m:0.3141222, b1:0.4933839
 2023-07-02 10:35:04,623 [model] Posterior to be computed for parameters {'Omega_m': 0.3186001496824632, 'b1': 0.48231671247591823}
 2023-07-02 10:35:04,623 [prior] Evaluating prior at array([0.31860015, 0.48231671])
 2023-07-02 10:35:04,623 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,623 [model] Got input parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48231671247591823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,623 [classy] Got parameters {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,623 [classy] Computing new state
 2023-07-02 10:35:04,623 [classy] Setting parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,671 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53052690318833}
 2023-07-02 10:35:04,671 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,673 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00246162
 2023-07-02 10:35:04,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48231671247591823, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,673 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,694 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50892
 2023-07-02 10:35:04,694 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,694 [mcmc] New sample, #1004:
   Omega_m:0.3141222, b1:0.4904875
 2023-07-02 10:35:04,694 [model] Posterior to be computed for parameters {'Omega_m': 0.3186001496824632, 'b1': 0.4625306730208523}
 2023-07-02 10:35:04,694 [prior] Evaluating prior at array([0.31860015, 0.46253067])
 2023-07-02 10:35:04,694 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,694 [model] Got input parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4625306730208523, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,694 [classy] Got parameters {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,694 [classy] Re-using computed results
 2023-07-02 10:35:04,694 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53052690318833}
 2023-07-02 10:35:04,694 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,694 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4625306730208523, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,694 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,714 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.297425
 2023-07-02 10:35:04,714 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,714 [model] Posterior to be computed for parameters {'Omega_m': 0.3357149786952634, 'b1': 0.45108765737105627}
 2023-07-02 10:35:04,714 [prior] Evaluating prior at array([0.33571498, 0.45108766])
 2023-07-02 10:35:04,714 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,714 [model] Got input parameters: {'Omega_m': 0.3357149786952634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45108765737105627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,714 [classy] Got parameters {'Omega_m': 0.3357149786952634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,714 [classy] Computing new state
 2023-07-02 10:35:04,714 [classy] Setting parameters: {'Omega_m': 0.3357149786952634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.55359667338078}
 2023-07-02 10:35:04,762 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,764 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0314754
 2023-07-02 10:35:04,764 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45108765737105627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,764 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,784 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.382344
 2023-07-02 10:35:04,784 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,784 [model] Posterior to be computed for parameters {'Omega_m': 0.3186001496824632, 'b1': 0.46515693322959323}
 2023-07-02 10:35:04,784 [prior] Evaluating prior at array([0.31860015, 0.46515693])
 2023-07-02 10:35:04,784 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,784 [model] Got input parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46515693322959323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,784 [classy] Got parameters {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,784 [classy] Re-using computed results
 2023-07-02 10:35:04,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53052690318833}
 2023-07-02 10:35:04,784 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46515693322959323, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,784 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,804 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.70427
 2023-07-02 10:35:04,804 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,804 [model] Posterior to be computed for parameters {'Omega_m': 0.31283210097420755, 'b1': 0.49284154511216155}
 2023-07-02 10:35:04,804 [prior] Evaluating prior at array([0.3128321 , 0.49284155])
 2023-07-02 10:35:04,804 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,804 [model] Got input parameters: {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49284154511216155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,804 [classy] Got parameters {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,804 [classy] Computing new state
 2023-07-02 10:35:04,804 [classy] Setting parameters: {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21825539093967}
 2023-07-02 10:35:04,853 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,855 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000209809
 2023-07-02 10:35:04,855 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49284154511216155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,855 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,874 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54686
 2023-07-02 10:35:04,874 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,874 [mcmc] New sample, #1005:
   Omega_m:0.3186001, b1:0.4823167
 2023-07-02 10:35:04,875 [model] Posterior to be computed for parameters {'Omega_m': 0.31283210097420755, 'b1': 0.49567106674399247}
 2023-07-02 10:35:04,875 [prior] Evaluating prior at array([0.3128321 , 0.49567107])
 2023-07-02 10:35:04,875 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,875 [model] Got input parameters: {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49567106674399247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,875 [classy] Got parameters {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,875 [classy] Re-using computed results
 2023-07-02 10:35:04,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21825539093967}
 2023-07-02 10:35:04,875 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,875 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49567106674399247, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,875 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,895 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69724
 2023-07-02 10:35:04,895 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,895 [mcmc] New sample, #1006:
   Omega_m:0.3128321, b1:0.4928415
 2023-07-02 10:35:04,895 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.4836212131828336}
 2023-07-02 10:35:04,895 [prior] Evaluating prior at array([0.31943592, 0.48362121])
 2023-07-02 10:35:04,895 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,896 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4836212131828336, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,896 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,896 [classy] Computing new state
 2023-07-02 10:35:04,896 [classy] Setting parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:04,942 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:04,942 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:04,944 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00311524
 2023-07-02 10:35:04,944 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4836212131828336, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,944 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,963 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62527
 2023-07-02 10:35:04,963 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,963 [mcmc] New sample, #1007:
   Omega_m:0.3128321, b1:0.4956711
 2023-07-02 10:35:04,963 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5158522859490702}
 2023-07-02 10:35:04,964 [prior] Evaluating prior at array([0.31943592, 0.51585229])
 2023-07-02 10:35:04,964 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,964 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5158522859490702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,964 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,964 [classy] Re-using computed results
 2023-07-02 10:35:04,964 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:04,964 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:04,964 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5158522859490702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,964 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:04,984 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2892
 2023-07-02 10:35:04,984 [model] Computed derived parameters: {}
 2023-07-02 10:35:04,984 [model] Posterior to be computed for parameters {'Omega_m': 0.2810559809136331, 'b1': 0.553652259757853}
 2023-07-02 10:35:04,984 [prior] Evaluating prior at array([0.28105598, 0.55365226])
 2023-07-02 10:35:04,984 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:04,984 [model] Got input parameters: {'Omega_m': 0.2810559809136331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.553652259757853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:04,984 [classy] Got parameters {'Omega_m': 0.2810559809136331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:04,984 [classy] Computing new state
 2023-07-02 10:35:04,984 [classy] Setting parameters: {'Omega_m': 0.2810559809136331, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,030 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.22000155237208}
 2023-07-02 10:35:05,030 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,032 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0658585
 2023-07-02 10:35:05,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.553652259757853, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,032 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,052 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.80674
 2023-07-02 10:35:05,053 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,053 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.527157235678055}
 2023-07-02 10:35:05,053 [prior] Evaluating prior at array([0.31943592, 0.52715724])
 2023-07-02 10:35:05,053 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,053 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.527157235678055, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,053 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,053 [classy] Re-using computed results
 2023-07-02 10:35:05,053 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:05,053 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,053 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.527157235678055, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,053 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,072 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.579564
 2023-07-02 10:35:05,073 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,073 [model] Posterior to be computed for parameters {'Omega_m': 0.28769412846101794, 'b1': 0.541539776752826}
 2023-07-02 10:35:05,073 [prior] Evaluating prior at array([0.28769413, 0.54153978])
 2023-07-02 10:35:05,073 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,073 [model] Got input parameters: {'Omega_m': 0.28769412846101794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.541539776752826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,073 [classy] Got parameters {'Omega_m': 0.28769412846101794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,073 [classy] Computing new state
 2023-07-02 10:35:05,073 [classy] Setting parameters: {'Omega_m': 0.28769412846101794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,119 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.35258196336758}
 2023-07-02 10:35:05,120 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,123 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.040344
 2023-07-02 10:35:05,123 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.541539776752826, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,123 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,151 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.02545
 2023-07-02 10:35:05,151 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,151 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.45740156160562223}
 2023-07-02 10:35:05,151 [prior] Evaluating prior at array([0.31943592, 0.45740156])
 2023-07-02 10:35:05,151 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,151 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45740156160562223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,151 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,151 [classy] Re-using computed results
 2023-07-02 10:35:05,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:05,152 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45740156160562223, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,152 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,171 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.354989
 2023-07-02 10:35:05,171 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,171 [model] Posterior to be computed for parameters {'Omega_m': 0.3296361182228213, 'b1': 0.4650091430842509}
 2023-07-02 10:35:05,171 [prior] Evaluating prior at array([0.32963612, 0.46500914])
 2023-07-02 10:35:05,171 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,171 [model] Got input parameters: {'Omega_m': 0.3296361182228213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4650091430842509, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,171 [classy] Got parameters {'Omega_m': 0.3296361182228213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,171 [classy] Computing new state
 2023-07-02 10:35:05,171 [classy] Setting parameters: {'Omega_m': 0.3296361182228213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2451206559734}
 2023-07-02 10:35:05,218 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0175014
 2023-07-02 10:35:05,220 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4650091430842509, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,220 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,240 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61351
 2023-07-02 10:35:05,240 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,240 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.47190281592175476}
 2023-07-02 10:35:05,240 [prior] Evaluating prior at array([0.31943592, 0.47190282])
 2023-07-02 10:35:05,240 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,240 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47190281592175476, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,240 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,240 [classy] Re-using computed results
 2023-07-02 10:35:05,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:05,241 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,241 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47190281592175476, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,241 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,260 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72422
 2023-07-02 10:35:05,260 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,260 [model] Posterior to be computed for parameters {'Omega_m': 0.27421586656949504, 'b1': 0.5661332671705994}
 2023-07-02 10:35:05,260 [prior] Evaluating prior at array([0.27421587, 0.56613327])
 2023-07-02 10:35:05,260 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,260 [model] Got input parameters: {'Omega_m': 0.27421586656949504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5661332671705994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,260 [classy] Got parameters {'Omega_m': 0.27421586656949504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,260 [classy] Computing new state
 2023-07-02 10:35:05,260 [classy] Setting parameters: {'Omega_m': 0.27421586656949504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13236186098842}
 2023-07-02 10:35:05,307 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.099339
 2023-07-02 10:35:05,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5661332671705994, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,309 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,329 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.44517
 2023-07-02 10:35:05,329 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,329 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5044123233255025}
 2023-07-02 10:35:05,329 [prior] Evaluating prior at array([0.31943592, 0.50441232])
 2023-07-02 10:35:05,329 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,330 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5044123233255025, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,330 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,330 [classy] Re-using computed results
 2023-07-02 10:35:05,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:05,330 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5044123233255025, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,330 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,350 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.425
 2023-07-02 10:35:05,350 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,350 [mcmc] New sample, #1008:
   Omega_m:0.3194359, b1:0.4836212
 2023-07-02 10:35:05,350 [model] Posterior to be computed for parameters {'Omega_m': 0.30400604035490675, 'b1': 0.5325668971402411}
 2023-07-02 10:35:05,350 [prior] Evaluating prior at array([0.30400604, 0.5325669 ])
 2023-07-02 10:35:05,350 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,350 [model] Got input parameters: {'Omega_m': 0.30400604035490675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5325668971402411, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,350 [classy] Got parameters {'Omega_m': 0.30400604035490675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,350 [classy] Computing new state
 2023-07-02 10:35:05,350 [classy] Setting parameters: {'Omega_m': 0.30400604035490675, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,397 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.29270557354687}
 2023-07-02 10:35:05,397 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,399 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00470462
 2023-07-02 10:35:05,399 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5325668971402411, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,399 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,418 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.78403
 2023-07-02 10:35:05,418 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,419 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5314609703453154}
 2023-07-02 10:35:05,419 [prior] Evaluating prior at array([0.31943592, 0.53146097])
 2023-07-02 10:35:05,419 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,419 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5314609703453154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,419 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,419 [classy] Re-using computed results
 2023-07-02 10:35:05,419 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:05,419 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5314609703453154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,419 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.49112
 2023-07-02 10:35:05,438 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,438 [model] Posterior to be computed for parameters {'Omega_m': 0.3666060024188422, 'b1': 0.41834211210763506}
 2023-07-02 10:35:05,438 [prior] Evaluating prior at array([0.366606  , 0.41834211])
 2023-07-02 10:35:05,439 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,439 [model] Got input parameters: {'Omega_m': 0.3666060024188422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41834211210763506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,439 [classy] Got parameters {'Omega_m': 0.3666060024188422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,439 [classy] Computing new state
 2023-07-02 10:35:05,439 [classy] Setting parameters: {'Omega_m': 0.3666060024188422, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,485 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.20676856243296}
 2023-07-02 10:35:05,485 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,487 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.158222
 2023-07-02 10:35:05,487 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41834211210763506, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,487 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,507 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.35011
 2023-07-02 10:35:05,507 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,507 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5804313589430583}
 2023-07-02 10:35:05,507 [prior] Evaluating prior at array([0.31943592, 0.58043136])
 2023-07-02 10:35:05,507 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,508 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5804313589430583, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,508 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,508 [classy] Re-using computed results
 2023-07-02 10:35:05,508 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
 2023-07-02 10:35:05,508 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,508 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5804313589430583, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,508 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,527 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.1246
 2023-07-02 10:35:05,527 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,527 [model] Posterior to be computed for parameters {'Omega_m': 0.3109572151205396, 'b1': 0.5198832401994021}
 2023-07-02 10:35:05,527 [prior] Evaluating prior at array([0.31095722, 0.51988324])
 2023-07-02 10:35:05,527 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,527 [model] Got input parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5198832401994021, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,527 [classy] Got parameters {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,528 [classy] Computing new state
 2023-07-02 10:35:05,528 [classy] Setting parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44424411384878}
 2023-07-02 10:35:05,574 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000345867
 2023-07-02 10:35:05,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5198832401994021, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,576 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,596 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41989
 2023-07-02 10:35:05,596 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,596 [mcmc] New sample, #1009:
   Omega_m:0.3194359, b1:0.5044123
 2023-07-02 10:35:05,596 [model] Posterior to be computed for parameters {'Omega_m': 0.3109572151205396, 'b1': 0.54136738611382}
 2023-07-02 10:35:05,596 [prior] Evaluating prior at array([0.31095722, 0.54136739])
 2023-07-02 10:35:05,596 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,597 [model] Got input parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.54136738611382, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,597 [classy] Got parameters {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,597 [classy] Re-using computed results
 2023-07-02 10:35:05,597 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44424411384878}
 2023-07-02 10:35:05,597 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.54136738611382, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,597 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,616 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.325742
 2023-07-02 10:35:05,616 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,616 [mcmc] New sample, #1010:
   Omega_m:0.3109572, b1:0.5198832
 2023-07-02 10:35:05,616 [model] Posterior to be computed for parameters {'Omega_m': 0.2855623427685354, 'b1': 0.5877048556537461}
 2023-07-02 10:35:05,616 [prior] Evaluating prior at array([0.28556234, 0.58770486])
 2023-07-02 10:35:05,616 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,616 [model] Got input parameters: {'Omega_m': 0.2855623427685354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5877048556537461, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,616 [classy] Got parameters {'Omega_m': 0.2855623427685354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,616 [classy] Computing new state
 2023-07-02 10:35:05,616 [classy] Setting parameters: {'Omega_m': 0.2855623427685354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,662 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.62923438209796}
 2023-07-02 10:35:05,663 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0478094
 2023-07-02 10:35:05,665 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5877048556537461, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,665 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.77621
 2023-07-02 10:35:05,684 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,684 [model] Posterior to be computed for parameters {'Omega_m': 0.3109572151205396, 'b1': 0.5802191203371481}
 2023-07-02 10:35:05,684 [prior] Evaluating prior at array([0.31095722, 0.58021912])
 2023-07-02 10:35:05,684 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,684 [model] Got input parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5802191203371481, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,684 [classy] Got parameters {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,685 [classy] Re-using computed results
 2023-07-02 10:35:05,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44424411384878}
 2023-07-02 10:35:05,685 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5802191203371481, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,685 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,704 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.3548
 2023-07-02 10:35:05,705 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5379474753056178}
 2023-07-02 10:35:05,705 [prior] Evaluating prior at array([0.31283147, 0.53794748])
 2023-07-02 10:35:05,705 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,705 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5379474753056178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,705 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,705 [classy] Computing new state
 2023-07-02 10:35:05,705 [classy] Setting parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
 2023-07-02 10:35:05,752 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000209781
 2023-07-02 10:35:05,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5379474753056178, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,754 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,773 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.257545
 2023-07-02 10:35:05,773 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,774 [mcmc] New sample, #1011:
   Omega_m:0.3109572, b1:0.5413674
 2023-07-02 10:35:05,774 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5207644652408809}
 2023-07-02 10:35:05,774 [prior] Evaluating prior at array([0.31283147, 0.52076447])
 2023-07-02 10:35:05,774 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,774 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5207644652408809, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,774 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,774 [classy] Re-using computed results
 2023-07-02 10:35:05,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
 2023-07-02 10:35:05,774 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5207644652408809, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,774 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,793 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15237
 2023-07-02 10:35:05,793 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,793 [mcmc] New sample, #1012:
   Omega_m:0.3128315, b1:0.5379475
 2023-07-02 10:35:05,794 [model] Posterior to be computed for parameters {'Omega_m': 0.357226753630325, 'b1': 0.4397573585943402}
 2023-07-02 10:35:05,794 [prior] Evaluating prior at array([0.35722675, 0.43975736])
 2023-07-02 10:35:05,794 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,794 [model] Got input parameters: {'Omega_m': 0.357226753630325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4397573585943402, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,794 [classy] Got parameters {'Omega_m': 0.357226753630325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,794 [classy] Computing new state
 2023-07-02 10:35:05,794 [classy] Setting parameters: {'Omega_m': 0.357226753630325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.1946026330719}
 2023-07-02 10:35:05,840 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.110526
 2023-07-02 10:35:05,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4397573585943402, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,842 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,862 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.07196
 2023-07-02 10:35:05,862 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,862 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5256307579423719}
 2023-07-02 10:35:05,862 [prior] Evaluating prior at array([0.31283147, 0.52563076])
 2023-07-02 10:35:05,862 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,862 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5256307579423719, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,862 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,863 [classy] Re-using computed results
 2023-07-02 10:35:05,863 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
 2023-07-02 10:35:05,863 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,863 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5256307579423719, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,863 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,882 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64288
 2023-07-02 10:35:05,882 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3061705766051662, 'b1': 0.532918450917833}
 2023-07-02 10:35:05,882 [prior] Evaluating prior at array([0.30617058, 0.53291845])
 2023-07-02 10:35:05,882 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,882 [model] Got input parameters: {'Omega_m': 0.3061705766051662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.532918450917833, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,882 [classy] Got parameters {'Omega_m': 0.3061705766051662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,882 [classy] Computing new state
 2023-07-02 10:35:05,882 [classy] Setting parameters: {'Omega_m': 0.3061705766051662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:05,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.02668982745112}
 2023-07-02 10:35:05,929 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:05,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00268564
 2023-07-02 10:35:05,931 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.532918450917833, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,931 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,951 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70853
 2023-07-02 10:35:05,951 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,951 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5469439941427626}
 2023-07-02 10:35:05,951 [prior] Evaluating prior at array([0.31283147, 0.54694399])
 2023-07-02 10:35:05,951 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,951 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5469439941427626, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,951 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,951 [classy] Re-using computed results
 2023-07-02 10:35:05,951 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
 2023-07-02 10:35:05,951 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:05,951 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5469439941427626, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,951 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:05,971 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.21321
 2023-07-02 10:35:05,971 [model] Computed derived parameters: {}
 2023-07-02 10:35:05,971 [model] Posterior to be computed for parameters {'Omega_m': 0.33891877381913726, 'b1': 0.4731635299300092}
 2023-07-02 10:35:05,971 [prior] Evaluating prior at array([0.33891877, 0.47316353])
 2023-07-02 10:35:05,971 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:05,971 [model] Got input parameters: {'Omega_m': 0.33891877381913726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4731635299300092, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:05,971 [classy] Got parameters {'Omega_m': 0.33891877381913726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:05,971 [classy] Computing new state
 2023-07-02 10:35:05,971 [classy] Setting parameters: {'Omega_m': 0.33891877381913726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,018 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.19367035062794}
 2023-07-02 10:35:06,018 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0403893
 2023-07-02 10:35:06,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4731635299300092, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,020 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,039 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.663637
 2023-07-02 10:35:06,039 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,039 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5576830607960829}
 2023-07-02 10:35:06,039 [prior] Evaluating prior at array([0.31283147, 0.55768306])
 2023-07-02 10:35:06,039 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,039 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5576830607960829, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,039 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,039 [classy] Re-using computed results
 2023-07-02 10:35:06,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
 2023-07-02 10:35:06,039 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5576830607960829, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,059 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.19427
 2023-07-02 10:35:06,059 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,059 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.5251299916918357}
 2023-07-02 10:35:06,059 [prior] Evaluating prior at array([0.31043898, 0.52512999])
 2023-07-02 10:35:06,060 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,060 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5251299916918357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,060 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,060 [classy] Computing new state
 2023-07-02 10:35:06,060 [classy] Setting parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
 2023-07-02 10:35:06,107 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,109 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000460153
 2023-07-02 10:35:06,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5251299916918357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,109 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,132 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05431
 2023-07-02 10:35:06,132 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,133 [mcmc] New sample, #1013:
   Omega_m:0.3128315, b1:0.5207645
 2023-07-02 10:35:06,133 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.6359790755516318}
 2023-07-02 10:35:06,133 [prior] Evaluating prior at array([0.31043898, 0.63597908])
 2023-07-02 10:35:06,133 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,133 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6359790755516318, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,133 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,133 [classy] Re-using computed results
 2023-07-02 10:35:06,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
 2023-07-02 10:35:06,133 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6359790755516318, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,133 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,160 [fs_likelihood.fslikelihood] Computed log-likelihood = -46.5261
 2023-07-02 10:35:06,160 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,161 [model] Posterior to be computed for parameters {'Omega_m': 0.27538262473486586, 'b1': 0.5890965549937988}
 2023-07-02 10:35:06,161 [prior] Evaluating prior at array([0.27538262, 0.58909655])
 2023-07-02 10:35:06,161 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,161 [model] Got input parameters: {'Omega_m': 0.27538262473486586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5890965549937988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,161 [classy] Got parameters {'Omega_m': 0.27538262473486586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,161 [classy] Computing new state
 2023-07-02 10:35:06,161 [classy] Setting parameters: {'Omega_m': 0.27538262473486586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.97537772925733}
 2023-07-02 10:35:06,208 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,209 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0930955
 2023-07-02 10:35:06,210 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5890965549937988, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,210 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,229 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.35736
 2023-07-02 10:35:06,229 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,229 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.5082245865207342}
 2023-07-02 10:35:06,229 [prior] Evaluating prior at array([0.31043898, 0.50822459])
 2023-07-02 10:35:06,229 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,229 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5082245865207342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,229 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,229 [classy] Re-using computed results
 2023-07-02 10:35:06,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
 2023-07-02 10:35:06,229 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,229 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5082245865207342, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,230 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,249 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79672
 2023-07-02 10:35:06,249 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,249 [mcmc] New sample, #1014:
   Omega_m:0.310439, b1:0.52513
 2023-07-02 10:35:06,249 [model] Posterior to be computed for parameters {'Omega_m': 0.3245244596700607, 'b1': 0.48252311574549644}
 2023-07-02 10:35:06,249 [prior] Evaluating prior at array([0.32452446, 0.48252312])
 2023-07-02 10:35:06,250 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,250 [model] Got input parameters: {'Omega_m': 0.3245244596700607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48252311574549644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,250 [classy] Got parameters {'Omega_m': 0.3245244596700607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,250 [classy] Computing new state
 2023-07-02 10:35:06,250 [classy] Setting parameters: {'Omega_m': 0.3245244596700607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,297 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.83563703822506}
 2023-07-02 10:35:06,297 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0088323
 2023-07-02 10:35:06,299 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48252311574549644, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,299 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,320 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45515
 2023-07-02 10:35:06,320 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,320 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.5241135293384505}
 2023-07-02 10:35:06,320 [prior] Evaluating prior at array([0.31043898, 0.52411353])
 2023-07-02 10:35:06,320 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,320 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241135293384505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,320 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,320 [classy] Re-using computed results
 2023-07-02 10:35:06,320 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
 2023-07-02 10:35:06,320 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,320 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241135293384505, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,320 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,339 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14368
 2023-07-02 10:35:06,339 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,340 [model] Posterior to be computed for parameters {'Omega_m': 0.30731123900552176, 'b1': 0.5139317039506722}
 2023-07-02 10:35:06,340 [prior] Evaluating prior at array([0.30731124, 0.5139317 ])
 2023-07-02 10:35:06,340 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,340 [model] Got input parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5139317039506722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,340 [classy] Got parameters {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,340 [classy] Computing new state
 2023-07-02 10:35:06,340 [classy] Setting parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,386 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.88716812632163}
 2023-07-02 10:35:06,387 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,388 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00186464
 2023-07-02 10:35:06,388 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5139317039506722, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,388 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,409 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56541
 2023-07-02 10:35:06,409 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,409 [mcmc] New sample, #1015:
   Omega_m:0.310439, b1:0.5082246
 2023-07-02 10:35:06,409 [model] Posterior to be computed for parameters {'Omega_m': 0.30731123900552176, 'b1': 0.5126146077356437}
 2023-07-02 10:35:06,409 [prior] Evaluating prior at array([0.30731124, 0.51261461])
 2023-07-02 10:35:06,409 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,409 [model] Got input parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5126146077356437, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,409 [classy] Got parameters {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,409 [classy] Re-using computed results
 2023-07-02 10:35:06,409 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.88716812632163}
 2023-07-02 10:35:06,409 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,409 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5126146077356437, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,409 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,429 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55811
 2023-07-02 10:35:06,429 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,429 [mcmc] New sample, #1016:
   Omega_m:0.3073112, b1:0.5139317
 2023-07-02 10:35:06,429 [model] Posterior to be computed for parameters {'Omega_m': 0.33485263836002027, 'b1': 0.4623604172051172}
 2023-07-02 10:35:06,429 [prior] Evaluating prior at array([0.33485264, 0.46236042])
 2023-07-02 10:35:06,429 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,429 [model] Got input parameters: {'Omega_m': 0.33485263836002027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4623604172051172, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,429 [classy] Got parameters {'Omega_m': 0.33485263836002027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,429 [classy] Computing new state
 2023-07-02 10:35:06,429 [classy] Setting parameters: {'Omega_m': 0.33485263836002027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,476 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.6510032450243}
 2023-07-02 10:35:06,476 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,478 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292566
 2023-07-02 10:35:06,478 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4623604172051172, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,478 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,497 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.915826
 2023-07-02 10:35:06,497 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,498 [model] Posterior to be computed for parameters {'Omega_m': 0.30731123900552176, 'b1': 0.5510394829791909}
 2023-07-02 10:35:06,498 [prior] Evaluating prior at array([0.30731124, 0.55103948])
 2023-07-02 10:35:06,498 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,498 [model] Got input parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5510394829791909, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,498 [classy] Got parameters {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,498 [classy] Re-using computed results
 2023-07-02 10:35:06,498 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.88716812632163}
 2023-07-02 10:35:06,498 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,498 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5510394829791909, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,498 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,518 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.17784
 2023-07-02 10:35:06,518 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,518 [model] Posterior to be computed for parameters {'Omega_m': 0.31569074546303894, 'b1': 0.49732470511858357}
 2023-07-02 10:35:06,518 [prior] Evaluating prior at array([0.31569075, 0.49732471])
 2023-07-02 10:35:06,518 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,518 [model] Got input parameters: {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49732470511858357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,518 [classy] Got parameters {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,519 [classy] Computing new state
 2023-07-02 10:35:06,519 [classy] Setting parameters: {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,565 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87600437085086}
 2023-07-02 10:35:06,565 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,567 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000828062
 2023-07-02 10:35:06,567 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49732470511858357, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,567 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91691
 2023-07-02 10:35:06,587 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,587 [mcmc] New sample, #1017:
   Omega_m:0.3073112, b1:0.5126146
 2023-07-02 10:35:06,587 [model] Posterior to be computed for parameters {'Omega_m': 0.31569074546303894, 'b1': 0.5235064712382926}
 2023-07-02 10:35:06,587 [prior] Evaluating prior at array([0.31569075, 0.52350647])
 2023-07-02 10:35:06,587 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,587 [model] Got input parameters: {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5235064712382926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,587 [classy] Got parameters {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,587 [classy] Re-using computed results
 2023-07-02 10:35:06,587 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87600437085086}
 2023-07-02 10:35:06,587 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,587 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5235064712382926, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,587 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,607 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.27779
 2023-07-02 10:35:06,607 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,607 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.5122249216125379}
 2023-07-02 10:35:06,608 [prior] Evaluating prior at array([0.3075248 , 0.51222492])
 2023-07-02 10:35:06,608 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,608 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122249216125379, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,608 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,608 [classy] Computing new state
 2023-07-02 10:35:06,608 [classy] Setting parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
 2023-07-02 10:35:06,654 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,657 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00172939
 2023-07-02 10:35:06,657 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122249216125379, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,657 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,676 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57769
 2023-07-02 10:35:06,677 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,677 [mcmc] New sample, #1018:
   Omega_m:0.3156907, b1:0.4973247
 2023-07-02 10:35:06,677 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.47678640078786116}
 2023-07-02 10:35:06,677 [prior] Evaluating prior at array([0.3075248, 0.4767864])
 2023-07-02 10:35:06,677 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,677 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47678640078786116, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,677 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,677 [classy] Re-using computed results
 2023-07-02 10:35:06,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
 2023-07-02 10:35:06,677 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,677 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47678640078786116, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,677 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,697 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.970283
 2023-07-02 10:35:06,697 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,697 [model] Posterior to be computed for parameters {'Omega_m': 0.23502993489670398, 'b1': 0.6445047263793846}
 2023-07-02 10:35:06,697 [prior] Evaluating prior at array([0.23502993, 0.64450473])
 2023-07-02 10:35:06,697 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,697 [model] Got input parameters: {'Omega_m': 0.23502993489670398, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6445047263793846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,697 [classy] Got parameters {'Omega_m': 0.23502993489670398, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,697 [classy] Computing new state
 2023-07-02 10:35:06,697 [classy] Setting parameters: {'Omega_m': 0.23502993489670398, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.76128523408792}
 2023-07-02 10:35:06,743 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.453514
 2023-07-02 10:35:06,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6445047263793846, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,745 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,766 [fs_likelihood.fslikelihood] Computed log-likelihood = -47.475
 2023-07-02 10:35:06,766 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,766 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.5641447840570022}
 2023-07-02 10:35:06,766 [prior] Evaluating prior at array([0.3075248 , 0.56414478])
 2023-07-02 10:35:06,766 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,766 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641447840570022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,766 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,766 [classy] Re-using computed results
 2023-07-02 10:35:06,766 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
 2023-07-02 10:35:06,766 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641447840570022, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,766 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.5094
 2023-07-02 10:35:06,786 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,786 [model] Posterior to be computed for parameters {'Omega_m': 0.2974926621607847, 'b1': 0.5305303506920175}
 2023-07-02 10:35:06,786 [prior] Evaluating prior at array([0.29749266, 0.53053035])
 2023-07-02 10:35:06,787 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,787 [model] Got input parameters: {'Omega_m': 0.2974926621607847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305303506920175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,787 [classy] Got parameters {'Omega_m': 0.2974926621607847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,787 [classy] Computing new state
 2023-07-02 10:35:06,787 [classy] Setting parameters: {'Omega_m': 0.2974926621607847, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.10336947977225}
 2023-07-02 10:35:06,834 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,836 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0145151
 2023-07-02 10:35:06,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305303506920175, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,836 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,855 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.02262
 2023-07-02 10:35:06,855 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,855 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.6005456261154756}
 2023-07-02 10:35:06,855 [prior] Evaluating prior at array([0.3075248 , 0.60054563])
 2023-07-02 10:35:06,855 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,856 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6005456261154756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,856 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,856 [classy] Re-using computed results
 2023-07-02 10:35:06,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
 2023-07-02 10:35:06,856 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,856 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6005456261154756, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,856 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,877 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.2859
 2023-07-02 10:35:06,877 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,877 [model] Posterior to be computed for parameters {'Omega_m': 0.3240326131346507, 'b1': 0.4821034811729985}
 2023-07-02 10:35:06,877 [prior] Evaluating prior at array([0.32403261, 0.48210348])
 2023-07-02 10:35:06,877 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,877 [model] Got input parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4821034811729985, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,877 [classy] Got parameters {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,877 [classy] Computing new state
 2023-07-02 10:35:06,877 [classy] Setting parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:06,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89289505253635}
 2023-07-02 10:35:06,924 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:06,926 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0081511
 2023-07-02 10:35:06,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4821034811729985, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,926 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,945 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49404
 2023-07-02 10:35:06,945 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,945 [mcmc] New sample, #1019:
   Omega_m:0.3075248, b1:0.5122249
 2023-07-02 10:35:06,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3240326131346507, 'b1': 0.4192901371143257}
 2023-07-02 10:35:06,946 [prior] Evaluating prior at array([0.32403261, 0.41929014])
 2023-07-02 10:35:06,946 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,946 [model] Got input parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4192901371143257, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,946 [classy] Got parameters {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,946 [classy] Re-using computed results
 2023-07-02 10:35:06,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89289505253635}
 2023-07-02 10:35:06,946 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:06,946 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4192901371143257, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,946 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:06,966 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.1415
 2023-07-02 10:35:06,966 [model] Computed derived parameters: {}
 2023-07-02 10:35:06,966 [model] Posterior to be computed for parameters {'Omega_m': 0.29198729253320754, 'b1': 0.540575878540625}
 2023-07-02 10:35:06,966 [prior] Evaluating prior at array([0.29198729, 0.54057588])
 2023-07-02 10:35:06,966 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:06,966 [model] Got input parameters: {'Omega_m': 0.29198729253320754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.540575878540625, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:06,967 [classy] Got parameters {'Omega_m': 0.29198729253320754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:06,967 [classy] Computing new state
 2023-07-02 10:35:06,967 [classy] Setting parameters: {'Omega_m': 0.29198729253320754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.80078028440124}
 2023-07-02 10:35:07,015 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0273402
 2023-07-02 10:35:07,019 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.540575878540625, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,019 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,039 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.416746
 2023-07-02 10:35:07,039 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,040 [model] Posterior to be computed for parameters {'Omega_m': 0.3240326131346507, 'b1': 0.4898941472097447}
 2023-07-02 10:35:07,040 [prior] Evaluating prior at array([0.32403261, 0.48989415])
 2023-07-02 10:35:07,040 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,040 [model] Got input parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4898941472097447, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,040 [classy] Got parameters {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,040 [classy] Re-using computed results
 2023-07-02 10:35:07,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89289505253635}
 2023-07-02 10:35:07,040 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4898941472097447, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,040 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,059 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40709
 2023-07-02 10:35:07,059 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,059 [mcmc] New sample, #1020:
   Omega_m:0.3240326, b1:0.4821035
 2023-07-02 10:35:07,060 [model] Posterior to be computed for parameters {'Omega_m': 0.32210066425083966, 'b1': 0.49341933218864154}
 2023-07-02 10:35:07,060 [prior] Evaluating prior at array([0.32210066, 0.49341933])
 2023-07-02 10:35:07,060 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,060 [model] Got input parameters: {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49341933218864154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,060 [classy] Got parameters {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,060 [classy] Computing new state
 2023-07-02 10:35:07,060 [classy] Setting parameters: {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11855611390976}
 2023-07-02 10:35:07,106 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00574002
 2023-07-02 10:35:07,108 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49341933218864154, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,108 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,133 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56921
 2023-07-02 10:35:07,134 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,134 [mcmc] New sample, #1021:
   Omega_m:0.3240326, b1:0.4898941
 2023-07-02 10:35:07,134 [model] Posterior to be computed for parameters {'Omega_m': 0.32210066425083966, 'b1': 0.5179895625729616}
 2023-07-02 10:35:07,134 [prior] Evaluating prior at array([0.32210066, 0.51798956])
 2023-07-02 10:35:07,134 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,134 [model] Got input parameters: {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5179895625729616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,134 [classy] Got parameters {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,134 [classy] Re-using computed results
 2023-07-02 10:35:07,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11855611390976}
 2023-07-02 10:35:07,134 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5179895625729616, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,134 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,159 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0584937
 2023-07-02 10:35:07,159 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,159 [model] Posterior to be computed for parameters {'Omega_m': 0.3316826280809165, 'b1': 0.47593533183792436}
 2023-07-02 10:35:07,159 [prior] Evaluating prior at array([0.33168263, 0.47593533])
 2023-07-02 10:35:07,159 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,160 [model] Got input parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47593533183792436, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,160 [classy] Got parameters {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,160 [classy] Computing new state
 2023-07-02 10:35:07,160 [classy] Setting parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01103906154577}
 2023-07-02 10:35:07,206 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,208 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0217686
 2023-07-02 10:35:07,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47593533183792436, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,208 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,228 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.40724
 2023-07-02 10:35:07,229 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,229 [mcmc] New sample, #1022:
   Omega_m:0.3221007, b1:0.4934193
 2023-07-02 10:35:07,229 [model] Posterior to be computed for parameters {'Omega_m': 0.3316826280809165, 'b1': 0.42690244653728865}
 2023-07-02 10:35:07,229 [prior] Evaluating prior at array([0.33168263, 0.42690245])
 2023-07-02 10:35:07,229 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,229 [model] Got input parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42690244653728865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,229 [classy] Got parameters {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,229 [classy] Re-using computed results
 2023-07-02 10:35:07,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01103906154577}
 2023-07-02 10:35:07,229 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,229 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42690244653728865, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,229 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,248 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.38707
 2023-07-02 10:35:07,248 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,249 [model] Posterior to be computed for parameters {'Omega_m': 0.34582129867748496, 'b1': 0.45013680806421313}
 2023-07-02 10:35:07,249 [prior] Evaluating prior at array([0.3458213 , 0.45013681])
 2023-07-02 10:35:07,249 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,249 [model] Got input parameters: {'Omega_m': 0.34582129867748496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45013680806421313, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,249 [classy] Got parameters {'Omega_m': 0.34582129867748496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,249 [classy] Computing new state
 2023-07-02 10:35:07,249 [classy] Setting parameters: {'Omega_m': 0.34582129867748496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,297 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42860489928856}
 2023-07-02 10:35:07,297 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0630884
 2023-07-02 10:35:07,299 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45013680806421313, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,299 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,319 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.7906
 2023-07-02 10:35:07,319 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,319 [model] Posterior to be computed for parameters {'Omega_m': 0.3316826280809165, 'b1': 0.4471023418328156}
 2023-07-02 10:35:07,319 [prior] Evaluating prior at array([0.33168263, 0.44710234])
 2023-07-02 10:35:07,320 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,320 [model] Got input parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4471023418328156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,320 [classy] Got parameters {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,320 [classy] Re-using computed results
 2023-07-02 10:35:07,320 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01103906154577}
 2023-07-02 10:35:07,320 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,320 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4471023418328156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,320 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,339 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0861262
 2023-07-02 10:35:07,339 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,339 [model] Posterior to be computed for parameters {'Omega_m': 0.3208541233473353, 'b1': 0.49569386817944155}
 2023-07-02 10:35:07,339 [prior] Evaluating prior at array([0.32085412, 0.49569387])
 2023-07-02 10:35:07,340 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,340 [model] Got input parameters: {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49569386817944155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,340 [classy] Got parameters {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,340 [classy] Computing new state
 2023-07-02 10:35:07,340 [classy] Setting parameters: {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,389 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26479654260697}
 2023-07-02 10:35:07,389 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,391 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00441031
 2023-07-02 10:35:07,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49569386817944155, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,391 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,410 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65353
 2023-07-02 10:35:07,410 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,410 [mcmc] New sample, #1023:
   Omega_m:0.3316826, b1:0.4759353
 2023-07-02 10:35:07,410 [model] Posterior to be computed for parameters {'Omega_m': 0.3208541233473353, 'b1': 0.4809719506029375}
 2023-07-02 10:35:07,410 [prior] Evaluating prior at array([0.32085412, 0.48097195])
 2023-07-02 10:35:07,411 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,411 [model] Got input parameters: {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4809719506029375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,411 [classy] Got parameters {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,411 [classy] Re-using computed results
 2023-07-02 10:35:07,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26479654260697}
 2023-07-02 10:35:07,411 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,411 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4809719506029375, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,411 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54492
 2023-07-02 10:35:07,432 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,432 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.49010851218382173}
 2023-07-02 10:35:07,432 [prior] Evaluating prior at array([0.32391513, 0.49010851])
 2023-07-02 10:35:07,432 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,432 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49010851218382173, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,432 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,432 [classy] Computing new state
 2023-07-02 10:35:07,432 [classy] Setting parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
 2023-07-02 10:35:07,480 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,482 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00799245
 2023-07-02 10:35:07,482 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49010851218382173, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,482 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,503 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41802
 2023-07-02 10:35:07,503 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,503 [mcmc] New sample, #1024:
   Omega_m:0.3208541, b1:0.4956939
 2023-07-02 10:35:07,503 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.4606982027946477}
 2023-07-02 10:35:07,503 [prior] Evaluating prior at array([0.32391513, 0.4606982 ])
 2023-07-02 10:35:07,503 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,503 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4606982027946477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,503 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,503 [classy] Re-using computed results
 2023-07-02 10:35:07,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
 2023-07-02 10:35:07,503 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4606982027946477, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,503 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,527 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05163
 2023-07-02 10:35:07,527 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,527 [model] Posterior to be computed for parameters {'Omega_m': 0.3475953664194987, 'b1': 0.4468997053602557}
 2023-07-02 10:35:07,527 [prior] Evaluating prior at array([0.34759537, 0.44689971])
 2023-07-02 10:35:07,527 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,527 [model] Got input parameters: {'Omega_m': 0.3475953664194987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4468997053602557, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,527 [classy] Got parameters {'Omega_m': 0.3475953664194987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,527 [classy] Computing new state
 2023-07-02 10:35:07,527 [classy] Setting parameters: {'Omega_m': 0.3475953664194987, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,577 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2342416526686}
 2023-07-02 10:35:07,577 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,578 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0696702
 2023-07-02 10:35:07,579 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4468997053602557, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,579 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,599 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.30224
 2023-07-02 10:35:07,599 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,599 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.4875687796484934}
 2023-07-02 10:35:07,599 [prior] Evaluating prior at array([0.32391513, 0.48756878])
 2023-07-02 10:35:07,599 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,599 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4875687796484934, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,599 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,599 [classy] Re-using computed results
 2023-07-02 10:35:07,599 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
 2023-07-02 10:35:07,599 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,599 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4875687796484934, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,599 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,621 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48291
 2023-07-02 10:35:07,621 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,621 [mcmc] New sample, #1025:
   Omega_m:0.3239151, b1:0.4901085
 2023-07-02 10:35:07,621 [model] Posterior to be computed for parameters {'Omega_m': 0.3318423058451499, 'b1': 0.4731042387698944}
 2023-07-02 10:35:07,621 [prior] Evaluating prior at array([0.33184231, 0.47310424])
 2023-07-02 10:35:07,621 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,622 [model] Got input parameters: {'Omega_m': 0.3318423058451499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4731042387698944, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,622 [classy] Got parameters {'Omega_m': 0.3318423058451499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,622 [classy] Computing new state
 2023-07-02 10:35:07,622 [classy] Setting parameters: {'Omega_m': 0.3318423058451499, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,670 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9928285230569}
 2023-07-02 10:35:07,671 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,672 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221204
 2023-07-02 10:35:07,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4731042387698944, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,673 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,693 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44434
 2023-07-02 10:35:07,693 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,693 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.5222298755311566}
 2023-07-02 10:35:07,693 [prior] Evaluating prior at array([0.32391513, 0.52222988])
 2023-07-02 10:35:07,693 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,693 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5222298755311566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,693 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,693 [classy] Re-using computed results
 2023-07-02 10:35:07,693 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
 2023-07-02 10:35:07,693 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,693 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5222298755311566, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,693 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,713 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.57568
 2023-07-02 10:35:07,713 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,713 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.5019596378600945}
 2023-07-02 10:35:07,713 [prior] Evaluating prior at array([0.31602834, 0.50195964])
 2023-07-02 10:35:07,713 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,713 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5019596378600945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,713 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,713 [classy] Computing new state
 2023-07-02 10:35:07,713 [classy] Setting parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
 2023-07-02 10:35:07,762 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,764 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000966025
 2023-07-02 10:35:07,764 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5019596378600945, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,764 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,785 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89005
 2023-07-02 10:35:07,785 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,785 [mcmc] New sample, #1026:
   Omega_m:0.3239151, b1:0.4875688
 2023-07-02 10:35:07,786 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.4688032408897801}
 2023-07-02 10:35:07,786 [prior] Evaluating prior at array([0.31602834, 0.46880324])
 2023-07-02 10:35:07,786 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,786 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4688032408897801, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,786 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,786 [classy] Re-using computed results
 2023-07-02 10:35:07,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
 2023-07-02 10:35:07,786 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4688032408897801, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,786 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,806 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.615974
 2023-07-02 10:35:07,806 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,806 [model] Posterior to be computed for parameters {'Omega_m': 0.33486431033566555, 'b1': 0.4675900531072232}
 2023-07-02 10:35:07,806 [prior] Evaluating prior at array([0.33486431, 0.46759005])
 2023-07-02 10:35:07,806 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,806 [model] Got input parameters: {'Omega_m': 0.33486431033566555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4675900531072232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,806 [classy] Got parameters {'Omega_m': 0.33486431033566555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,806 [classy] Computing new state
 2023-07-02 10:35:07,806 [classy] Setting parameters: {'Omega_m': 0.33486431033566555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,855 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.64968662982378}
 2023-07-02 10:35:07,855 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292859
 2023-07-02 10:35:07,857 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4675900531072232, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,857 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,878 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.895857
 2023-07-02 10:35:07,878 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,878 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.5435518277887451}
 2023-07-02 10:35:07,878 [prior] Evaluating prior at array([0.31602834, 0.54355183])
 2023-07-02 10:35:07,878 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,878 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5435518277887451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,878 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,878 [classy] Re-using computed results
 2023-07-02 10:35:07,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
 2023-07-02 10:35:07,878 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5435518277887451, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,878 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,898 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.81119
 2023-07-02 10:35:07,898 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,898 [model] Posterior to be computed for parameters {'Omega_m': 0.28946826962585825, 'b1': 0.5504232181834765}
 2023-07-02 10:35:07,898 [prior] Evaluating prior at array([0.28946827, 0.55042322])
 2023-07-02 10:35:07,898 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,898 [model] Got input parameters: {'Omega_m': 0.28946826962585825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5504232181834765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,898 [classy] Got parameters {'Omega_m': 0.28946826962585825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,898 [classy] Computing new state
 2023-07-02 10:35:07,898 [classy] Setting parameters: {'Omega_m': 0.28946826962585825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:07,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12369173085096}
 2023-07-02 10:35:07,947 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:07,949 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0346446
 2023-07-02 10:35:07,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5504232181834765, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,949 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,968 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25473
 2023-07-02 10:35:07,968 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,968 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.5391844009862896}
 2023-07-02 10:35:07,968 [prior] Evaluating prior at array([0.31602834, 0.5391844 ])
 2023-07-02 10:35:07,968 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,968 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5391844009862896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,969 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,969 [classy] Re-using computed results
 2023-07-02 10:35:07,969 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
 2023-07-02 10:35:07,969 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:07,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5391844009862896, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,969 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:07,989 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.73356
 2023-07-02 10:35:07,989 [model] Computed derived parameters: {}
 2023-07-02 10:35:07,989 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.49697262978946577}
 2023-07-02 10:35:07,989 [prior] Evaluating prior at array([0.31876143, 0.49697263])
 2023-07-02 10:35:07,989 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:07,989 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49697262978946577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:07,989 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:07,989 [classy] Computing new state
 2023-07-02 10:35:07,989 [classy] Setting parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,037 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00258141
 2023-07-02 10:35:08,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49697262978946577, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,039 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,058 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82381
 2023-07-02 10:35:08,058 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,058 [mcmc] New sample, #1027:
   Omega_m:0.3160283, b1:0.5019596
 2023-07-02 10:35:08,058 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4861198818226653}
 2023-07-02 10:35:08,058 [prior] Evaluating prior at array([0.31876143, 0.48611988])
 2023-07-02 10:35:08,058 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,058 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4861198818226653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,058 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,058 [classy] Re-using computed results
 2023-07-02 10:35:08,058 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,058 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4861198818226653, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,058 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,079 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70908
 2023-07-02 10:35:08,079 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,079 [mcmc] New sample, #1028:
   Omega_m:0.3187614, b1:0.4969726
 2023-07-02 10:35:08,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3310714915161198, 'b1': 0.46365797889239324}
 2023-07-02 10:35:08,079 [prior] Evaluating prior at array([0.33107149, 0.46365798])
 2023-07-02 10:35:08,079 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,079 [model] Got input parameters: {'Omega_m': 0.3310714915161198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46365797889239324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,079 [classy] Got parameters {'Omega_m': 0.3310714915161198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,079 [classy] Computing new state
 2023-07-02 10:35:08,079 [classy] Setting parameters: {'Omega_m': 0.3310714915161198, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0808057934897}
 2023-07-02 10:35:08,127 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,129 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0204472
 2023-07-02 10:35:08,130 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46365797889239324, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,130 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,150 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44618
 2023-07-02 10:35:08,150 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,150 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4695062984992326}
 2023-07-02 10:35:08,150 [prior] Evaluating prior at array([0.31876143, 0.4695063 ])
 2023-07-02 10:35:08,150 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,150 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4695062984992326, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,150 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,150 [classy] Re-using computed results
 2023-07-02 10:35:08,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,150 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4695062984992326, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,150 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,170 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.33326
 2023-07-02 10:35:08,170 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,170 [mcmc] New sample, #1029:
   Omega_m:0.3187614, b1:0.4861199
 2023-07-02 10:35:08,170 [model] Posterior to be computed for parameters {'Omega_m': 0.3298709082023951, 'b1': 0.44923507374834787}
 2023-07-02 10:35:08,170 [prior] Evaluating prior at array([0.32987091, 0.44923507])
 2023-07-02 10:35:08,171 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,171 [model] Got input parameters: {'Omega_m': 0.3298709082023951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44923507374834787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,171 [classy] Got parameters {'Omega_m': 0.3298709082023951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,171 [classy] Computing new state
 2023-07-02 10:35:08,171 [classy] Setting parameters: {'Omega_m': 0.3298709082023951, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.21820126031002}
 2023-07-02 10:35:08,218 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.017968
 2023-07-02 10:35:08,220 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44923507374834787, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,220 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,239 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.233302
 2023-07-02 10:35:08,239 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,239 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4854278396919156}
 2023-07-02 10:35:08,239 [prior] Evaluating prior at array([0.31876143, 0.48542784])
 2023-07-02 10:35:08,240 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,240 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4854278396919156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,240 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,240 [classy] Re-using computed results
 2023-07-02 10:35:08,240 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,240 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,240 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4854278396919156, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,240 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,259 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6804
 2023-07-02 10:35:08,259 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,259 [mcmc] New sample, #1030:
   Omega_m:0.3187614, b1:0.4695063
 2023-07-02 10:35:08,259 [model] Posterior to be computed for parameters {'Omega_m': 0.35260204325852296, 'b1': 0.42367960873004495}
 2023-07-02 10:35:08,259 [prior] Evaluating prior at array([0.35260204, 0.42367961])
 2023-07-02 10:35:08,259 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,259 [model] Got input parameters: {'Omega_m': 0.35260204325852296, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42367960873004495, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,260 [classy] Got parameters {'Omega_m': 0.35260204325852296, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,260 [classy] Computing new state
 2023-07-02 10:35:08,260 [classy] Setting parameters: {'Omega_m': 0.35260204325852296, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,308 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.69056120918876}
 2023-07-02 10:35:08,308 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0898457
 2023-07-02 10:35:08,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42367960873004495, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,309 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,329 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.99727
 2023-07-02 10:35:08,329 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,329 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.48285830005573693}
 2023-07-02 10:35:08,329 [prior] Evaluating prior at array([0.31876143, 0.4828583 ])
 2023-07-02 10:35:08,329 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,329 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48285830005573693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,330 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,330 [classy] Re-using computed results
 2023-07-02 10:35:08,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,330 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48285830005573693, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,330 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,349 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55187
 2023-07-02 10:35:08,349 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,349 [mcmc] New sample, #1031:
   Omega_m:0.3187614, b1:0.4854278
 2023-07-02 10:35:08,349 [model] Posterior to be computed for parameters {'Omega_m': 0.30433693805608064, 'b1': 0.5091783535553551}
 2023-07-02 10:35:08,349 [prior] Evaluating prior at array([0.30433694, 0.50917835])
 2023-07-02 10:35:08,349 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,349 [model] Got input parameters: {'Omega_m': 0.30433693805608064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5091783535553551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,349 [classy] Got parameters {'Omega_m': 0.30433693805608064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,349 [classy] Computing new state
 2023-07-02 10:35:08,350 [classy] Setting parameters: {'Omega_m': 0.30433693805608064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,397 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.25193240975852}
 2023-07-02 10:35:08,397 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,398 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00435659
 2023-07-02 10:35:08,399 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5091783535553551, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,399 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,418 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94041
 2023-07-02 10:35:08,418 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,418 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4904082641696383}
 2023-07-02 10:35:08,418 [prior] Evaluating prior at array([0.31876143, 0.49040826])
 2023-07-02 10:35:08,418 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,418 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904082641696383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,418 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,418 [classy] Re-using computed results
 2023-07-02 10:35:08,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,418 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904082641696383, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,418 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,438 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83004
 2023-07-02 10:35:08,438 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,438 [mcmc] New sample, #1032:
   Omega_m:0.3187614, b1:0.4828583
 2023-07-02 10:35:08,438 [model] Posterior to be computed for parameters {'Omega_m': 0.32691742349601877, 'b1': 0.47552619852620426}
 2023-07-02 10:35:08,438 [prior] Evaluating prior at array([0.32691742, 0.4755262 ])
 2023-07-02 10:35:08,438 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,438 [model] Got input parameters: {'Omega_m': 0.32691742349601877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47552619852620426, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,438 [classy] Got parameters {'Omega_m': 0.32691742349601877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,438 [classy] Computing new state
 2023-07-02 10:35:08,438 [classy] Setting parameters: {'Omega_m': 0.32691742349601877, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,485 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.55816136393182}
 2023-07-02 10:35:08,486 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,487 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0125322
 2023-07-02 10:35:08,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47552619852620426, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,488 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,507 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.16316
 2023-07-02 10:35:08,507 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,507 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.45951800180218555}
 2023-07-02 10:35:08,507 [prior] Evaluating prior at array([0.31876143, 0.459518  ])
 2023-07-02 10:35:08,507 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,507 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45951800180218555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,507 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,507 [classy] Re-using computed results
 2023-07-02 10:35:08,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
 2023-07-02 10:35:08,507 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,507 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45951800180218555, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,507 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,526 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.166277
 2023-07-02 10:35:08,526 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,526 [model] Posterior to be computed for parameters {'Omega_m': 0.3199822654120504, 'b1': 0.4881806301774465}
 2023-07-02 10:35:08,526 [prior] Evaluating prior at array([0.31998227, 0.48818063])
 2023-07-02 10:35:08,527 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,527 [model] Got input parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4881806301774465, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,527 [classy] Got parameters {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,527 [classy] Computing new state
 2023-07-02 10:35:08,527 [classy] Setting parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36738807560533}
 2023-07-02 10:35:08,574 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00358651
 2023-07-02 10:35:08,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4881806301774465, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,576 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,595 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77392
 2023-07-02 10:35:08,595 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,595 [mcmc] New sample, #1033:
   Omega_m:0.3187614, b1:0.4904083
 2023-07-02 10:35:08,595 [model] Posterior to be computed for parameters {'Omega_m': 0.3199822654120504, 'b1': 0.43240203612913003}
 2023-07-02 10:35:08,595 [prior] Evaluating prior at array([0.31998227, 0.43240204])
 2023-07-02 10:35:08,596 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,596 [model] Got input parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43240203612913003, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,596 [classy] Got parameters {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,596 [classy] Re-using computed results
 2023-07-02 10:35:08,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36738807560533}
 2023-07-02 10:35:08,596 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43240203612913003, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,596 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,615 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.05209
 2023-07-02 10:35:08,615 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,615 [model] Posterior to be computed for parameters {'Omega_m': 0.34702855530393056, 'b1': 0.43882985508154004}
 2023-07-02 10:35:08,615 [prior] Evaluating prior at array([0.34702856, 0.43882986])
 2023-07-02 10:35:08,616 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,616 [model] Got input parameters: {'Omega_m': 0.34702855530393056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43882985508154004, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,616 [classy] Got parameters {'Omega_m': 0.34702855530393056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,616 [classy] Computing new state
 2023-07-02 10:35:08,616 [classy] Setting parameters: {'Omega_m': 0.34702855530393056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,662 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2962409684692}
 2023-07-02 10:35:08,662 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0675348
 2023-07-02 10:35:08,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43882985508154004, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,664 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.08786
 2023-07-02 10:35:08,684 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,684 [model] Posterior to be computed for parameters {'Omega_m': 0.3199822654120504, 'b1': 0.4818369931368075}
 2023-07-02 10:35:08,684 [prior] Evaluating prior at array([0.31998227, 0.48183699])
 2023-07-02 10:35:08,684 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,684 [model] Got input parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4818369931368075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,684 [classy] Got parameters {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,685 [classy] Re-using computed results
 2023-07-02 10:35:08,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36738807560533}
 2023-07-02 10:35:08,685 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4818369931368075, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,685 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,704 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55976
 2023-07-02 10:35:08,704 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,704 [mcmc] New sample, #1034:
   Omega_m:0.3199823, b1:0.4881806
 2023-07-02 10:35:08,704 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.4919196601272578}
 2023-07-02 10:35:08,704 [prior] Evaluating prior at array([0.31445654, 0.49191966])
 2023-07-02 10:35:08,704 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,704 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4919196601272578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,704 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,705 [classy] Computing new state
 2023-07-02 10:35:08,705 [classy] Setting parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,751 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
 2023-07-02 10:35:08,751 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,753 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000439891
 2023-07-02 10:35:08,753 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4919196601272578, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,753 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,772 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68707
 2023-07-02 10:35:08,772 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,772 [mcmc] New sample, #1035:
   Omega_m:0.3199823, b1:0.481837
 2023-07-02 10:35:08,772 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.44981503289275676}
 2023-07-02 10:35:08,772 [prior] Evaluating prior at array([0.31445654, 0.44981503])
 2023-07-02 10:35:08,772 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,772 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44981503289275676, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,772 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,772 [classy] Re-using computed results
 2023-07-02 10:35:08,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
 2023-07-02 10:35:08,772 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,772 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44981503289275676, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,772 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,792 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.86562
 2023-07-02 10:35:08,793 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,793 [model] Posterior to be computed for parameters {'Omega_m': 0.3295677053360502, 'b1': 0.4643466500333471}
 2023-07-02 10:35:08,793 [prior] Evaluating prior at array([0.32956771, 0.46434665])
 2023-07-02 10:35:08,793 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,793 [model] Got input parameters: {'Omega_m': 0.3295677053360502, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4643466500333471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,793 [classy] Got parameters {'Omega_m': 0.3295677053360502, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,793 [classy] Computing new state
 2023-07-02 10:35:08,793 [classy] Setting parameters: {'Omega_m': 0.3295677053360502, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,839 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.25297019729933}
 2023-07-02 10:35:08,839 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,841 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0173664
 2023-07-02 10:35:08,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4643466500333471, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,841 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58469
 2023-07-02 10:35:08,861 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,861 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.5407098898760135}
 2023-07-02 10:35:08,861 [prior] Evaluating prior at array([0.31445654, 0.54070989])
 2023-07-02 10:35:08,861 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,861 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5407098898760135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,861 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,861 [classy] Re-using computed results
 2023-07-02 10:35:08,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
 2023-07-02 10:35:08,861 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,861 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5407098898760135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,861 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,881 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.42138
 2023-07-02 10:35:08,881 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,881 [model] Posterior to be computed for parameters {'Omega_m': 0.33446424786503753, 'b1': 0.4554120357087353}
 2023-07-02 10:35:08,881 [prior] Evaluating prior at array([0.33446425, 0.45541204])
 2023-07-02 10:35:08,881 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,881 [model] Got input parameters: {'Omega_m': 0.33446424786503753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4554120357087353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,881 [classy] Got parameters {'Omega_m': 0.33446424786503753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,881 [classy] Computing new state
 2023-07-02 10:35:08,881 [classy] Setting parameters: {'Omega_m': 0.33446424786503753, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:08,927 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.69495118105922}
 2023-07-02 10:35:08,927 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:08,929 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0282823
 2023-07-02 10:35:08,929 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4554120357087353, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,929 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,949 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.748278
 2023-07-02 10:35:08,949 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,949 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.5138059754665897}
 2023-07-02 10:35:08,949 [prior] Evaluating prior at array([0.31445654, 0.51380598])
 2023-07-02 10:35:08,949 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,949 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5138059754665897, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,949 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,949 [classy] Re-using computed results
 2023-07-02 10:35:08,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
 2023-07-02 10:35:08,949 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:08,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5138059754665897, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,949 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:08,969 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49932
 2023-07-02 10:35:08,969 [model] Computed derived parameters: {}
 2023-07-02 10:35:08,969 [mcmc] New sample, #1036:
   Omega_m:0.3144565, b1:0.4919197
 2023-07-02 10:35:08,969 [model] Posterior to be computed for parameters {'Omega_m': 0.34417623635635236, 'b1': 0.45957709753474135}
 2023-07-02 10:35:08,969 [prior] Evaluating prior at array([0.34417624, 0.4595771 ])
 2023-07-02 10:35:08,969 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:08,969 [model] Got input parameters: {'Omega_m': 0.34417623635635236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45957709753474135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:08,969 [classy] Got parameters {'Omega_m': 0.34417623635635236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:08,969 [classy] Computing new state
 2023-07-02 10:35:08,969 [classy] Setting parameters: {'Omega_m': 0.34417623635635236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:09,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6096585255666}
 2023-07-02 10:35:09,016 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:09,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0572549
 2023-07-02 10:35:09,018 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45957709753474135, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,018 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,037 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.65422
 2023-07-02 10:35:09,037 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,037 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.4589538282593211}
 2023-07-02 10:35:09,037 [prior] Evaluating prior at array([0.31445654, 0.45895383])
 2023-07-02 10:35:09,038 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,038 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4589538282593211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,038 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,038 [classy] Re-using computed results
 2023-07-02 10:35:09,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
 2023-07-02 10:35:09,038 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:09,038 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4589538282593211, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,038 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,057 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.71353
 2023-07-02 10:35:09,057 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,057 [model] Posterior to be computed for parameters {'Omega_m': 0.28590053202600774, 'b1': 0.565911503823339}
 2023-07-02 10:35:09,057 [prior] Evaluating prior at array([0.28590053, 0.5659115 ])
 2023-07-02 10:35:09,058 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,058 [model] Got input parameters: {'Omega_m': 0.28590053202600774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.565911503823339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,058 [classy] Got parameters {'Omega_m': 0.28590053202600774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,058 [classy] Computing new state
 2023-07-02 10:35:09,058 [classy] Setting parameters: {'Omega_m': 0.28590053202600774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:09,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.5852256997668}
 2023-07-02 10:35:09,104 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:09,106 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0465797
 2023-07-02 10:35:09,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.565911503823339, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,107 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,128 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.95988
 2023-07-02 10:35:09,128 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,128 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.5680557699525874}
 2023-07-02 10:35:09,128 [prior] Evaluating prior at array([0.31445654, 0.56805577])
 2023-07-02 10:35:09,128 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,128 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5680557699525874, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,128 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,128 [classy] Re-using computed results
 2023-07-02 10:35:09,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
 2023-07-02 10:35:09,128 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:09,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5680557699525874, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,128 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.89368
 2023-07-02 10:35:09,151 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,151 [model] Posterior to be computed for parameters {'Omega_m': 0.3186696435499658, 'b1': 0.5061184209503702}
 2023-07-02 10:35:09,151 [prior] Evaluating prior at array([0.31866964, 0.50611842])
 2023-07-02 10:35:09,151 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,151 [model] Got input parameters: {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061184209503702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,151 [classy] Got parameters {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,151 [classy] Computing new state
 2023-07-02 10:35:09,151 [classy] Setting parameters: {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:09,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5223102323367}
 2023-07-02 10:35:09,199 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:09,201 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00251284
 2023-07-02 10:35:09,201 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061184209503702, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,201 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,221 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4364
 2023-07-02 10:35:09,221 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,221 [mcmc] New sample, #1037:
   Omega_m:0.3144565, b1:0.513806
 2023-07-02 10:35:09,222 [model] Posterior to be computed for parameters {'Omega_m': 0.3186696435499658, 'b1': 0.5712602913875514}
 2023-07-02 10:35:09,222 [prior] Evaluating prior at array([0.31866964, 0.57126029])
 2023-07-02 10:35:09,222 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,222 [model] Got input parameters: {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5712602913875514, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,222 [classy] Got parameters {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,222 [classy] Re-using computed results
 2023-07-02 10:35:09,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5223102323367}
 2023-07-02 10:35:09,222 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:09,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5712602913875514, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,222 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.7246
 2023-07-02 10:35:09,243 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3219917227547285, 'b1': 0.5000566955033524}
 2023-07-02 10:35:09,243 [prior] Evaluating prior at array([0.32199172, 0.5000567 ])
 2023-07-02 10:35:09,243 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,243 [model] Got input parameters: {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5000566955033524, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,243 [classy] Got parameters {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,243 [classy] Computing new state
 2023-07-02 10:35:09,243 [classy] Setting parameters: {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:09,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13131686436915}
 2023-07-02 10:35:09,292 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:09,294 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0056167
 2023-07-02 10:35:09,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5000566955033524, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,294 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,315 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2519
 2023-07-02 10:35:09,315 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,315 [mcmc] New sample, #1038:
   Omega_m:0.3186696, b1:0.5061184
 2023-07-02 10:35:09,315 [model] Posterior to be computed for parameters {'Omega_m': 0.3219917227547285, 'b1': 0.4352841546914152}
 2023-07-02 10:35:09,315 [prior] Evaluating prior at array([0.32199172, 0.43528415])
 2023-07-02 10:35:09,315 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,315 [model] Got input parameters: {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4352841546914152, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,315 [classy] Got parameters {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,315 [classy] Re-using computed results
 2023-07-02 10:35:09,315 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13131686436915}
 2023-07-02 10:35:09,315 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:09,315 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4352841546914152, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,315 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,336 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.38444
 2023-07-02 10:35:09,336 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,336 [model] Posterior to be computed for parameters {'Omega_m': 0.3085284211800855, 'b1': 0.5246228881573046}
 2023-07-02 10:35:09,336 [prior] Evaluating prior at array([0.30852842, 0.52462289])
 2023-07-02 10:35:09,336 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,336 [model] Got input parameters: {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5246228881573046, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,336 [classy] Got parameters {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,336 [classy] Computing new state
 2023-07-02 10:35:09,336 [classy] Setting parameters: {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:09,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73878994153398}
 2023-07-02 10:35:09,385 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:09,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00117145
 2023-07-02 10:35:09,386 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5246228881573046, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,387 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,407 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2446
 2023-07-02 10:35:09,407 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,407 [mcmc] New sample, #1039:
   Omega_m:0.3219917, b1:0.5000567
 2023-07-02 10:35:09,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3085284211800855, 'b1': 0.5402539877013627}
 2023-07-02 10:35:09,407 [prior] Evaluating prior at array([0.30852842, 0.54025399])
 2023-07-02 10:35:09,407 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,407 [model] Got input parameters: {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5402539877013627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,407 [classy] Got parameters {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,407 [classy] Re-using computed results
 2023-07-02 10:35:09,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73878994153398}
 2023-07-02 10:35:09,407 [bao_likelihood.baolikelihood] Re-using computed results
 2023-07-02 10:35:09,407 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5402539877013627, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,407 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,427 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.486176
 2023-07-02 10:35:09,427 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,427 [model] Posterior to be computed for parameters {'Omega_m': 0.32769842517074427, 'b1': 0.489643800108165}
 2023-07-02 10:35:09,427 [prior] Evaluating prior at array([0.32769843, 0.4896438 ])
 2023-07-02 10:35:09,427 [prior] Got logpriors (internal) = -1.2809338454620642
 2023-07-02 10:35:09,427 [model] Got input parameters: {'Omega_m': 0.32769842517074427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489643800108165, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,427 [classy] Got parameters {'Omega_m': 0.32769842517074427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
 2023-07-02 10:35:09,427 [classy] Computing new state
 2023-07-02 10:35:09,427 [classy] Setting parameters: {'Omega_m': 0.32769842517074427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
 2023-07-02 10:35:09,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4679967540426}
 2023-07-02 10:35:09,475 [bao_likelihood.baolikelihood] Computing new state
 2023-07-02 10:35:09,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0138769
 2023-07-02 10:35:09,476 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489643800108165, 'sigmapar': 0.0, 'sigmaper': 0.0}
 2023-07-02 10:35:09,476 [fs_likelihood.fslikelihood] Computing new state
 2023-07-02 10:35:09,496 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67305
 2023-07-02 10:35:09,496 [model] Computed derived parameters: {}
 2023-07-02 10:35:09,497 [mcmc] New sample, #1040:
   Omega_m:0.3085284, b1:0.5246229
 2023-07-02 10:35:09,497 [mcmc] Learn + convergence test @ 1040 samples accepted.
 2023-07-02 10:35:09,497 [mcmc] Ready to check convergence and learn a new proposal covmat
 2023-07-02 10:35:09,502 [mcmc]  - Acceptance rate: 0.451
 2023-07-02 10:35:09,502 [mcmc]  - Condition number = 4.45256
 2023-07-02 10:35:09,502 [mcmc]  - Eigenvalues = array([0.00484795, 0.02158577])
 2023-07-02 10:35:09,502 [mcmc]  - Convergence of means: R-1 = 0.021586 after 832 accepted steps
 2023-07-02 10:35:09,508 [mcmc]  - normalized std's of bounds = array([[0.14346561, 0.17114478],
       [0.17787582, 0.18262451]])
 2023-07-02 10:35:09,508 [mcmc]  - Convergence of bounds: R-1 = 0.182625 after 1040 accepted steps
 2023-07-02 10:35:09,508 [mcmc] The run has converged!
 2023-07-02 10:35:09,518 [mcmc] Dumped checkpoint and progress info, and current covmat.
 2023-07-02 10:35:09,519 [mcmc] Sampling complete after 1040 accepted steps.

CosmoSIS¶

In [51]:
%%file _tests/config_bao_fs.ini

[DEFAULT]
fatal_errors = T

[runtime]
sampler = emcee

[output]
filename = _tests/chains_bao_fs_cosmosis/chain.txt
format = text
verbosity = 0

[pipeline]
modules = consistency camb bao fs
values = _tests/values_bao_fs.ini
likelihoods = BAOLikelihood FSLikelihood  ; notice the name of the liklelihood: the same as the *.py file
quiet = T
debug = F
timing = F

[consistency]
file = ${COSMOSIS_STD_DIR}/utility/consistency/consistency_interface.py

[camb]
file = ${COSMOSIS_STD_DIR}/boltzmann/camb/camb_interface.py
mode = background
feedback = 0
; We need quite fine redshift spacing, because the supernovae
; go down to low z where things are pretty sensitive
nz = 901

[bao]
file = _tests/cosmosis/BAOLikelihood.py

[fs]
file = _tests/cosmosis/FSLikelihood.py

[emcee]
walkers = 10
samples = 800
nsteps = 20
Writing _tests/config_bao_fs.ini

In this case the likelihood has nuisance parameters, to be copied in the input *values.ini file.

In [52]:
!cat _tests/cosmosis/FSLikelihood_values.ini
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
[desi]
sigmapar = 0.0
sigmaper = 0.0
b1 = 0.0 1.5 4.0
In [53]:
%%file _tests/values_bao_fs.ini

[desi]
sigmapar = 0.0
sigmaper = 0.0
b1 = 0.0 1.5 4.0

[cosmological_parameters]
; This is the only parameter being varied.
omega_m = 0.1 0.3 0.9
ombh2 = 0.02237
h0 = 0.6736
A_s = 2.083e-09
n_s = 0.9649
tau = 0.0544

mnu = 0.06
nnu = 3.046
num_massive_neutrinos = 1
omega_k = 0.0
w = -1.0
wa = 0.0
Writing _tests/values_bao_fs.ini

Let's sample!

In [54]:
!cosmosis _tests/config_bao_fs.ini
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)

Parameter Priors
----------------
cosmological_parameters--omega_m                ~ U(0.1, 0.9)
cosmological_parameters--ombh2                  ~ delta(0.02237)
cosmological_parameters--h0                     ~ delta(0.6736)
cosmological_parameters--a_s                    ~ delta(2.083e-09)
cosmological_parameters--n_s                    ~ delta(0.9649)
cosmological_parameters--tau                    ~ delta(0.0544)
cosmological_parameters--mnu                    ~ delta(0.06)
cosmological_parameters--nnu                    ~ delta(3.046)
cosmological_parameters--num_massive_neutrinos  ~ delta(1)
cosmological_parameters--omega_k                ~ delta(0.0)
cosmological_parameters--w                      ~ delta(-1.0)
cosmological_parameters--wa                     ~ delta(0.0)
desi--sigmapar                                  ~ delta(0.0)
desi--sigmaper                                  ~ delta(0.0)
desi--b1                                        ~ U(0.0, 4.0)

****************************
* Running sampler 1/1: emcee
* Saving output -> _tests/chains_bao_fs_cosmosis/chain.txt
****************************
Begun sampling
Done 20 iterations of emcee. Acceptance fraction 0.485
Done 40 iterations of emcee. Acceptance fraction 0.467
Done 60 iterations of emcee. Acceptance fraction 0.455
Done 80 iterations of emcee. Acceptance fraction 0.444
Done 100 iterations of emcee. Acceptance fraction 0.442
Done 120 iterations of emcee. Acceptance fraction 0.465
Done 140 iterations of emcee. Acceptance fraction 0.494
Done 160 iterations of emcee. Acceptance fraction 0.519
Done 180 iterations of emcee. Acceptance fraction 0.537
Done 200 iterations of emcee. Acceptance fraction 0.557
Done 220 iterations of emcee. Acceptance fraction 0.572
Done 240 iterations of emcee. Acceptance fraction 0.584
Done 260 iterations of emcee. Acceptance fraction 0.592
Done 280 iterations of emcee. Acceptance fraction 0.599
Done 300 iterations of emcee. Acceptance fraction 0.610
Done 320 iterations of emcee. Acceptance fraction 0.617
Done 340 iterations of emcee. Acceptance fraction 0.623
Done 360 iterations of emcee. Acceptance fraction 0.625
Done 380 iterations of emcee. Acceptance fraction 0.632
Done 400 iterations of emcee. Acceptance fraction 0.634
Done 420 iterations of emcee. Acceptance fraction 0.642
Done 440 iterations of emcee. Acceptance fraction 0.650
Done 460 iterations of emcee. Acceptance fraction 0.652
Done 480 iterations of emcee. Acceptance fraction 0.656
Done 500 iterations of emcee. Acceptance fraction 0.655

MontePython¶

In [56]:
!ls -la _tests/montepython/FSLikelihood
!cp -r _tests/montepython/FSLikelihood _tests/montepython_public/montepython/likelihoods/
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
total 20
drwxr-xr-x 2 adematti idphp 4096 juil.  2 10:32 .
drwxr-xr-x 4 adematti idphp 4096 juil.  2 10:32 ..
-rw-r--r-- 1 adematti idphp   33 juil.  2 10:33 FSLikelihood.data
-rw-r--r-- 1 adematti idphp  268 juil.  2 10:33 FSLikelihood.param
-rw-r--r-- 1 adematti idphp  477 juil.  2 10:33 __init__.py
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)

In this case the likelihood has nuisance parameters, to be copied in the input *.param file.

In [57]:
!cat _tests/montepython/FSLikelihood/FSLikelihood.param
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
# To be copy-pasted in the MontePython *.param file
data.parameters['sigmapar'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance']
data.parameters['sigmaper'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance']
data.parameters['b1'] = [1.5, 0.0, 4.0, 0.28867513459481287, 1.0, 'nuisance']
In [58]:
%%file _tests/conf_bao_fs.param

data.experiments = ['BAOLikelihood', 'FSLikelihood']

# Cosmological parameters list
data.parameters['Omega_m'] = [0.3, 0.1, 0.9, 0.1, 1., 'cosmo']
# Fixed parameters
data.parameters['omega_b'] = [0.02237, 0.001, 0.1, 0., 1., 'cosmo']
data.parameters['H0'] = [67.36, 0.1, 0.9, 0., 1., 'cosmo']
data.parameters['A_s'] = [2.083e-09, 1e-09, 3e-09, 0., 1., 'cosmo']
data.parameters['n_s'] = [0.9649, 0.9, 1.0, 0., 1., 'cosmo']
data.parameters['tau_reio'] = [0.0544, 0.02, 0.1, 0., 1., 'cosmo']

# Nuisance parameters list
data.parameters['sigmapar'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance']
data.parameters['sigmaper'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance']
data.parameters['b1'] = [1.5, 0.0, 4.0, 0.28867513459481287, 1.0, 'nuisance']

# Cosmo arguments
data.cosmo_arguments['k_pivot'] = 0.05
# The base model features two massless
# and one massive neutrino with m=0.06eV.
# The settings below ensures that Neff=3.046
# and m/omega = 93.14 eV
data.cosmo_arguments['N_ur'] = 2.0328
data.cosmo_arguments['N_ncdm'] = 1
data.cosmo_arguments['m_ncdm'] = 0.06
data.cosmo_arguments['T_ncdm'] = 0.71611

#------ MCMC parameters ----
# Number of steps taken, by default (overwritten by the -N command)
data.N = 9000
# Number of accepted steps before writing to file the chain. Larger means less
# access to disc, but this is not so much time consuming.
data.write_step = 5
Writing _tests/conf_bao_fs.param

Let's sample!

In [59]:
!python _tests/montepython_public/montepython/MontePython.py run --conf _tests/montepython_public/default.conf -p _tests/conf_bao_fs.param -o _tests/chains_bao_fs_montepython
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
 /!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
     safely ignore this if not running with option -m NS
Running Monte Python v3.6.0

with CLASS v3.2.0

Testing likelihoods for:
 ->BAOLikelihood, FSLikelihood

WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Creating _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt


Deduced starting covariance matrix:

['Omega_m', 'b1']
[[0.01 0.  ]
 [0.   0.08]]
Update routine is enabled with value 50 (recommended: 50)
This number is rescaled by cycle length 2 (N_slow + f_fast * N_fast) to 100

#  -LogLkl	Omega_m         b1
 /!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
     safely ignore this if not running with option -m NS
1  8711.4	3.000000e-01	1.621846e+00
2  174.297	3.000000e-01	2.266003e-01
22  53.5086	3.000000e-01	6.624145e-01
14  0.128235	3.000000e-01	5.022887e-01
14  -0.877214	3.000000e-01	5.117996e-01
28  -1.51021	3.000000e-01	5.249515e-01
8  0.661607	3.000000e-01	4.984443e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 1 steps
Step  90  chain  0 : Failed to calculate covariance matrix
 /!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
     safely ignore this if not running with option -m NS
35  -1.4765	3.000000e-01	5.231471e-01
10  -1.78897	3.135776e-01	5.231471e-01
30  0.583581	3.213354e-01	5.231471e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 4 steps
Step  190  chain  0 : Failed to calculate covariance matrix
28  -2.14692	3.111806e-01	5.231471e-01
19  -2.2103	3.105647e-01	5.231471e-01
19  -2.58273	3.105647e-01	5.174114e-01
41  -1.65937	3.172893e-01	5.174114e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 4 steps
Step  290  chain  0 : Failed to calculate covariance matrix
21  -2.27128	3.172893e-01	5.113553e-01
81  -2.72205	3.135318e-01	5.113553e-01
13  -2.38692	3.135318e-01	4.889639e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 6 steps
 /!\ Convergence computed for a single file
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.099171 	for  Omega_m
           0.152791 	for  b1
--> Not computing covariance matrix
6  -1.08039	3.079173e-01	4.889639e-01
15  -2.57355	3.229237e-01	4.889639e-01
73  -2.41446	3.229237e-01	4.941567e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 9 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.762166 	for  Omega_m
           0.227418 	for  b1
--> Computing covariance matrix
After 20 accepted steps: update proposal with max(R-1) = 0.762166 and jumping factor = 2.400000

16  -0.198255	3.308563e-01	4.941567e-01
1  0.269173	3.331269e-01	4.906302e-01
1  0.122175	3.331269e-01	4.894809e-01
4  -2.06522	3.163232e-01	5.155794e-01
1  -1.82068	3.059657e-01	5.316662e-01
1  -2.41079	3.059657e-01	5.189505e-01
2  -2.83301	3.121173e-01	5.093961e-01
2  -2.72094	3.197148e-01	4.975962e-01
4  -2.63538	3.084015e-01	5.151673e-01
2  -2.81726	3.176557e-01	5.007942e-01
3  -2.86978	3.150349e-01	5.048647e-01
4  -2.78399	3.150349e-01	4.929856e-01
1  -2.48015	3.150349e-01	4.873329e-01
1  -1.73945	3.284564e-01	4.664873e-01
1  -1.75524	3.284564e-01	4.850044e-01
1  -2.67847	3.092750e-01	5.147959e-01
3  -1.78269	3.092750e-01	4.918417e-01
1  -2.02488	3.219731e-01	4.721197e-01
2  -2.6075	3.219731e-01	4.925893e-01
1  -2.28852	3.219731e-01	4.995245e-01
1  -1.9185	3.253604e-01	4.942636e-01
1  -2.36331	3.253604e-01	4.819940e-01
1  -1.76992	3.298628e-01	4.750011e-01
2  -1.72151	3.298628e-01	4.688852e-01
1  -1.54832	3.298628e-01	4.825050e-01
1  -2.84839	3.154596e-01	5.048752e-01
1  -2.68635	3.154596e-01	5.089021e-01
1  -2.69775	3.143231e-01	5.106672e-01
1  -2.02753	3.143231e-01	5.196380e-01
1  -1.97856	3.160946e-01	5.168868e-01
1  -2.88856	3.160946e-01	4.948279e-01
1  -2.82494	3.123324e-01	5.006710e-01
2  -2.76043	3.123324e-01	4.985110e-01
1  -2.78416	3.123324e-01	5.111336e-01
1  -2.8091	3.143523e-01	5.079964e-01
2  -2.65632	3.143523e-01	4.915310e-01
1  -2.22919	3.143523e-01	4.853497e-01
1  -2.20022	3.205898e-01	4.756621e-01
1  -2.33525	3.205898e-01	4.775312e-01
1  -2.04697	3.089504e-01	4.956089e-01
1  -1.36037	3.089504e-01	4.887274e-01
1  -1.58635	3.237990e-01	4.656653e-01
1  -2.4905	3.237990e-01	4.877160e-01
1  -1.19841	2.984948e-01	5.270172e-01
3  -1.21519	2.984948e-01	5.281876e-01
1  -1.10185	2.979733e-01	5.289976e-01
1  -0.810813	2.979733e-01	5.204834e-01
3  -2.30022	3.066080e-01	5.070724e-01
1  -2.49176	3.066080e-01	5.150718e-01
3  -2.61849	3.079409e-01	5.130016e-01
1  -2.26864	3.079409e-01	5.016692e-01
2  -2.66508	3.143217e-01	4.917589e-01
3  -1.56472	3.027503e-01	5.097310e-01
1  -1.14098	3.027503e-01	5.403921e-01
2  -1.74653	3.122373e-01	5.256574e-01
2  -1.71702	3.147584e-01	5.217417e-01
1  -1.59707	3.175411e-01	5.174198e-01
1  -2.79804	3.175411e-01	4.897053e-01
3  -2.60881	3.101335e-01	5.012104e-01
2  -2.57811	3.101335e-01	5.005145e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 39 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.031991 	for  Omega_m
           0.013889 	for  b1
--> Not computing covariance matrix
1  -1.93895	3.101335e-01	4.913420e-01
2  -2.21739	3.182281e-01	4.787699e-01
1  -2.03711	3.229024e-01	4.715100e-01
1  -2.49364	3.229024e-01	4.797388e-01
2  -2.72235	3.183170e-01	4.868606e-01
1  -2.69366	3.192768e-01	4.853700e-01
1  -2.7947	3.192768e-01	4.887888e-01
2  -2.29989	3.258307e-01	4.786096e-01
3  -1.53158	3.313979e-01	4.699629e-01
1  -0.771878	3.313979e-01	4.871602e-01
2  -0.103681	3.346447e-01	4.821175e-01
1  -2.42334	3.178278e-01	5.082366e-01
1  -2.71773	3.178278e-01	4.872532e-01
1  -2.72821	3.170955e-01	4.883906e-01
4  -1.69531	3.170955e-01	4.751416e-01
2  -2.69881	3.170955e-01	4.877407e-01
2  -2.78086	3.170955e-01	5.033364e-01
3  -1.24952	3.170955e-01	4.714638e-01
1  -0.978931	3.251948e-01	4.588844e-01
1  -1.98209	3.251948e-01	4.696616e-01
1  -0.995291	3.328695e-01	4.577417e-01
2  -1.26469	3.328695e-01	4.657235e-01
2  -1.26413	3.328695e-01	4.702373e-01
1  -1.23509	3.328695e-01	4.639778e-01
1  -2.6565	3.125135e-01	4.955938e-01
1  -2.75276	3.125135e-01	5.118628e-01
1  -2.74716	3.122632e-01	5.122514e-01
1  -2.85149	3.122632e-01	5.022127e-01
2  -2.49689	3.071813e-01	5.101057e-01
1  -2.86136	3.125325e-01	5.017945e-01
1  -2.75235	3.125325e-01	5.118542e-01
2  -2.72927	3.116448e-01	5.132329e-01
2  -2.76086	3.130136e-01	5.111069e-01
2  -1.90042	3.266461e-01	4.899336e-01
1  -2.71706	3.172449e-01	5.045351e-01
1  -2.66118	3.172449e-01	5.056897e-01
2  -2.43868	3.210611e-01	4.997625e-01
1  -2.71872	3.144238e-01	5.100712e-01
1  -2.7178	3.144238e-01	5.100906e-01
2  -2.57159	3.191130e-01	5.028076e-01
1  -1.93404	3.258488e-01	4.923459e-01
1  -2.2811	3.258488e-01	4.839058e-01
1  -2.02716	3.278339e-01	4.808227e-01
6  -1.95696	3.278339e-01	4.707396e-01
2  -0.857491	3.278339e-01	4.978995e-01
3  -0.626278	3.278339e-01	4.997837e-01
1  -0.382551	3.292355e-01	4.976067e-01
1  -1.46853	3.292355e-01	4.865920e-01
1  -2.54497	3.199658e-01	5.009893e-01
1  -0.975104	3.199658e-01	5.169600e-01
1  -1.33703	3.131144e-01	5.276011e-01
1  -2.89748	3.131144e-01	5.024811e-01
1  -2.6455	3.084686e-01	5.096967e-01
3  -2.18978	3.084686e-01	5.254041e-01
1  -1.2591	3.003120e-01	5.380726e-01
3  -1.22135	3.003120e-01	5.386877e-01
3  -0.363049	2.960085e-01	5.453716e-01
1  -0.392384	2.960085e-01	5.247159e-01
1  -2.14137	3.049283e-01	5.108621e-01
2  -2.06162	3.049283e-01	5.091126e-01
1  -2.29421	3.049283e-01	5.169806e-01
1  -2.53105	3.070251e-01	5.137240e-01
1  -2.50203	3.070251e-01	5.182989e-01
1  -2.52404	3.072663e-01	5.179242e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 69 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.017263 	for  Omega_m
           0.002206 	for  b1
--> Not computing covariance matrix
1  -1.86645	3.072663e-01	5.303369e-01
2  -1.07973	3.004919e-01	5.408585e-01
2  -1.90993	3.180441e-01	5.135974e-01
1  -2.01418	3.158476e-01	5.170088e-01
5  -0.981019	3.158476e-01	5.252932e-01
1  -1.07248	3.108087e-01	5.331194e-01
1  -2.10508	3.108087e-01	5.240938e-01
1  -2.03892	3.090706e-01	5.267934e-01
1  -1.9274	3.090706e-01	5.280389e-01
5  -1.85933	3.179980e-01	5.141733e-01
1  -2.67289	3.179980e-01	5.036735e-01
2  -2.72954	3.163691e-01	5.062035e-01
1  -2.74994	3.131108e-01	5.112641e-01
3  -2.0632	3.131108e-01	5.212781e-01
1  -1.67403	3.050365e-01	5.338186e-01
1  -2.08268	3.050365e-01	5.090707e-01
3  -2.32723	3.070296e-01	5.059752e-01
2  -2.42606	3.070296e-01	5.211769e-01
1  -2.52951	3.070296e-01	5.162228e-01
2  -2.83374	3.115933e-01	5.091346e-01
1  -2.86151	3.171122e-01	5.005630e-01
1  -2.82608	3.171122e-01	5.019377e-01
2  -2.86318	3.147033e-01	5.056791e-01
1  -2.48738	3.226947e-01	4.932672e-01
1  -2.39295	3.226947e-01	4.954252e-01
1  -2.29383	3.236884e-01	4.938820e-01
4  -0.430854	3.236884e-01	4.563858e-01
1  -2.10081	3.236884e-01	4.719223e-01
3  -2.21814	3.120697e-01	4.899679e-01
1  -2.85059	3.120697e-01	5.029409e-01
1  -2.83271	3.192531e-01	4.917839e-01
1  -2.63517	3.192531e-01	4.840068e-01
2  -2.62688	3.132142e-01	4.933861e-01
1  -2.6188	3.130018e-01	4.937161e-01
1  -2.79495	3.130018e-01	4.977332e-01
1  -2.74177	3.200812e-01	4.867378e-01
2  -2.52726	3.200812e-01	4.811585e-01
2  -1.77511	3.200812e-01	5.103317e-01
1  -2.79047	3.200812e-01	4.900316e-01
2  -2.66132	3.221159e-01	4.868712e-01
1  -2.89116	3.173755e-01	4.942338e-01
2  -2.67999	3.173755e-01	5.050171e-01
1  -2.66203	3.173755e-01	5.053750e-01
1  -2.49199	3.079451e-01	5.200219e-01
1  -2.60424	3.079451e-01	5.154988e-01
1  -2.6837	3.089870e-01	5.138805e-01
1  -2.32634	3.089870e-01	4.993570e-01
1  -1.19651	3.009962e-01	5.117680e-01
4  -1.71019	3.009962e-01	5.252293e-01
2  -1.27029	3.009962e-01	5.128181e-01
2  -1.13115	3.009962e-01	5.108982e-01
1  -0.702957	3.009962e-01	5.061118e-01
1  -1.21259	3.037827e-01	5.017840e-01
2  -1.49685	3.037827e-01	5.049368e-01
1  -2.12397	3.037827e-01	5.175600e-01
2  -2.9093	3.134981e-01	5.024705e-01
2  -2.62503	3.081442e-01	5.107859e-01
3  -2.56437	3.231990e-01	4.874035e-01
1  -2.54585	3.231990e-01	4.887154e-01
1  -2.36806	3.249687e-01	4.859668e-01
1  -2.04979	3.249687e-01	4.707623e-01
1  -2.2796	3.119799e-01	4.909358e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 101 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.023649 	for  Omega_m
           0.051105 	for  b1
--> Not computing covariance matrix
1  -2.85466	3.119799e-01	5.036656e-01
2  -2.66876	3.088596e-01	5.085120e-01
1  -2.91703	3.162909e-01	4.969700e-01
1  -2.84533	3.162909e-01	5.032474e-01
1  -2.72252	3.097757e-01	5.133666e-01
1  -2.64501	3.097757e-01	5.033794e-01
2  -2.7387	3.204179e-01	4.868504e-01
1  -2.83698	3.137743e-01	4.971689e-01
1  -2.88888	3.137743e-01	4.994410e-01
1  -2.87842	3.177412e-01	4.932798e-01
2  -2.8874	3.177412e-01	4.943487e-01
1  -2.6307	3.177412e-01	5.051232e-01
1  -1.84285	3.023012e-01	5.291039e-01
3  -1.70818	3.023012e-01	5.142449e-01
1  -2.61967	3.097976e-01	5.026019e-01
1  -2.70458	3.097976e-01	5.142262e-01
2  -2.7397	3.185632e-01	5.006120e-01
2  -2.51136	3.220042e-01	4.952676e-01
3  -2.82755	3.132213e-01	5.089088e-01
3  -2.89773	3.132213e-01	5.019970e-01
2  -2.75492	3.207495e-01	4.903046e-01
1  -2.69777	3.091865e-01	5.082636e-01
2  -2.33822	3.091865e-01	4.989561e-01
2  -2.48787	3.091865e-01	5.200965e-01
1  -2.30184	3.091865e-01	4.983910e-01
1  -2.5989	3.146958e-01	4.898342e-01
2  -2.83472	3.146958e-01	4.950858e-01
1  -1.87796	3.146958e-01	5.204218e-01
1  -1.62106	3.196067e-01	5.127945e-01
3  -2.56062	3.196067e-01	5.016906e-01
1  -2.6792	3.172100e-01	5.054130e-01
1  -2.69581	3.172100e-01	4.875231e-01
1  -2.6646	3.188047e-01	4.850463e-01
1  -2.8371	3.188047e-01	4.909606e-01
1  -2.81221	3.194254e-01	4.899966e-01
3  -2.81084	3.194254e-01	4.947363e-01
1  -2.88183	3.176697e-01	4.974631e-01
2  -2.49238	3.176697e-01	5.075916e-01
1  -2.89188	3.176697e-01	4.951344e-01
1  -2.90309	3.134320e-01	5.017162e-01
2  -2.59806	3.134320e-01	4.923899e-01
2  -2.63323	3.134320e-01	4.930226e-01
1  -2.85435	3.134320e-01	4.986806e-01
2  -2.86604	3.139278e-01	4.979106e-01
1  -2.84328	3.130479e-01	4.992772e-01
4  -2.59704	3.130479e-01	5.144532e-01
3  -2.85514	3.130479e-01	5.079827e-01
4  -2.78311	3.108239e-01	5.114369e-01
1  -2.80798	3.114101e-01	5.105264e-01
1  -1.32268	3.114101e-01	5.303859e-01
2  -0.869705	3.208461e-01	5.157304e-01
2  -1.21355	3.163769e-01	5.226718e-01
1  -1.32519	3.122280e-01	5.291157e-01
1  -1.03271	3.122280e-01	5.312298e-01
1  -1.03316	3.114334e-01	5.324639e-01
1  -1.73721	3.114334e-01	5.269284e-01
1  -1.7426	3.119664e-01	5.261006e-01
2  -2.10416	3.119664e-01	5.225597e-01
1  -2.78334	3.119664e-01	5.114115e-01
1  -2.67135	3.194517e-01	4.997856e-01
1  -2.80128	3.194517e-01	4.892728e-01
2  -2.86782	3.140881e-01	4.976034e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 131 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000178 	for  Omega_m
           0.004217 	for  b1
--> Not computing covariance matrix
10  -2.86893	3.141483e-01	4.975098e-01
4  -2.84837	3.181254e-01	4.913328e-01
1  -2.55579	3.232905e-01	4.833106e-01
1  -2.16387	3.232905e-01	4.974067e-01
1  -1.82559	3.261094e-01	4.930286e-01
1  -2.27369	3.261094e-01	4.817043e-01
2  -1.71716	3.301371e-01	4.754487e-01
1  -2.85779	3.186896e-01	4.932282e-01
2  -2.83864	3.186896e-01	4.963415e-01
1  -2.27778	3.186896e-01	4.788936e-01
3  -1.28525	3.306641e-01	4.602954e-01
2  -0.813053	3.306641e-01	4.542723e-01
2  -1.52351	3.306641e-01	4.650645e-01
2  -1.40069	3.306641e-01	4.623110e-01
1  -1.61213	3.306641e-01	4.757707e-01
1  -1.44749	3.316356e-01	4.742618e-01
1  -1.47326	3.316356e-01	4.728745e-01
2  -1.21739	3.330660e-01	4.706529e-01
2  1.66636	3.451358e-01	4.519067e-01
3  5.76347	3.573801e-01	4.328895e-01
2  5.73255	3.573801e-01	4.154388e-01
1  5.95807	3.573801e-01	4.114964e-01
1  5.66174	3.565255e-01	4.128236e-01
1  5.29386	3.565255e-01	4.303529e-01
1  -1.79693	3.296793e-01	4.720490e-01
1  -1.66812	3.296793e-01	4.666365e-01
1  -2.15618	3.256221e-01	4.729380e-01
1  -2.33469	3.256221e-01	4.806718e-01
5  -2.79894	3.197899e-01	4.897301e-01
1  -2.79491	3.197899e-01	4.939291e-01
1  -2.81238	3.194548e-01	4.944496e-01
1  -2.82383	3.194548e-01	4.930118e-01
2  -2.87922	3.124179e-01	5.039411e-01
1  -2.87676	3.123459e-01	5.040530e-01
1  -1.78844	3.123459e-01	4.848122e-01
1  -1.93927	3.176194e-01	4.766216e-01
1  -2.82947	3.176194e-01	5.004533e-01
1  -2.84341	3.122046e-01	5.088632e-01
1  -2.87414	3.122046e-01	5.060882e-01
1  -2.28795	3.048539e-01	5.175050e-01
4  -2.06911	3.048539e-01	5.278758e-01
2  -2.06683	3.048539e-01	5.279218e-01
3  -2.28873	3.048539e-01	5.199198e-01
1  -2.88002	3.135913e-01	5.063493e-01
3  -1.91103	3.135913e-01	5.220047e-01
1  -1.91519	3.129551e-01	5.229930e-01
3  -2.28925	3.129551e-01	5.189907e-01
2  -2.28968	3.131216e-01	5.187320e-01
1  -1.64598	3.238124e-01	5.021275e-01
4  -1.46663	3.238124e-01	5.038496e-01
1  -1.47602	3.238124e-01	5.037634e-01
1  -2.14733	3.129711e-01	5.206016e-01
1  -1.84005	3.129711e-01	5.236710e-01
2  -1.47653	3.205034e-01	5.119722e-01
1  -1.66627	3.073423e-01	5.324133e-01
1  -1.6127	3.073423e-01	5.329419e-01
1  -1.6988	3.088862e-01	5.305441e-01
2  -2.62999	3.088862e-01	5.163483e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 161 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001871 	for  Omega_m
           0.001055 	for  b1
--> Not computing covariance matrix
1  -2.62148	3.088862e-01	5.062140e-01
1  -1.66088	3.014932e-01	5.176963e-01
1  -1.75797	3.014932e-01	5.210383e-01
4  -1.53744	3.002898e-01	5.229074e-01
1  -2.914	3.137615e-01	5.019839e-01
2  -2.83147	3.137615e-01	4.970114e-01
1  -1.54889	3.137615e-01	4.798137e-01
2  -1.3472	3.106547e-01	4.846390e-01
1  -1.15558	3.086621e-01	4.877338e-01
1  -2.17549	3.086621e-01	4.980739e-01
4  -1.64121	3.043409e-01	5.047854e-01
1  -1.59253	3.040247e-01	5.052765e-01
1  -1.7159	3.040247e-01	5.334395e-01
1  -1.21565	3.004782e-01	5.389477e-01
1  -1.61308	3.004782e-01	5.280555e-01
2  -0.798015	2.965807e-01	5.341089e-01
1  -2.82436	3.122677e-01	5.097447e-01
2  -1.37374	3.122677e-01	5.286834e-01
1  -0.836582	3.122677e-01	5.324885e-01
2  -0.312465	3.025335e-01	5.476071e-01
1  -0.641672	3.060094e-01	5.422085e-01
1  -2.19203	3.060094e-01	5.260396e-01
1  -2.29153	3.071183e-01	5.243174e-01
4  -2.43295	3.071183e-01	5.210657e-01
1  -1.9383	3.071183e-01	4.995075e-01
3  -2.47851	3.154226e-01	4.866097e-01
2  -2.72705	3.154226e-01	4.909456e-01
1  -2.59346	3.154226e-01	4.884073e-01
1  -2.31518	3.095735e-01	4.974919e-01
4  -2.68129	3.095735e-01	5.053958e-01
1  -2.67162	3.095735e-01	5.050316e-01
1  -2.67138	3.218518e-01	4.859615e-01
1  -2.25797	3.218518e-01	5.003335e-01
2  -2.40123	3.200879e-01	5.030731e-01
2  -2.0354	3.240236e-01	4.969604e-01
2  -1.97838	3.245128e-01	4.962007e-01
1  -2.54021	3.101075e-01	5.185743e-01
3  -2.76899	3.101075e-01	5.075524e-01
2  -2.91535	3.138644e-01	5.017173e-01
1  -2.53909	3.072387e-01	5.120080e-01
1  -2.36472	3.072387e-01	5.228386e-01
1  -2.6353	3.144377e-01	5.116576e-01
1  -1.95333	3.144377e-01	5.201663e-01
1  -1.82696	3.176960e-01	5.151055e-01
1  0.605125	3.176960e-01	5.307920e-01
1  0.505574	3.163959e-01	5.328113e-01
1  0.946785	3.163959e-01	5.349582e-01
1  0.739324	3.119077e-01	5.419290e-01
5  -0.69492	3.119077e-01	5.339794e-01
2  -0.687161	3.126802e-01	5.327796e-01
1  -0.623353	3.080712e-01	5.399380e-01
1  0.0876989	3.080712e-01	5.442937e-01
1  0.039644	3.103778e-01	5.407113e-01
1  -2.75623	3.103778e-01	5.123985e-01
2  -2.81718	3.118202e-01	5.101583e-01
1  -1.51373	2.999336e-01	5.286200e-01
1  -1.50446	2.999336e-01	5.297837e-01
1  -2.82829	3.149066e-01	5.065284e-01
2  -2.84009	3.149066e-01	5.061559e-01
1  -2.24929	3.149066e-01	4.845432e-01
2  -2.23204	3.198104e-01	4.769269e-01
1  -2.22991	3.142306e-01	4.855932e-01
1  -2.72761	3.142306e-01	4.932267e-01
1  -2.71731	3.185422e-01	4.865301e-01
1  -2.79971	3.185422e-01	4.987775e-01
1  -2.80414	3.110327e-01	5.104409e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 194 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000222 	for  Omega_m
           0.001046 	for  b1
--> Not computing covariance matrix
4  -2.57779	3.110327e-01	4.978800e-01
1  -2.79949	3.110327e-01	5.043690e-01
1  -2.8278	3.116050e-01	5.034803e-01
3  -2.44245	3.116050e-01	4.940838e-01
1  -2.45648	3.213206e-01	4.789939e-01
2  -2.67198	3.213206e-01	4.847147e-01
2  -2.50699	3.213206e-01	4.800009e-01
1  -0.938533	3.213206e-01	5.141761e-01
1  -1.17653	3.187174e-01	5.182193e-01
1  -2.73314	3.187174e-01	4.868063e-01
1  -2.27061	3.255922e-01	4.761287e-01
2  -2.26012	3.255922e-01	4.864834e-01
2  0.164055	3.255922e-01	5.110017e-01
1  -1.93081	3.255922e-01	4.932959e-01
1  -2.63735	3.170663e-01	5.065379e-01
1  -2.50378	3.170663e-01	4.843047e-01
2  -2.19131	3.241848e-01	4.732486e-01
1  -2.48867	3.150282e-01	4.874700e-01
1  -2.87473	3.150282e-01	4.959021e-01
1  -2.16786	3.049137e-01	5.116114e-01
1  -2.22588	3.049137e-01	5.133915e-01
1  -2.90086	3.167204e-01	4.950539e-01
2  -2.77041	3.167204e-01	4.899173e-01
1  -1.96813	3.167204e-01	4.783351e-01
3  -1.82596	3.225131e-01	4.693383e-01
3  -1.92415	3.225131e-01	4.704409e-01
6  -2.06529	3.186802e-01	4.763940e-01
1  -1.91913	3.120951e-01	4.866216e-01
1  -2.78049	3.120951e-01	5.114233e-01
1  -2.76926	3.170775e-01	5.036848e-01
1  -1.97039	3.170775e-01	5.150233e-01
1  -1.84937	3.190832e-01	5.119081e-01
3  -2.78935	3.190832e-01	4.973433e-01
1  -2.64653	3.213793e-01	4.937771e-01
5  -2.39786	3.213793e-01	4.779011e-01
2  -2.27934	3.232629e-01	4.749756e-01
1  -2.17458	3.245740e-01	4.729392e-01
1  -1.27137	3.245740e-01	5.035462e-01
1  -1.37688	3.237439e-01	5.048355e-01
1  -1.40192	3.237439e-01	5.046147e-01
2  -2.02834	3.158159e-01	5.169282e-01
1  -1.58273	3.221569e-01	5.070797e-01
2  -2.62301	3.221569e-01	4.910004e-01
1  -2.5934	3.221569e-01	4.824290e-01
2  -2.80155	3.149158e-01	4.936755e-01
5  -2.77899	3.137557e-01	4.954773e-01
1  -2.47388	3.137557e-01	5.153241e-01
2  -2.31489	3.084702e-01	5.235332e-01
1  -2.47394	3.137285e-01	5.153664e-01
1  -2.91418	3.137285e-01	5.029795e-01
2  -1.91425	3.023237e-01	5.206928e-01
4  -1.17529	2.984200e-01	5.267558e-01
3  -1.25972	2.988147e-01	5.261428e-01
1  -1.26643	2.988147e-01	5.329482e-01
3  -1.15743	2.982842e-01	5.337720e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 221 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000097 	for  Omega_m
           0.000604 	for  b1
--> Not computing covariance matrix
3  -1.15033	2.982842e-01	5.272087e-01
3  -1.4872	2.999133e-01	5.246786e-01
1  -0.397815	2.999133e-01	5.070446e-01
1  -2.15914	3.141577e-01	4.849209e-01
1  -2.10431	3.141577e-01	5.191355e-01
1  -1.89262	3.070390e-01	5.301918e-01
4  -1.7249	3.070390e-01	5.320661e-01
2  -2.39851	3.070390e-01	5.076186e-01
1  -2.43466	3.070390e-01	5.086408e-01
4  -2.51634	3.078492e-01	5.073826e-01
1  -2.77101	3.112971e-01	5.020274e-01
2  -2.83732	3.112971e-01	5.062741e-01
1  -2.36159	3.112971e-01	5.203156e-01
1  -2.34662	3.107811e-01	5.211171e-01
1  -1.82889	3.107811e-01	4.886678e-01
1  -1.68225	3.257560e-01	4.654095e-01
1  -1.98643	3.257560e-01	4.697023e-01
1  -2.37792	3.138498e-01	4.881944e-01
2  -2.787	3.138498e-01	5.093449e-01
2  -2.46413	3.138498e-01	4.893920e-01
1  -2.22548	3.138498e-01	4.862884e-01
1  -2.27819	3.180293e-01	4.797972e-01
1  -2.80536	3.180293e-01	5.001445e-01
1  -2.7692	3.188522e-01	4.988664e-01
2  -2.81833	3.188522e-01	4.968677e-01
3  -2.42899	3.188522e-01	5.057790e-01
5  -1.70777	3.261549e-01	4.944368e-01
1  -2.10564	3.261549e-01	4.879595e-01
1  -2.45058	3.230621e-01	4.927632e-01
1  -2.07659	3.230621e-01	4.719253e-01
1  -2.05234	3.234169e-01	4.713742e-01
3  -2.4727	3.234169e-01	4.905796e-01
4  -2.08705	3.267916e-01	4.853381e-01
1  -1.84671	3.285049e-01	4.826772e-01
3  -1.87745	3.285049e-01	4.698756e-01
1  -1.46268	3.313688e-01	4.654275e-01
1  -1.53213	3.313688e-01	4.692612e-01
1  -1.12886	3.336756e-01	4.656785e-01
1  -0.727217	3.336756e-01	4.785625e-01
2  -1.90147	3.268306e-01	4.891938e-01
1  -1.67412	3.283908e-01	4.867706e-01
1  -0.57477	3.283908e-01	4.985830e-01
1  -1.3554	3.030021e-01	5.380154e-01
3  -2.01052	3.030021e-01	5.253289e-01
1  -0.992796	2.974560e-01	5.339427e-01
1  -0.624575	2.974560e-01	5.440531e-01
3  -0.179542	2.954578e-01	5.471566e-01
1  -0.0114715	2.954578e-01	5.218215e-01
1  -2.1631	3.065702e-01	5.045624e-01
2  -2.48637	3.065702e-01	5.165610e-01
2  -1.37811	3.065702e-01	4.950660e-01
1  0.0884683	3.065702e-01	4.841155e-01
1  -0.0445494	3.075416e-01	4.826067e-01
2  -2.2343	3.075416e-01	5.024102e-01
2  -2.57442	3.075416e-01	5.156947e-01
1  -1.86359	3.075416e-01	4.973594e-01
2  -1.77292	3.067743e-01	4.985513e-01
1  -1.84375	3.267794e-01	4.674804e-01
2  -2.08821	3.267794e-01	4.853701e-01
3  -2.05682	3.267794e-01	4.717044e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 251 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000799 	for  Omega_m
           0.000527 	for  b1
--> Not computing covariance matrix
2  -2.4886	3.217884e-01	4.794562e-01
1  -1.14698	3.331151e-01	4.618641e-01
3  -1.22997	3.331151e-01	4.687292e-01
3  -2.06988	3.278015e-01	4.769819e-01
1  -2.05073	3.278015e-01	4.744737e-01
1  -2.83424	3.155323e-01	4.935296e-01
1  -1.06867	3.155323e-01	4.727869e-01
1  -0.677918	3.095966e-01	4.820058e-01
1  -0.686503	3.095966e-01	4.820652e-01
3  -1.03698	3.220104e-01	4.627847e-01
4  -1.08912	3.220104e-01	4.631895e-01
2  -2.43732	3.220104e-01	4.783218e-01
3  -2.5366	3.220104e-01	4.946153e-01
3  -2.64995	3.205238e-01	4.969243e-01
1  -2.28965	3.205238e-01	5.035327e-01
4  -2.55058	3.148917e-01	5.122801e-01
1  -2.52324	3.161723e-01	5.102911e-01
2  -2.91965	3.161723e-01	4.974359e-01
1  -2.48754	3.161723e-01	4.854612e-01
1  -1.72813	3.054599e-01	5.020991e-01
1  -1.74998	3.054599e-01	5.023704e-01
4  -2.42058	3.128313e-01	4.909215e-01
1  -1.76975	3.056043e-01	5.021462e-01
2  -2.06572	3.056043e-01	5.064574e-01
1  -2.3729	3.056043e-01	5.154933e-01
1  -2.92568	3.149881e-01	5.009189e-01
1  -2.73826	3.149881e-01	4.919788e-01
1  -2.4519	3.091445e-01	5.010549e-01
1  -0.466288	3.091445e-01	4.815978e-01
1  -0.530498	3.097559e-01	4.806482e-01
1  -1.04048	3.097559e-01	4.842628e-01
2  -1.1731	3.112685e-01	4.819135e-01
1  -0.269166	3.327263e-01	4.485864e-01
1  -1.10897	3.327263e-01	4.766219e-01
2  -2.34023	3.245459e-01	4.893273e-01
2  -2.63586	3.213428e-01	4.943021e-01
2  -2.88771	3.148376e-01	5.044057e-01
1  -2.66962	3.208776e-01	4.950247e-01
1  -2.58734	3.208776e-01	4.973367e-01
1  -2.80045	3.165589e-01	5.040443e-01
1  -2.66599	3.165589e-01	4.878450e-01
1  -2.63781	3.141662e-01	4.915612e-01
1  -2.32763	3.141662e-01	4.869125e-01
3  -1.90106	3.080048e-01	4.964820e-01
2  -1.69369	3.080048e-01	5.315210e-01
1  -1.89543	3.080048e-01	4.964171e-01
1  -2.00598	3.091034e-01	4.947108e-01
1  -2.70674	3.091034e-01	5.122398e-01
3  -2.87127	3.124251e-01	5.070807e-01
1  -2.83933	3.124251e-01	5.090300e-01
2  -2.65558	3.086961e-01	5.148218e-01
1  -2.12003	3.036202e-01	5.227054e-01
1  -2.11249	3.036202e-01	5.233975e-01
1  -2.63617	3.086013e-01	5.156610e-01
1  -2.61908	3.086013e-01	5.164375e-01
1  -2.71863	3.102212e-01	5.139217e-01
2  -2.57606	3.102212e-01	5.177748e-01
1  -2.43312	3.102212e-01	4.975375e-01
1  -2.45256	3.224363e-01	4.785656e-01
1  -2.11548	3.224363e-01	4.728888e-01
1  -2.10645	3.116033e-01	4.897140e-01
1  -1.58395	3.116033e-01	4.845488e-01
2  -1.78661	3.186655e-01	4.735802e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 284 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002006 	for  Omega_m
           0.000231 	for  b1
--> Not computing covariance matrix
4  -1.26331	3.081193e-01	4.899600e-01
5  -0.83538	3.049325e-01	4.949095e-01
3  -2.01993	3.049325e-01	5.082965e-01
4  -2.11183	3.056192e-01	5.072300e-01
6  -2.03876	3.050695e-01	5.080837e-01
1  -2.23528	3.066250e-01	5.056679e-01
1  -2.34371	3.066250e-01	5.080266e-01
2  -2.22101	3.056004e-01	5.096180e-01
1  -2.3884	3.070295e-01	5.073984e-01
1  -2.11808	3.070295e-01	5.022633e-01
1  -0.843718	2.993362e-01	5.142122e-01
1  -0.895551	2.993362e-01	5.149135e-01
2  -2.21158	3.074672e-01	5.022847e-01
2  -2.67315	3.176087e-01	4.865334e-01
1  -2.37011	3.238036e-01	4.769119e-01
1  -2.11097	3.238036e-01	4.965732e-01
1  -1.48533	3.284509e-01	4.893553e-01
1  -0.943811	3.284509e-01	4.952711e-01
1  -2.22789	3.155535e-01	5.153028e-01
1  -1.33512	3.155535e-01	5.233390e-01
3  -1.27873	3.076512e-01	5.356124e-01
1  0.404423	3.076512e-01	4.796519e-01
1  -0.314844	3.184062e-01	4.629478e-01
1  -1.88672	3.184062e-01	4.749239e-01
1  -1.85491	3.149789e-01	4.802469e-01
1  -1.03673	3.149789e-01	4.735507e-01
1  -1.02477	3.146716e-01	4.740281e-01
1  -2.91856	3.146716e-01	5.025115e-01
1  -2.88515	3.125957e-01	5.057357e-01
1  -2.80673	3.125957e-01	5.101944e-01
4  -2.50528	3.071819e-01	5.186028e-01
1  -1.54114	3.296273e-01	4.837418e-01
2  -1.29614	3.296273e-01	4.874792e-01
1  -1.25469	3.296273e-01	4.880129e-01
1  -2.62988	3.152075e-01	5.104090e-01
1  -2.91314	3.152075e-01	5.022143e-01
1  -2.09704	3.269879e-01	4.839176e-01
2  -1.72238	3.269879e-01	4.656423e-01
2  -2.15341	3.269879e-01	4.813749e-01
1  -1.78279	3.269879e-01	4.905196e-01
1  -2.57686	3.092339e-01	5.180941e-01
1  -2.70005	3.092339e-01	5.135281e-01
2  -2.83889	3.120869e-01	5.090970e-01
1  -2.81949	3.115247e-01	5.099702e-01
1  -1.84256	3.115247e-01	5.258286e-01
1  -1.37243	3.216817e-01	5.100532e-01
1  -0.856866	3.216817e-01	5.139121e-01
2  1.05489	3.330089e-01	4.963195e-01
3  -1.32709	3.154482e-01	5.235938e-01
1  -2.82771	3.154482e-01	4.934684e-01
1  -2.56823	3.227153e-01	4.821815e-01
1  -2.6074	3.227153e-01	4.880402e-01
1  -2.89827	3.130409e-01	5.030659e-01
1  -2.81906	3.130409e-01	5.093805e-01
2  -2.77947	3.174199e-01	5.025793e-01
1  -2.66689	3.092499e-01	5.152685e-01
1  -2.57836	3.092499e-01	5.034715e-01
1  -2.8173	3.178888e-01	4.900540e-01
1  -2.88477	3.178888e-01	4.944566e-01
1  -2.75484	3.207571e-01	4.900018e-01
1  -0.958001	3.207571e-01	4.638111e-01
1  -0.972692	3.201408e-01	4.647682e-01
2  -0.911495	3.201408e-01	4.643240e-01
2  -2.20875	3.201408e-01	4.762545e-01
1  -1.93541	3.201408e-01	4.730904e-01
1  -1.54711	3.262617e-01	4.635837e-01
1  -2.24172	3.262617e-01	4.771787e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 316 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001302 	for  Omega_m
           0.000446 	for  b1
--> Not computing covariance matrix
2  -1.35543	3.324146e-01	4.676223e-01
1  -2.3277	3.254760e-01	4.783989e-01
1  -1.29568	3.254760e-01	4.614522e-01
1  -1.35204	3.109632e-01	4.839928e-01
2  -2.67625	3.109632e-01	5.150489e-01
1  -2.18493	3.109632e-01	5.229780e-01
1  -2.11752	3.091792e-01	5.257488e-01
1  -1.90495	3.091792e-01	4.933719e-01
2  -1.64682	3.068163e-01	4.970419e-01
2  -1.46041	3.054189e-01	4.992121e-01
1  -1.95637	3.097459e-01	4.924918e-01
1  -1.7985	3.097459e-01	4.908322e-01
2  -1.81333	3.099140e-01	4.905710e-01
1  -0.979901	3.034286e-01	5.006439e-01
2  -1.06423	3.034286e-01	5.014468e-01
1  -0.791091	3.034286e-01	4.989471e-01
1  -1.73565	3.111088e-01	4.870186e-01
1  -2.53668	3.111088e-01	4.969038e-01
1  -2.6946	3.168012e-01	4.880625e-01
1  -2.62916	3.168012e-01	5.072627e-01
1  -2.31003	3.219456e-01	4.992728e-01
2  -2.67358	3.219456e-01	4.884311e-01
1  -2.38434	3.219456e-01	4.980381e-01
1  -1.86783	3.023597e-01	5.284580e-01
2  -1.93662	3.023597e-01	5.242363e-01
1  -1.92386	3.023597e-01	5.256799e-01
1  -2.68674	3.094579e-01	5.146553e-01
1  -2.31269	3.094579e-01	5.228872e-01
1  -2.10057	3.207357e-01	5.053712e-01
1  -2.06879	3.207357e-01	5.057379e-01
1  -1.34044	3.269345e-01	4.961102e-01
2  -1.80208	3.269345e-01	4.904235e-01
1  -1.89321	3.269345e-01	4.889249e-01
2  -2.33281	3.232672e-01	4.946207e-01
2  -2.61072	3.199007e-01	4.998494e-01
2  -2.47748	3.071455e-01	5.196601e-01
1  -2.72373	3.109503e-01	5.137507e-01
1  -2.31132	3.109503e-01	5.214056e-01
1  -1.67281	3.029911e-01	5.337675e-01
2  -1.96904	3.029911e-01	5.271613e-01
2  -2.03445	3.029911e-01	5.213680e-01
1  -1.89145	3.029911e-01	5.147597e-01
1  -2.00145	3.282978e-01	4.754546e-01
2  -1.98778	3.282978e-01	4.785995e-01
1  -0.358964	3.282978e-01	5.004816e-01
2  -1.122	3.231249e-01	5.085159e-01
1  -1.29398	3.215940e-01	5.108936e-01
4  -1.81482	3.215940e-01	5.062853e-01
1  -2.61613	3.215940e-01	4.939293e-01
1  -2.76603	3.102301e-01	5.115790e-01
1  -2.70993	3.102301e-01	5.142421e-01
1  -2.80107	3.128901e-01	5.101109e-01
1  -2.25076	3.128901e-01	5.195502e-01
1  -1.94619	3.061858e-01	5.299630e-01
1  -2.44702	3.061858e-01	5.157965e-01
3  -2.13024	3.036665e-01	5.197094e-01
1  -1.94026	3.036665e-01	5.294237e-01
2  -1.5215	3.008350e-01	5.338214e-01
2  -1.67676	3.018011e-01	5.323209e-01
2  -1.77827	3.024807e-01	5.312654e-01
2  -1.07251	2.984021e-01	5.376000e-01
1  -1.0376	2.982302e-01	5.378670e-01
2  -1.13616	2.982302e-01	5.271671e-01
1  -0.716038	2.982302e-01	5.176093e-01
2  -1.48937	3.019971e-01	5.117588e-01
1  -1.90682	3.045778e-01	5.077506e-01
1  -0.971584	3.045778e-01	4.970797e-01
2  -1.94418	3.190757e-01	4.745623e-01
3  -1.91973	3.147927e-01	4.812145e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 351 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002483 	for  Omega_m
           0.001701 	for  b1
--> Not computing covariance matrix
4  -2.65805	3.147927e-01	4.907074e-01
4  -2.89319	3.147927e-01	5.041978e-01
1  -2.91303	3.147927e-01	5.029005e-01
2  -2.91257	3.146108e-01	5.031830e-01
2  -2.6136	3.078875e-01	5.136252e-01
3  -2.46509	3.063464e-01	5.160188e-01
1  -2.31811	3.063464e-01	5.086200e-01
2  -1.66032	3.018491e-01	5.156050e-01
1  -2.83438	3.137695e-01	4.970910e-01
2  -2.90751	3.137695e-01	5.008971e-01
3  -2.82674	3.137695e-01	5.082959e-01
1  -1.47313	2.997679e-01	5.300424e-01
2  -1.41502	2.997679e-01	5.228912e-01
1  -1.16704	2.997679e-01	5.388782e-01
5  -1.97749	3.057153e-01	5.296410e-01
2  -2.06141	3.057153e-01	5.283305e-01
2  -1.06398	3.057153e-01	5.392913e-01
1  -2.31866	3.057153e-01	5.118322e-01
2  -2.87482	3.178240e-01	4.930256e-01
1  -2.81148	3.195742e-01	4.903074e-01
2  -2.75143	3.195742e-01	4.970528e-01
1  -2.6007	3.195742e-01	5.009982e-01
1  -2.17427	3.044520e-01	5.244852e-01
1  -2.21264	3.044520e-01	5.227471e-01
2  -1.94638	3.025348e-01	5.257248e-01
1  -2.41382	3.062118e-01	5.200139e-01
1  -2.4418	3.062118e-01	5.144846e-01
2  -1.30888	2.990649e-01	5.255847e-01
1  -0.812825	2.968469e-01	5.290296e-01
2  -0.853491	2.968469e-01	5.349951e-01
3  -0.035645	2.968469e-01	5.508167e-01
1  -1.55747	3.097103e-01	5.308380e-01
1  -2.13848	3.097103e-01	4.947151e-01
1  -2.078	3.090319e-01	4.957688e-01
1  -2.55333	3.090319e-01	5.036272e-01
3  -2.74898	3.197788e-01	4.869356e-01
1  -2.719	3.197788e-01	4.858766e-01
1  -2.52679	3.229782e-01	4.809075e-01
3  -2.48996	3.229782e-01	4.796816e-01
3  -2.74697	3.153004e-01	4.916063e-01
1  -2.72363	3.153004e-01	5.084423e-01
2  -2.71211	3.123279e-01	5.130589e-01
1  -2.70914	3.121961e-01	5.132637e-01
2  -2.3798	3.121961e-01	4.917746e-01
2  -2.82605	3.121961e-01	5.096986e-01
1  -2.67257	3.121961e-01	4.967240e-01
2  -2.75996	3.153303e-01	4.918562e-01
1  -2.71831	3.133476e-01	4.949357e-01
1  -1.98276	3.133476e-01	4.846413e-01
3  0.0996424	3.376484e-01	4.468985e-01
1  0.351411	3.376484e-01	4.435781e-01
1  -1.7273	3.163617e-01	4.766394e-01
1  -2.66707	3.163617e-01	4.881682e-01
1  -2.21517	3.253834e-01	4.741562e-01
1  -2.3592	3.253834e-01	4.823994e-01
2  -2.63777	3.224326e-01	4.869824e-01
1  -2.81269	3.111886e-01	5.044460e-01
2  -1.85462	3.111886e-01	5.261849e-01
2  -0.0648706	3.111886e-01	5.388756e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 381 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.005295 	for  Omega_m
           0.001232 	for  b1
--> Not computing covariance matrix
1  -0.201356	3.111886e-01	5.380988e-01
1  0.0448934	3.174417e-01	5.283867e-01
1  0.189027	3.174417e-01	5.291595e-01
2  1.02624	3.245778e-01	5.180761e-01
2  1.55533	3.276585e-01	5.132913e-01
3  0.207106	3.176709e-01	5.288036e-01
1  -0.576149	3.176709e-01	5.243533e-01
1  -0.797353	3.108780e-01	5.349036e-01
1  -2.81892	3.108780e-01	5.077121e-01
2  -2.87015	3.120615e-01	5.058740e-01
2  -2.40961	3.058885e-01	5.154616e-01
1  -2.75891	3.098269e-01	5.093447e-01
1  -2.74151	3.098269e-01	5.123169e-01
2  -2.7845	3.106158e-01	5.110917e-01
1  -2.84422	3.173538e-01	5.006265e-01
1  -2.72073	3.173538e-01	5.041975e-01
1  -2.62883	3.193047e-01	5.011675e-01
1  -2.66801	3.193047e-01	5.002955e-01
2  -2.4469	3.066815e-01	5.199011e-01
1  -2.39641	3.228610e-01	4.947720e-01
1  -2.49988	3.228610e-01	4.798973e-01
1  -1.08737	2.997502e-01	5.157919e-01
1  -1.48045	2.997502e-01	5.283600e-01
1  -1.13942	2.980839e-01	5.309479e-01
1  -1.04241	2.980839e-01	5.249928e-01
1  -2.5647	3.077090e-01	5.100436e-01
1  -2.53332	3.077090e-01	5.185006e-01
1  -2.61371	3.200538e-01	4.993273e-01
2  -2.67067	3.200538e-01	4.979327e-01
1  -1.84199	3.200538e-01	5.097604e-01
4  -2.0644	3.096844e-01	5.258656e-01
2  -1.91504	3.070956e-01	5.298864e-01
1  -1.97079	3.079022e-01	5.286336e-01
1  -1.83391	3.079022e-01	4.960065e-01
1  -2.00733	3.096632e-01	4.932714e-01
1  -0.742828	3.096632e-01	4.823071e-01
1  -0.385069	3.066684e-01	4.869586e-01
1  1.23658	3.066684e-01	4.773810e-01
1  0.936318	3.298434e-01	4.413868e-01
1  0.554099	3.298434e-01	4.437631e-01
2  0.0054257	3.149667e-01	4.668688e-01
1  -0.0631787	3.207797e-01	4.578404e-01
4  -2.49836	3.207797e-01	4.801096e-01
2  -2.68721	3.207797e-01	4.849021e-01
3  -2.57559	3.207797e-01	4.979274e-01
2  -1.7006	3.284675e-01	4.859870e-01
2  -1.81347	3.277127e-01	4.871595e-01
1  -2.55277	3.210852e-01	4.974528e-01
1  -2.73275	3.210852e-01	4.900506e-01
1  -2.91586	3.140381e-01	5.009958e-01
3  -2.91897	3.140381e-01	5.018668e-01
1  -2.72592	3.094033e-01	5.090653e-01
1  -2.68653	3.094033e-01	5.145994e-01
1  -2.83034	3.129847e-01	5.090371e-01
4  -2.47952	3.129847e-01	4.914466e-01
1  -2.86574	3.129847e-01	5.004987e-01
5  -2.11786	3.274330e-01	4.780584e-01
2  -2.08197	3.274330e-01	4.814295e-01
1  -2.10074	3.274330e-01	4.803153e-01
1  -2.56611	3.232322e-01	4.868398e-01
3  -1.74909	3.232322e-01	5.026620e-01
1  -2.25347	3.166405e-01	5.128999e-01
1  -2.73993	3.166405e-01	5.053876e-01
2  -2.75264	3.161324e-01	5.061767e-01
1  -2.68523	3.181375e-01	5.030625e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 414 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.006120 	for  Omega_m
           0.000829 	for  b1
--> Not computing covariance matrix
1  -2.60037	3.181375e-01	5.047360e-01
2  -2.67293	3.161278e-01	5.078574e-01
4  -0.707625	3.330412e-01	4.815885e-01
2  -0.929124	3.319117e-01	4.833427e-01
1  -2.47776	3.202074e-01	5.015212e-01
1  -2.74029	3.202074e-01	4.950332e-01
1  -2.28852	3.253021e-01	4.871204e-01
1  -2.25824	3.253021e-01	4.880506e-01
2  -2.7104	3.203110e-01	4.958026e-01
1  -2.87823	3.133397e-01	5.066299e-01
2  -1.94904	3.133397e-01	4.843158e-01
1  -2.24924	3.133397e-01	4.876058e-01
2  -2.31286	3.154758e-01	4.842883e-01
1  -2.07842	3.236299e-01	4.716236e-01
2  -2.33206	3.236299e-01	4.759825e-01
2  -2.38442	3.236299e-01	4.771858e-01
1  -2.41465	3.236299e-01	4.913586e-01
2  -1.52913	3.302190e-01	4.811247e-01
1  -2.71705	3.095431e-01	5.132375e-01
1  -2.73478	3.095431e-01	5.087412e-01
1  -2.88742	3.177990e-01	4.959186e-01
1  -2.58633	3.177990e-01	5.057858e-01
1  -2.4746	3.197998e-01	5.026782e-01
1  -2.76594	3.197998e-01	4.876669e-01
2  -2.73273	3.112290e-01	5.009786e-01
1  -2.68014	3.103553e-01	5.023357e-01
1  -2.76708	3.103553e-01	5.117618e-01
2  -2.82204	3.178104e-01	5.001828e-01
1  -2.6244	3.213328e-01	4.947121e-01
1  -2.69476	3.213328e-01	4.917767e-01
1  -2.79424	3.104133e-01	5.087362e-01
1  -2.57623	3.104133e-01	4.996237e-01
2  -2.70212	3.195375e-01	4.854524e-01
6  -2.13025	3.268479e-01	4.740984e-01
3  -2.43023	3.238846e-01	4.787007e-01
1  -2.47802	3.238846e-01	4.878001e-01
3  -2.91925	3.143158e-01	5.026619e-01
1  -2.75999	3.143158e-01	5.093230e-01
1  -2.66754	3.181906e-01	5.033049e-01
1  -2.77332	3.181906e-01	5.007092e-01
1  -2.85003	3.140982e-01	5.070653e-01
1  -2.56117	3.140982e-01	4.903783e-01
2  -2.46695	3.212884e-01	4.792108e-01
1  -2.51595	3.202621e-01	4.808049e-01
2  -1.82302	3.202621e-01	5.094538e-01
1  -2.35906	3.202621e-01	4.781975e-01
2  -2.18426	3.233989e-01	4.733256e-01
1  -2.31557	3.212484e-01	4.766657e-01
1  -2.67553	3.212484e-01	4.847898e-01
1  -2.66446	3.214289e-01	4.845095e-01
1  -2.54102	3.214289e-01	4.807222e-01
1  -1.48168	3.312221e-01	4.655118e-01
3  -1.24736	3.312221e-01	4.601588e-01
1  -1.73029	3.275692e-01	4.658323e-01
1  -2.0981	3.275692e-01	4.784724e-01
2  -2.34984	3.254852e-01	4.817092e-01
2  -1.98975	3.283698e-01	4.772291e-01
2  -2.77961	3.202914e-01	4.897760e-01
1  -2.66168	3.221139e-01	4.869454e-01
1  -2.57509	3.221139e-01	4.817528e-01
1  -1.36512	3.322323e-01	4.660373e-01
1  -1.35675	3.322323e-01	4.726396e-01
3  -1.29901	3.325526e-01	4.721421e-01
1  -0.284991	3.325526e-01	4.879224e-01
1  -0.514859	3.314035e-01	4.897072e-01
2  -0.283182	3.314035e-01	4.917490e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 446 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.007503 	for  Omega_m
           0.002133 	for  b1
--> Not computing covariance matrix
3  -1.52892	3.314035e-01	4.716435e-01
3  -2.50457	3.074719e-01	5.088127e-01
1  -2.23504	3.074719e-01	5.252557e-01
4  -2.40339	3.166898e-01	5.109389e-01
1  -2.4443	3.118308e-01	5.184857e-01
2  -2.326	3.118308e-01	4.918860e-01
1  -2.83763	3.118308e-01	5.090825e-01
1  -2.65492	3.085254e-01	5.142163e-01
1  -2.64167	3.085254e-01	5.090340e-01
2  -2.77419	3.103749e-01	5.061615e-01
2  -2.69367	3.091823e-01	5.080138e-01
1  -2.87275	3.182749e-01	4.938916e-01
1  -2.86642	3.182749e-01	4.927893e-01
1  -2.89898	3.140271e-01	4.993868e-01
1  -2.10202	3.140271e-01	5.193805e-01
1  -1.524	3.033515e-01	5.359612e-01
1  -1.59338	3.033515e-01	5.350509e-01
1  -2.06291	3.177662e-01	5.126628e-01
2  -2.50628	3.177662e-01	5.071635e-01
1  -2.7835	3.177662e-01	5.015700e-01
2  -2.82533	3.126805e-01	5.094688e-01
1  -2.65438	3.202574e-01	4.977008e-01
1  -1.53657	3.202574e-01	5.120372e-01
1  -0.413982	3.287017e-01	4.989219e-01
1  -0.0593511	3.287017e-01	5.014571e-01
2  -0.641012	3.251218e-01	5.070172e-01
1  -0.585645	3.255006e-01	5.064288e-01
1  -1.48959	3.255006e-01	4.633736e-01
1  -1.83486	3.170491e-01	4.765001e-01
1  -1.97286	3.170491e-01	4.778525e-01
3  -1.95375	3.155487e-01	4.801828e-01
2  -2.91329	3.155487e-01	4.971776e-01
1  -2.75974	3.155487e-01	5.071728e-01
2  -2.76849	3.137779e-01	5.099230e-01
3  -2.51731	3.078140e-01	5.191859e-01
1  -2.55661	3.078140e-01	5.090276e-01
1  -2.61481	3.227125e-01	4.858880e-01
1  -2.25135	3.227125e-01	4.978656e-01
1  -1.89437	3.258221e-01	4.930360e-01
1  -2.30016	3.258221e-01	4.828645e-01
2  -2.72887	3.211323e-01	4.901484e-01
1  -2.83343	3.113324e-01	5.053692e-01
2  -2.65585	3.113324e-01	5.152673e-01
1  -2.3205	3.113324e-01	4.929954e-01
3  -2.48868	3.172565e-01	4.837944e-01
2  -2.89991	3.172565e-01	4.972759e-01
1  -1.72638	3.172565e-01	4.751627e-01
2  -1.69568	3.153152e-01	4.781779e-01
1  -1.67745	3.147178e-01	4.791056e-01
1  -2.89831	3.147178e-01	5.040287e-01
5  -2.66014	3.085206e-01	5.136539e-01
1  -2.31133	3.085206e-01	5.235631e-01
2  -2.368	3.176372e-01	5.094038e-01
1  -2.45709	3.123013e-01	5.176912e-01
1  -0.893161	3.123013e-01	5.320602e-01
1  -0.478555	3.035648e-01	5.456292e-01
1  -2.04741	3.035648e-01	5.263134e-01
1  -2.63795	3.185073e-01	5.031054e-01
1  -2.76324	3.185073e-01	5.001019e-01
2  -2.69802	3.197456e-01	4.981787e-01
2  -2.60722	3.210995e-01	4.960759e-01
4  -2.52915	3.072504e-01	5.175855e-01
3  -2.71703	3.097826e-01	5.136527e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 476 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.007339 	for  Omega_m
           0.002052 	for  b1
--> Not computing covariance matrix
1  -2.66871	3.097826e-01	5.155280e-01
5  -1.84409	3.272986e-01	4.883231e-01
1  -1.23572	3.272986e-01	4.960427e-01
1  -2.2775	3.166856e-01	5.125263e-01
2  -2.50025	3.166856e-01	5.095928e-01
3  -2.76831	3.166856e-01	5.046105e-01
2  -2.12529	3.252466e-01	4.913140e-01
1  -1.67545	3.285114e-01	4.862432e-01
1  -0.968308	3.285114e-01	4.948554e-01
1  -2.21581	3.167268e-01	5.131588e-01
3  -2.76983	3.167268e-01	4.898938e-01
1  -1.90627	3.286469e-01	4.713802e-01
3  -1.60557	3.286469e-01	4.642257e-01
1  -2.12833	3.233124e-01	4.725109e-01
2  -2.40662	3.233124e-01	4.776091e-01
1  -2.5481	3.233124e-01	4.877316e-01
2  -2.29459	3.257505e-01	4.839449e-01
2  -2.82127	3.194202e-01	4.937767e-01
2  -2.92462	3.145980e-01	5.012665e-01
1  -2.90695	3.133376e-01	5.032240e-01
1  -2.89828	3.133376e-01	5.015641e-01
1  -2.07602	3.276776e-01	4.792920e-01
1  -1.33624	3.276776e-01	4.606309e-01
1  -0.712154	3.324057e-01	4.532874e-01
1  -1.2928	3.324057e-01	4.737648e-01
3  -2.92321	3.144347e-01	5.016765e-01
4  -2.72284	3.144347e-01	5.099660e-01
1  -2.7534	3.144347e-01	5.092874e-01
1  -2.68946	3.175053e-01	5.045183e-01
1  -2.74684	3.175053e-01	5.032184e-01
2  -2.41248	3.063608e-01	5.205274e-01
1  -1.74143	3.013247e-01	5.283493e-01
2  -1.72863	3.013247e-01	5.213166e-01
1  -1.47477	3.013247e-01	5.146213e-01
3  -0.754768	2.978962e-01	5.199463e-01
2  -0.995064	2.978962e-01	5.251330e-01
1  -0.998091	2.978962e-01	5.252257e-01
1  -2.16604	3.042928e-01	5.152908e-01
4  -2.18667	3.042928e-01	5.233134e-01
1  -0.202251	3.042928e-01	5.469272e-01
1  1.56614	2.936307e-01	5.634869e-01
1  1.18025	2.936307e-01	5.603829e-01
2  2.52117	2.889306e-01	5.676830e-01
1  2.25474	2.897748e-01	5.663717e-01
1  3.77532	2.897748e-01	5.772291e-01
1  2.03705	2.972219e-01	5.656627e-01
1  -0.12465	2.972219e-01	5.501083e-01
1  -1.60343	3.138120e-01	5.243414e-01
1  -2.9151	3.138120e-01	5.030261e-01
4  -2.89833	3.129776e-01	5.043221e-01
3  -2.8569	3.117136e-01	5.062853e-01
1  -2.7123	3.117136e-01	5.136241e-01
1  -2.73715	3.127777e-01	5.119715e-01
1  -2.61904	3.127777e-01	5.144284e-01
1  -2.55998	3.172258e-01	5.075199e-01
1  -2.80091	3.172258e-01	4.901277e-01
1  -2.79537	3.175680e-01	4.895962e-01
1  -2.7706	3.175680e-01	4.888788e-01
1  -2.37645	3.245991e-01	4.779584e-01
2  0.164159	3.245991e-01	4.514725e-01
3  1.68783	3.245991e-01	4.431656e-01
1  1.88714	3.122025e-01	4.624194e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 509 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.007776 	for  Omega_m
           0.002042 	for  b1
--> Not computing covariance matrix
1  -0.933801	3.122025e-01	4.781860e-01
1  -0.908277	3.118473e-01	4.787376e-01
1  -1.31432	3.118473e-01	4.817804e-01
2  -1.42453	3.137084e-01	4.788899e-01
1  -1.43765	3.217898e-01	4.663382e-01
1  -2.65252	3.217898e-01	4.844976e-01
1  -2.54902	3.086707e-01	5.048735e-01
3  -2.46271	3.086707e-01	5.207707e-01
1  -2.61148	3.155618e-01	5.100678e-01
3  -2.70877	3.155618e-01	4.903145e-01
3  -2.69371	3.180366e-01	4.864708e-01
1  -2.80873	3.180366e-01	4.896407e-01
1  -2.69947	3.111155e-01	5.003901e-01
4  -2.7425	3.111155e-01	5.016583e-01
1  -2.83025	3.111155e-01	5.070445e-01
2  -2.65096	3.083655e-01	5.113157e-01
2  -1.49299	2.999632e-01	5.243658e-01
1  -2.89463	3.128291e-01	5.043831e-01
1  -1.51485	3.128291e-01	5.266846e-01
3  -0.885037	3.023084e-01	5.430248e-01
1  -0.74016	3.023084e-01	5.443269e-01
1  -0.128133	2.983581e-01	5.504623e-01
1  -0.365372	2.983581e-01	5.481389e-01
1  -1.63115	3.111908e-01	5.282079e-01
3  -1.85392	3.111908e-01	5.261885e-01
2  -0.449324	3.284473e-01	4.993867e-01
2  -1.86655	3.123085e-01	5.244525e-01
1  -1.81719	3.098170e-01	5.283223e-01
2  -2.46789	3.098170e-01	5.201186e-01
2  -2.75307	3.098170e-01	5.112089e-01
1  -2.66268	3.098170e-01	5.037592e-01
1  -2.48329	3.077023e-01	5.070435e-01
1  -2.22226	3.077023e-01	5.016880e-01
2  -2.40208	3.096342e-01	4.986875e-01
3  -1.97009	3.276354e-01	4.707290e-01
1  -1.99581	3.276354e-01	4.714815e-01
1  -2.22347	3.256066e-01	4.746325e-01
1  -1.43851	3.256066e-01	4.627722e-01
2  -1.76891	3.195438e-01	4.721886e-01
1  -1.74704	3.148659e-01	4.794542e-01
1  -2.65117	3.148659e-01	4.904408e-01
2  -1.67625	3.036235e-01	5.079018e-01
1  -0.926131	2.995971e-01	5.141554e-01
1  -1.25053	2.995971e-01	5.195893e-01
2  -1.79932	3.025359e-01	5.150250e-01
2  -2.19746	3.267425e-01	4.774284e-01
1  -2.33528	3.255287e-01	4.793136e-01
2  -1.28361	3.255287e-01	4.612975e-01
2  -1.49046	3.255287e-01	4.633646e-01
1  -1.37686	3.255287e-01	4.622023e-01
2  -1.62335	3.217343e-01	4.680957e-01
1  -1.55557	3.230420e-01	4.660646e-01
4  -1.36512	3.230420e-01	4.643061e-01
1  -0.398333	3.230420e-01	4.569458e-01
1  -0.183931	3.263365e-01	4.518289e-01
1  -1.90306	3.263365e-01	4.910602e-01
2  -2.74143	3.137392e-01	5.106257e-01
1  -2.64183	3.100865e-01	5.162989e-01
1  -2.48604	3.100865e-01	4.988333e-01
1  -2.53337	3.107630e-01	4.977825e-01
1  -2.80734	3.107630e-01	5.065776e-01
1  -2.80902	3.107943e-01	5.065290e-01
1  -2.76922	3.107943e-01	5.120926e-01
1  -2.05486	3.031976e-01	5.238914e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 541 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.008302 	for  Omega_m
           0.001755 	for  b1
--> Not computing covariance matrix
3  -2.06588	3.031976e-01	5.223500e-01
1  -2.13858	3.037069e-01	5.215590e-01
1  -2.05539	3.037069e-01	5.152101e-01
1  -1.49713	3.004293e-01	5.203008e-01
1  -1.48166	3.004293e-01	5.337026e-01
1  -1.39632	2.999487e-01	5.344491e-01
5  -1.46186	2.999487e-01	5.230364e-01
1  -1.63268	3.008445e-01	5.216450e-01
1  -1.6366	3.008445e-01	5.218170e-01
1  -2.8508	3.116902e-01	5.049720e-01
1  -2.72671	3.116902e-01	4.993992e-01
3  -2.83178	3.161009e-01	4.925488e-01
1  -2.81256	3.161009e-01	5.046995e-01
1  -2.45048	3.065866e-01	5.194766e-01
6  -1.57487	3.065866e-01	4.969499e-01
3  -2.11325	3.065866e-01	5.036812e-01
2  -1.79927	3.042542e-01	5.073038e-01
1  -1.49012	3.023544e-01	5.102545e-01
1  -1.72312	3.023544e-01	5.142847e-01
2  -1.10733	3.337903e-01	4.654601e-01
2  -2.84358	3.159930e-01	4.931019e-01
3  -2.0854	3.046988e-01	5.106435e-01
1  -2.05312	3.046988e-01	5.099440e-01
4  -2.79747	3.139045e-01	4.956462e-01
2  -2.55224	3.228586e-01	4.817392e-01
5  -2.61643	3.100691e-01	5.016031e-01
1  -0.0562113	3.100691e-01	4.769523e-01
1  1.62995	2.999197e-01	4.927158e-01
1  -1.06297	2.999197e-01	5.146227e-01
3  -1.53436	3.023837e-01	5.107958e-01
1  -1.59345	3.023837e-01	5.117382e-01
2  -2.62027	3.210164e-01	4.827988e-01
1  -2.25119	3.256608e-01	4.755854e-01
1  -1.93394	3.256608e-01	4.930108e-01
1  -2.64927	3.170011e-01	5.064606e-01
1  -2.88169	3.170011e-01	4.998495e-01
4  -2.89237	3.132364e-01	5.056967e-01
1  -1.95058	3.024416e-01	5.224626e-01
1  -1.89212	3.024416e-01	5.184061e-01
1  -2.92058	3.157889e-01	4.976758e-01
2  -2.92366	3.157889e-01	4.995433e-01
3  -2.59455	3.157889e-01	5.099176e-01
1  -2.32868	3.208938e-01	5.019889e-01
1  -2.38544	3.208938e-01	5.011251e-01
1  -2.65949	3.130577e-01	5.132957e-01
2  -2.9005	3.130577e-01	5.037031e-01
2  -2.78869	3.130577e-01	4.974058e-01
1  -1.99755	3.130577e-01	4.853852e-01
1  -1.27044	3.054790e-01	4.971560e-01
2  -1.80576	3.054790e-01	5.320456e-01
3  -2.31526	3.054790e-01	5.220773e-01
1  -2.77658	3.124312e-01	5.112795e-01
1  -1.88567	3.124312e-01	4.855676e-01
1  -1.483	3.273176e-01	4.624468e-01
1  -2.0971	3.273176e-01	4.743806e-01
1  -2.62304	3.216970e-01	4.831103e-01
2  -2.66413	3.216970e-01	4.914418e-01
1  -2.52764	3.216970e-01	4.803612e-01
1  -1.76503	3.039645e-01	5.079024e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 569 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.004033 	for  Omega_m
           0.001285 	for  b1
--> Not computing covariance matrix
1  -1.34985	3.039645e-01	5.026341e-01
2  -1.67185	3.061748e-01	4.992012e-01
1  -2.31916	3.142062e-01	4.867273e-01
2  -2.09805	3.142062e-01	4.841542e-01
4  -2.06107	3.142062e-01	5.195001e-01
1  -2.8669	3.142062e-01	5.062682e-01
2  -2.55072	3.220489e-01	4.940873e-01
1  -2.79135	3.110451e-01	5.111777e-01
1  -2.80116	3.110451e-01	5.106398e-01
2  -2.78745	3.186824e-01	4.987780e-01
2  -2.42164	3.060244e-01	5.184376e-01
1  -0.816014	2.966604e-01	5.329814e-01
1  -0.669864	2.966604e-01	5.410806e-01
1  -1.16815	2.990489e-01	5.373708e-01
2  -1.29603	2.990489e-01	5.334569e-01
1  -1.34178	2.990489e-01	5.293562e-01
1  -2.87849	3.145193e-01	5.053285e-01
1  -2.92413	3.145193e-01	5.013033e-01
1  -2.92656	3.151503e-01	5.003232e-01
1  -2.92537	3.151503e-01	4.993658e-01
1  -2.83924	3.114716e-01	5.050794e-01
1  -2.83667	3.114716e-01	5.048139e-01
1  -2.89127	3.176955e-01	4.951473e-01
2  -2.52844	3.176955e-01	4.837968e-01
4  -2.88842	3.176955e-01	4.965260e-01
1  -2.80233	3.176955e-01	4.896940e-01
2  -1.95529	3.284716e-01	4.729572e-01
1  -2.40762	3.076692e-01	5.052663e-01
2  -2.57776	3.076692e-01	5.111442e-01
1  -2.5511	3.076692e-01	5.096182e-01
1  -2.38269	3.060739e-01	5.120959e-01
1  -2.43491	3.060739e-01	5.170883e-01
1  -2.39662	3.057298e-01	5.176228e-01
1  -2.37397	3.057298e-01	5.142342e-01
1  -2.90658	3.170838e-01	4.965998e-01
1  -2.59515	3.170838e-01	4.857698e-01
1  -2.48781	3.122023e-01	4.933515e-01
2  -2.61922	3.122023e-01	5.151392e-01
2  -2.55118	3.122023e-01	4.943890e-01
1  -2.67361	3.122023e-01	5.140509e-01
2  -2.40712	3.071976e-01	5.218239e-01
1  -2.69222	3.135234e-01	5.119990e-01
1  -2.90704	3.135234e-01	5.018506e-01
1  -2.92514	3.154521e-01	4.988551e-01
1  -2.86768	3.154521e-01	5.041807e-01
1  -2.58071	3.217497e-01	4.943996e-01
1  -2.01206	3.217497e-01	5.037727e-01
1  -2.2675	3.086022e-01	5.241927e-01
2  -2.59136	3.086022e-01	5.174684e-01
1  -2.13743	3.086022e-01	4.977277e-01
8  -1.61422	3.043914e-01	5.042678e-01
1  -2.36855	3.115326e-01	4.931764e-01
3  -2.84621	3.115326e-01	5.077322e-01
1  -2.19274	3.262836e-01	4.848217e-01
1  -1.62575	3.262836e-01	4.950191e-01
1  0.844275	3.386513e-01	4.758103e-01
1  -0.0906068	3.386513e-01	4.585904e-01
2  -1.2852	3.328289e-01	4.676335e-01
2  -1.80433	3.296547e-01	4.725635e-01
3  -2.71886	3.208031e-01	4.863113e-01
1  -2.34008	3.208031e-01	4.774111e-01
1  -2.28657	3.218635e-01	4.757642e-01
1  -2.53071	3.218635e-01	4.804259e-01
2  -1.74949	3.295003e-01	4.685648e-01
1  -1.79619	3.291650e-01	4.690856e-01
1  -1.70183	3.291650e-01	4.827219e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 604 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002865 	for  Omega_m
           0.000523 	for  b1
--> Not computing covariance matrix
4  -1.81666	3.284157e-01	4.838858e-01
1  -2.15165	3.259755e-01	4.876758e-01
3  -2.0421	3.259755e-01	4.900352e-01
1  -1.99434	3.263421e-01	4.894658e-01
2  -2.16165	3.263421e-01	4.855388e-01
1  -1.64662	3.263421e-01	4.647449e-01
4  -2.0828	3.155656e-01	4.814824e-01
1  -2.08464	3.188757e-01	4.763414e-01
1  -2.81759	3.188757e-01	4.898010e-01
1  -2.78943	3.195810e-01	4.887056e-01
1  -2.17951	3.195810e-01	4.765412e-01
3  -2.20777	3.181449e-01	4.787716e-01
1  -1.8338	3.181449e-01	4.747926e-01
2  -1.47102	3.257080e-01	4.630459e-01
1  -1.59844	3.111736e-01	4.856199e-01
1  -2.47368	3.111736e-01	4.956571e-01
2  -1.1554	3.009007e-01	5.116125e-01
1  -1.54861	3.030636e-01	5.082531e-01
1  -2.03625	3.030636e-01	5.240247e-01
1  -2.04399	3.031168e-01	5.239421e-01
2  -1.54425	3.031168e-01	5.079874e-01
1  -1.18306	3.031168e-01	5.036726e-01
1  -2.30167	3.195606e-01	4.781330e-01
2  -2.81173	3.195606e-01	4.902892e-01
1  -2.66301	3.195606e-01	4.844193e-01
1  -2.6615	3.196003e-01	4.843577e-01
1  -2.817	3.196003e-01	4.927133e-01
2  -1.98065	3.282856e-01	4.792238e-01
1  -2.5663	3.232081e-01	4.871099e-01
1  -2.57279	3.232081e-01	4.860504e-01
1  -2.92087	3.153472e-01	4.982595e-01
1  -2.87907	3.153472e-01	4.955110e-01
1  -2.84324	3.132082e-01	4.988332e-01
1  -2.904	3.132082e-01	5.033640e-01
2  -2.91194	3.167403e-01	4.978780e-01
4  -2.15865	3.039786e-01	5.176989e-01
1  -1.76879	3.014988e-01	5.215505e-01
1  -1.37316	3.014988e-01	5.121474e-01
1  -1.06418	2.999330e-01	5.145792e-01
1  -1.00456	2.999330e-01	5.414901e-01
1  -0.659503	2.980579e-01	5.444023e-01
1  -0.231025	2.980579e-01	5.494029e-01
1  0.101315	2.964103e-01	5.519619e-01
1  -0.540702	2.964103e-01	5.250024e-01
2  -2.43746	3.071114e-01	5.083820e-01
1  -1.97322	3.035090e-01	5.139771e-01
1  -1.69949	3.035090e-01	5.086988e-01
6  -1.50909	3.023711e-01	5.104661e-01
1  -2.26524	3.078219e-01	5.020002e-01
1  -1.86344	3.078219e-01	4.965630e-01
3  -2.31981	3.144377e-01	4.862877e-01
2  -2.29196	3.144377e-01	4.859410e-01
1  -2.1297	3.144377e-01	4.840557e-01
1  -2.14033	3.195728e-01	4.760802e-01
1  -2.56272	3.195728e-01	4.822580e-01
1  -2.46219	3.217200e-01	4.789231e-01
2  -2.63972	3.217200e-01	4.837883e-01
1  -2.4579	3.217200e-01	4.973837e-01
4  -2.53727	3.207175e-01	4.989408e-01
5  -1.23135	3.309587e-01	4.830347e-01
1  -0.958045	3.309587e-01	4.866774e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 634 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.002349 	for  Omega_m
           0.000222 	for  b1
--> Not computing covariance matrix
4  -1.28213	3.291131e-01	4.895439e-01
4  -1.24952	3.293077e-01	4.892416e-01
1  -2.07673	3.046496e-01	5.275393e-01
1  -1.07016	3.046496e-01	5.400981e-01
1  -1.04411	3.202209e-01	5.159135e-01
6  0.428675	3.202209e-01	5.247407e-01
1  -1.34209	3.202209e-01	5.136966e-01
1  -1.68906	3.136090e-01	5.239659e-01
2  -2.35695	3.136090e-01	5.171346e-01
1  -2.68528	3.136090e-01	5.120159e-01
1  -2.40803	3.072794e-01	5.218467e-01
1  -1.04114	3.072794e-01	5.379076e-01
2  -1.01641	3.170705e-01	5.227005e-01
1  -1.17267	3.111873e-01	5.318380e-01
1  -2.77036	3.111873e-01	5.023931e-01
1  -2.88735	3.161198e-01	4.947322e-01
4  -2.53791	3.161198e-01	5.101724e-01
3  -2.91141	3.161198e-01	4.963448e-01
3  -1.58398	3.008150e-01	5.201154e-01
1  -1.6008	3.008150e-01	5.315102e-01
1  -0.530222	2.956616e-01	5.395142e-01
3  -0.083015	2.956616e-01	5.217345e-01
1  0.809632	2.925980e-01	5.264926e-01
2  0.2723	2.925980e-01	5.390843e-01
1  0.483367	2.925980e-01	5.318114e-01
2  -1.04556	2.983727e-01	5.228425e-01
1  -2.07463	3.039777e-01	5.141371e-01
4  -1.41099	3.039777e-01	5.032656e-01
3  -1.48804	3.039777e-01	5.041550e-01
1  -2.39199	3.205183e-01	4.784651e-01
1  -2.66514	3.205183e-01	4.965092e-01
1  -2.81311	3.176405e-01	5.009788e-01
1  -2.78506	3.176405e-01	4.892140e-01
1  -2.6369	3.107717e-01	4.998822e-01
1  -2.42018	3.107717e-01	4.958484e-01
1  -2.60359	3.152269e-01	4.889288e-01
1  -2.58011	3.152269e-01	4.885337e-01
5  -2.44553	3.115735e-01	4.942079e-01
1  -2.81155	3.115735e-01	5.104004e-01
5  -2.57162	3.217771e-01	4.945528e-01
1  -2.68686	3.217771e-01	4.883518e-01
2  -0.956679	3.344085e-01	4.687334e-01
6  -1.71674	3.301468e-01	4.753524e-01
6  -1.22249	3.330231e-01	4.708851e-01
1  -1.83045	3.294107e-01	4.764957e-01
5  -1.57525	3.294107e-01	4.841001e-01
2  -2.36853	3.233837e-01	4.934609e-01
2  -2.60627	3.206048e-01	4.977769e-01
1  -2.77156	3.114166e-01	5.120475e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 659 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001971 	for  Omega_m
           0.000619 	for  b1
--> Not computing covariance matrix
2  -2.4931	3.114166e-01	4.953545e-01
3  -1.52523	3.114166e-01	5.287723e-01
2  -1.51303	3.139479e-01	5.248409e-01
1  0.561027	3.315247e-01	4.975415e-01
1  0.469284	3.315247e-01	4.969418e-01
4  -1.47233	3.170281e-01	5.194572e-01
1  -1.58586	3.140284e-01	5.241162e-01
1  -2.91573	3.140284e-01	5.010119e-01
1  -2.67646	3.088599e-01	5.090393e-01
1  -1.40905	3.088599e-01	4.893686e-01
1  -1.67958	3.120902e-01	4.843516e-01
1  -2.5393	3.120902e-01	4.944570e-01
1  -2.64849	3.166849e-01	4.873208e-01
2  -2.90796	3.166849e-01	4.988050e-01
1  -2.41679	3.166849e-01	4.836241e-01
1  -1.83937	3.069920e-01	4.986787e-01
1  -2.49795	3.069920e-01	5.184040e-01
1  -2.84192	3.142114e-01	5.071912e-01
1  -2.81011	3.142114e-01	4.953369e-01
4  -2.74285	3.121430e-01	4.985494e-01
2  -2.81996	3.170583e-01	4.909153e-01
2  -2.4753	3.238393e-01	4.803834e-01
1  -0.95473	3.345786e-01	4.637036e-01
1  -0.954881	3.345786e-01	4.660134e-01
1  -1.66319	3.305948e-01	4.722007e-01
1  -1.63076	3.305948e-01	4.686222e-01
2  -2.29631	3.254102e-01	4.766747e-01
1  -2.77583	3.150020e-01	4.928402e-01
2  -2.7133	3.150020e-01	4.914115e-01
1  -2.70917	3.150020e-01	5.092834e-01
2  -2.45534	3.075841e-01	5.208044e-01
1  -2.54901	3.088789e-01	5.187934e-01
1  -2.69053	3.088789e-01	5.103177e-01
1  -2.54278	3.233449e-01	4.878500e-01
1  -2.4595	3.233449e-01	4.913245e-01
1  -0.829214	3.341151e-01	4.745968e-01
1  -0.95274	3.341151e-01	4.715786e-01
4  -2.26345	3.259150e-01	4.843146e-01
5  -2.61636	3.224223e-01	4.897393e-01
1  -2.30769	3.224223e-01	4.757766e-01
2  -1.97703	3.263550e-01	4.696685e-01
1  -2.48575	3.157819e-01	4.860901e-01
3  -2.88079	3.157819e-01	5.029582e-01
3  -2.56465	3.222266e-01	4.929486e-01
1  -1.99764	3.222266e-01	5.026627e-01
1  -1.9118	3.043100e-01	5.304899e-01
1  -1.95009	3.043100e-01	5.096112e-01
1  -2.35395	3.248739e-01	4.776724e-01
1  -2.31435	3.248739e-01	4.885103e-01
1  -2.85147	3.174528e-01	5.000364e-01
1  -0.826938	3.174528e-01	5.232041e-01
1  -0.0866773	3.244154e-01	5.123902e-01
1  0.371475	3.244154e-01	5.150334e-01
1  0.825134	3.272009e-01	5.107071e-01
5  -0.161907	3.272009e-01	5.048494e-01
1  0.445454	3.305075e-01	4.997138e-01
1  -1.05363	3.305075e-01	4.872203e-01
3  -1.2244	3.295329e-01	4.887339e-01
1  -0.77749	3.295329e-01	4.542013e-01
4  -1.4219	3.218612e-01	4.661167e-01
2  -1.48116	3.201563e-01	4.687647e-01
1  -1.50245	3.190588e-01	4.704691e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 689 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001695 	for  Omega_m
           0.000540 	for  b1
--> Not computing covariance matrix
3  -2.51344	3.190588e-01	4.818811e-01
2  -2.52652	3.147073e-01	4.886397e-01
1  -2.54621	3.161292e-01	4.864313e-01
1  -2.88995	3.161292e-01	5.017262e-01
1  -2.83277	3.182109e-01	4.984931e-01
3  -2.87457	3.182109e-01	4.938931e-01
1  -2.74234	3.209583e-01	4.896259e-01
1  -2.73976	3.209583e-01	4.885542e-01
1  -2.84957	3.187443e-01	4.919929e-01
2  -2.49569	3.187443e-01	5.050279e-01
1  -2.8043	3.187443e-01	4.891654e-01
2  -2.75723	3.199230e-01	4.873348e-01
2  -2.75286	3.117061e-01	5.000967e-01
1  -2.55934	3.088176e-01	5.045830e-01
2  -2.66217	3.088176e-01	5.083801e-01
2  -2.6727	3.088176e-01	5.090723e-01
1  -1.14715	3.088176e-01	4.872907e-01
2  -1.31228	3.252290e-01	4.618014e-01
1  -0.978228	3.286387e-01	4.565057e-01
2  -0.727014	3.286387e-01	4.541651e-01
1  -1.92767	3.286387e-01	4.723982e-01
1  -1.78413	3.296576e-01	4.708157e-01
3  0.353825	3.296576e-01	5.015112e-01
1  2.48439	3.387270e-01	4.874250e-01
1  1.62365	3.387270e-01	4.819283e-01
1  1.74395	3.391749e-01	4.812328e-01
1  1.8028	3.391749e-01	4.816467e-01
2  1.63437	3.385476e-01	4.826210e-01
1  1.54018	3.381912e-01	4.831745e-01
1  -0.120881	3.381912e-01	4.636460e-01
3  -1.40695	3.319202e-01	4.733858e-01
2  -0.63508	3.319202e-01	4.523254e-01
1  0.544328	3.319202e-01	4.423417e-01
1  -0.372404	3.178453e-01	4.642021e-01
1  0.216534	3.178453e-01	4.607039e-01
1  0.512047	3.265947e-01	4.471147e-01
1  -1.06711	3.265947e-01	4.585059e-01
1  -1.46844	3.165136e-01	4.741634e-01
3  -2.27034	3.165136e-01	4.820038e-01
1  -1.53305	3.059248e-01	4.984498e-01
1  -2.3387	3.059248e-01	5.113268e-01
4  -2.79597	3.113301e-01	5.029314e-01
1  -2.56045	3.233331e-01	4.842890e-01
1  -2.29346	3.233331e-01	4.951362e-01
1  -2.70733	3.174420e-01	5.042861e-01
4  -2.56955	3.174420e-01	4.848244e-01
2  -2.79624	3.174420e-01	5.020410e-01
5  -2.84095	3.174420e-01	4.912994e-01
2  -2.84361	3.172940e-01	4.915293e-01
4  -2.84379	3.172831e-01	4.915462e-01
1  -2.64346	3.219370e-01	4.843179e-01
1  -2.41864	3.219370e-01	4.974418e-01
2  -2.76147	3.139475e-01	5.098508e-01
1  -2.73102	3.165101e-01	5.058706e-01
2  -2.61374	3.165101e-01	5.081480e-01
2  -2.91361	3.165101e-01	4.964961e-01
1  -2.81633	3.165101e-01	5.036923e-01
1  -0.371915	3.358092e-01	4.737180e-01
1  -0.677711	3.358092e-01	4.661846e-01
1  -1.10037	3.337053e-01	4.694523e-01
1  -0.773832	3.337053e-01	4.777066e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 719 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001956 	for  Omega_m
           0.000465 	for  b1
--> Not computing covariance matrix
5  -1.65701	3.288012e-01	4.853233e-01
1  -1.91457	3.288012e-01	4.779081e-01
1  -2.91977	3.144243e-01	5.002376e-01
2  -2.75286	3.144243e-01	4.934070e-01
3  -2.65227	3.144243e-01	5.113739e-01
1  -2.60287	3.168707e-01	5.075742e-01
1  -2.90854	3.168707e-01	4.978774e-01
2  -2.81326	3.107898e-01	5.073220e-01
1  -2.92262	3.159077e-01	4.993731e-01
1  -2.8596	3.159077e-01	5.035676e-01
3  -1.18321	3.321190e-01	4.783891e-01
1  -1.15505	3.321190e-01	4.789320e-01
3  -2.20125	3.252970e-01	4.895277e-01
1  -1.53318	3.252970e-01	4.990579e-01
4  -2.16053	3.077882e-01	5.262517e-01
1  -1.66625	3.029113e-01	5.338262e-01
1  -1.32607	3.029113e-01	5.059796e-01
2  -1.08123	3.015619e-01	5.080754e-01
1  -2.24998	3.104199e-01	4.943177e-01
2  -1.47768	3.104199e-01	4.862641e-01
1  -2.75793	3.104199e-01	5.049615e-01
1  -1.9649	3.030775e-01	5.163653e-01
1  -2.04771	3.030775e-01	5.226924e-01
2  -2.88704	3.149519e-01	5.042496e-01
5  -2.768	3.102675e-01	5.115252e-01
1  -2.67615	3.102675e-01	5.025250e-01
1  -2.8585	3.158326e-01	4.938816e-01
1  -2.10037	3.158326e-01	4.812050e-01
3  -1.74169	3.093174e-01	4.913241e-01
1  -2.4469	3.093174e-01	5.208116e-01
1  -2.37887	3.194076e-01	5.051400e-01
1  -2.66477	3.194076e-01	5.000729e-01
1  -2.77221	3.169730e-01	5.038541e-01
1  -2.85832	3.169730e-01	5.010830e-01
1  -2.23873	3.254388e-01	4.879344e-01
1  -1.24561	3.254388e-01	4.610103e-01
1  -0.647512	3.308933e-01	4.525387e-01
3  -1.59179	3.308933e-01	4.744710e-01
1  -1.23036	3.329531e-01	4.712718e-01
1  -0.899591	3.329531e-01	4.792657e-01
1  -2.8008	3.136902e-01	5.091839e-01
2  -2.0052	3.136902e-01	5.209296e-01
1  -2.07633	3.136902e-01	5.202089e-01
2  -1.95069	3.083763e-01	5.284621e-01
1  -2.07125	3.117725e-01	5.231873e-01
2  -2.85861	3.117725e-01	5.067031e-01
1  -2.82952	3.117725e-01	5.095301e-01
2  -2.49725	3.067603e-01	5.173147e-01
1  -2.02252	3.029181e-01	5.232822e-01
1  -1.69355	3.029181e-01	5.333851e-01
2  -0.448922	2.960909e-01	5.439888e-01
1  -1.43746	3.011704e-01	5.360995e-01
1  -0.675623	3.011704e-01	5.452887e-01
5  -0.967255	3.034364e-01	5.417694e-01
1  -2.09703	3.034364e-01	5.226369e-01
2  -2.72753	3.197308e-01	4.973293e-01
1  -2.18131	3.040475e-01	5.216877e-01
1  -2.13434	3.040475e-01	5.246685e-01
1  -2.49982	3.074665e-01	5.193583e-01
1  -2.55201	3.074665e-01	5.170334e-01
1  -2.48962	3.226222e-01	4.934943e-01
3  -2.60312	3.226222e-01	4.892004e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 751 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000339 	for  Omega_m
           0.000111 	for  b1
--> Not computing covariance matrix
2  -1.44269	3.315287e-01	4.753673e-01
1  -0.308232	3.371813e-01	4.665880e-01
1  -0.327471	3.371813e-01	4.542832e-01
1  -2.40115	3.222024e-01	4.775477e-01
1  -1.89312	3.222024e-01	5.039006e-01
1  -1.89969	3.221371e-01	5.040020e-01
1  -2.64233	3.221371e-01	4.848002e-01
3  -1.9862	3.284019e-01	4.750702e-01
1  -1.97359	3.284019e-01	4.736810e-01
6  -2.47214	3.239622e-01	4.805764e-01
2  -2.81685	3.139267e-01	4.961631e-01
2  -1.92643	3.287474e-01	4.731444e-01
1  -2.83393	3.149259e-01	4.946112e-01
1  -2.92336	3.149259e-01	5.015321e-01
1  -2.32264	3.253808e-01	4.852941e-01
1  -1.89337	3.253808e-01	4.945474e-01
1  -2.40878	3.077256e-01	5.219686e-01
1  -2.59928	3.077256e-01	5.131635e-01
2  -2.43227	3.060600e-01	5.157504e-01
5  -2.25264	3.045739e-01	5.180585e-01
1  -2.21955	3.045739e-01	5.155473e-01
1  -2.61115	3.227296e-01	4.873488e-01
1  -1.72416	3.227296e-01	5.042629e-01
1  -1.4403	3.250763e-01	5.006181e-01
1  -0.679073	3.250763e-01	5.068639e-01
1  -1.53253	3.160526e-01	5.208790e-01
1  -1.75856	3.160526e-01	5.189928e-01
1  -1.73537	3.087339e-01	5.303598e-01
1  -2.55345	3.087339e-01	5.186587e-01
1  -2.69444	3.166183e-01	5.064130e-01
4  -2.68221	3.166183e-01	4.880764e-01
4  -2.36925	3.166183e-01	5.115304e-01
3  -2.1872	3.166183e-01	5.136976e-01
1  -2.25528	3.136718e-01	5.182740e-01
1  -2.91339	3.136718e-01	5.029569e-01
1  -2.61833	3.224644e-01	4.893007e-01
1  -2.2369	3.224644e-01	4.746143e-01
1  -2.31271	3.210849e-01	4.767568e-01
1  -2.63281	3.210849e-01	4.954042e-01
1  -2.45142	3.232219e-01	4.920852e-01
1  -2.21578	3.232219e-01	4.968245e-01
3  -2.18271	3.235365e-01	4.963359e-01
3  -1.74908	3.235365e-01	5.018261e-01
1  -1.75422	3.234918e-01	5.018955e-01
2  -0.836516	3.234918e-01	5.097327e-01
1  -1.73901	3.234918e-01	5.020556e-01
1  -1.71113	3.237316e-01	5.016833e-01
3  -1.26479	3.237316e-01	5.058269e-01
1  -1.5947	3.206700e-01	5.105819e-01
1  -0.868032	3.206700e-01	5.161365e-01
1  0.066336	3.275029e-01	5.055241e-01
1  -0.312322	3.275029e-01	5.030161e-01
2  0.337106	3.310063e-01	4.975747e-01
2  0.722381	3.328313e-01	4.947403e-01
3  -0.252758	3.278537e-01	5.024712e-01
1  -0.658263	3.278537e-01	4.994758e-01
1  -1.85691	3.168254e-01	5.166044e-01
1  -2.89866	3.168254e-01	4.992296e-01
1  -2.43774	3.061024e-01	5.158840e-01
1  -2.4334	3.061024e-01	5.150875e-01
4  -1.98425	3.027415e-01	5.203075e-01
1  -2.1937	3.041709e-01	5.180874e-01
1  -2.10074	3.041709e-01	5.262046e-01
1  -2.66876	3.166998e-01	5.067453e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 781 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000770 	for  Omega_m
           0.000077 	for  b1
--> Not computing covariance matrix
1  -2.8529	3.166998e-01	5.020047e-01
1  -2.87677	3.149348e-01	5.047460e-01
1  -2.80715	3.149348e-01	5.070941e-01
2  -2.55575	3.209936e-01	4.976840e-01
1  -2.40352	3.227806e-01	4.949084e-01
1  -2.19981	3.227806e-01	4.984426e-01
1  -2.51423	3.187651e-01	5.046793e-01
1  -2.46894	3.187651e-01	4.814915e-01
1  -2.06567	3.254879e-01	4.710500e-01
1  0.501597	3.254879e-01	4.484113e-01
3  0.354364	3.227472e-01	4.526679e-01
1  -2.3873	3.227472e-01	4.771403e-01
1  -2.58274	3.144722e-01	4.899926e-01
2  -2.71402	3.144722e-01	4.924445e-01
1  -2.92374	3.144722e-01	5.012043e-01
3  -2.9112	3.168139e-01	4.975673e-01
2  -2.83585	3.168139e-01	5.023480e-01
3  -2.80697	3.168139e-01	5.032693e-01
2  -2.76158	3.109029e-01	5.124501e-01
2  -2.69467	3.096036e-01	5.144681e-01
1  -2.66157	3.090777e-01	5.152849e-01
2  -2.31112	3.090777e-01	5.232075e-01
1  -2.2856	3.090777e-01	5.235876e-01
3  -2.25148	3.184934e-01	5.089635e-01
4  -2.84951	3.184934e-01	4.915587e-01
1  -2.61583	3.184934e-01	4.843493e-01
1  -2.54904	3.204379e-01	4.813292e-01
1  -2.73503	3.204379e-01	4.942553e-01
1  -2.87893	3.172682e-01	4.991783e-01
2  -2.9021	3.172682e-01	4.958557e-01
1  -2.76923	3.172682e-01	4.891831e-01
1  -2.2466	3.067023e-01	5.055935e-01
1  -2.02776	3.067023e-01	5.286483e-01
1  -2.23251	3.100832e-01	5.233973e-01
1  -2.10172	3.100832e-01	5.249948e-01
2  -2.05483	3.171745e-01	5.139810e-01
1  -1.68847	3.220071e-01	5.064751e-01
1  -0.990434	3.220071e-01	5.122086e-01
1  -1.543	3.119004e-01	5.279059e-01
1  -2.66157	3.119004e-01	5.146226e-01
3  -2.642	3.112413e-01	5.156463e-01
1  -2.01503	3.112413e-01	4.895307e-01
2  -2.11776	3.129853e-01	4.868220e-01
2  -2.21402	3.164126e-01	4.814990e-01
1  -2.03924	3.227575e-01	4.716443e-01
2  -1.86144	3.227575e-01	4.695081e-01
1  -2.38375	3.227575e-01	4.770665e-01
4  -2.52205	3.202897e-01	4.808994e-01
3  -2.55622	3.193807e-01	4.823112e-01
1  -2.72152	3.193807e-01	4.860813e-01
1  -2.78372	3.163463e-01	4.907941e-01
1  -2.70172	3.163463e-01	4.888873e-01
1  -2.66015	3.189893e-01	4.847823e-01
1  -2.786	3.189893e-01	4.883820e-01
2  -2.54429	3.231327e-01	4.819467e-01
2  -2.75034	3.119400e-01	4.993306e-01
2  -2.79201	3.188154e-01	4.886521e-01
2  -2.83841	3.151192e-01	4.943928e-01
1  -2.71712	3.205474e-01	4.859621e-01
2  -2.76405	3.205474e-01	4.891616e-01
1  -2.71089	3.205474e-01	4.948378e-01
2  0.41317	2.921666e-01	5.389174e-01
2  -0.814215	2.966802e-01	5.319070e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 814 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000478 	for  Omega_m
           0.000137 	for  b1
--> Not computing covariance matrix
2  -2.83748	3.181039e-01	4.986328e-01
2  -2.76747	3.101043e-01	5.110575e-01
1  -1.81966	3.016303e-01	5.242189e-01
2  -0.90937	3.016303e-01	5.059495e-01
1  -1.0602	3.016303e-01	5.413891e-01
1  -1.58393	3.063548e-01	5.340512e-01
1  -2.39642	3.063548e-01	5.211364e-01
2  -2.76878	3.158025e-01	5.064627e-01
1  -2.71444	3.109261e-01	5.140365e-01
1  -2.5046	3.109261e-01	5.185484e-01
1  -2.53247	3.119282e-01	5.169921e-01
1  -2.79564	3.119282e-01	5.008221e-01
2  -1.22915	3.331393e-01	4.678782e-01
1  -2.65078	3.220507e-01	4.851004e-01
1  -2.20162	3.220507e-01	4.743697e-01
1  -2.03055	3.095934e-01	4.937178e-01
3  -1.88259	3.095934e-01	5.279330e-01
4  -1.92322	3.146558e-01	5.200702e-01
1  -1.85503	3.166421e-01	5.169852e-01
1  -2.02801	3.166421e-01	5.153279e-01
1  -2.01644	3.169007e-01	5.149262e-01
1  -2.24667	3.169007e-01	5.124510e-01
1  -2.1118	3.074534e-01	5.271240e-01
2  -2.39362	3.074534e-01	5.057851e-01
1  -2.3839	3.074534e-01	5.055657e-01
3  -2.5018	3.086801e-01	5.036606e-01
4  -1.35862	3.086801e-01	4.893751e-01
1  0.330429	3.086801e-01	4.777323e-01
1  1.28235	3.026690e-01	4.870684e-01
1  1.21328	3.026690e-01	4.874541e-01
1  -0.323542	3.181166e-01	4.634617e-01
1  -1.4306	3.181166e-01	4.712736e-01
1  -0.76211	3.290744e-01	4.542546e-01
1  -1.84706	3.290744e-01	4.789541e-01
1  -2.82177	3.193806e-01	4.940100e-01
3  -1.99212	3.193806e-01	5.098247e-01
1  -0.872117	3.285722e-01	4.955488e-01
1  -1.90381	3.285722e-01	4.709844e-01
2  -2.67413	3.198365e-01	4.845524e-01
2  -2.73808	3.176620e-01	4.879296e-01
3  -2.59269	3.109922e-01	4.982888e-01
2  -1.90096	3.109922e-01	4.889051e-01
1  -1.21352	3.109922e-01	4.828256e-01
2  -1.36252	3.131880e-01	4.794152e-01
2  -1.48214	3.167305e-01	4.739131e-01
1  -1.23864	3.113091e-01	4.823334e-01
1  -2.83129	3.113091e-01	5.052920e-01
1  -2.7617	3.100545e-01	5.072405e-01
2  -2.63176	3.100545e-01	5.020371e-01
1  -2.26901	3.100545e-01	4.955229e-01
1  -2.00039	3.072687e-01	4.998497e-01
1  -2.52233	3.072687e-01	5.180205e-01
1  -2.50346	3.070609e-01	5.183431e-01
3  -2.35662	3.070609e-01	5.229622e-01
2  -1.89399	3.029493e-01	5.293482e-01
2  0.364146	2.924259e-01	5.456926e-01
2  -0.736512	2.966557e-01	5.391231e-01
4  -1.85023	3.026414e-01	5.298264e-01
2  -2.55597	3.178178e-01	5.062552e-01
2  -2.63437	3.152824e-01	5.101931e-01
1  -2.22568	3.224460e-01	4.990669e-01
1  -2.1727	3.224460e-01	4.998263e-01
1  -2.548	3.168546e-01	5.085105e-01
1  -1.02088	3.168546e-01	4.701656e-01
1  -1.03154	3.185972e-01	4.674592e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 846 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000020 	for  Omega_m
           0.000355 	for  b1
--> Not computing covariance matrix
2  -2.15252	3.185972e-01	4.774924e-01
2  -2.16184	3.185972e-01	4.776009e-01
1  -2.79246	3.185972e-01	4.887425e-01
6  -2.3004	3.256794e-01	4.777427e-01
2  -2.34341	3.252695e-01	4.783795e-01
1  -2.24727	3.261646e-01	4.769892e-01
1  -2.18954	3.261646e-01	4.745291e-01
1  -2.73766	3.171113e-01	4.885902e-01
1  -2.54656	3.171113e-01	4.849132e-01
1  -2.29982	3.232685e-01	4.753502e-01
1  -2.05854	3.232685e-01	4.715487e-01
1  -1.89029	3.253804e-01	4.682686e-01
1  -2.36166	3.253804e-01	4.815861e-01
2  -2.09995	3.275644e-01	4.781940e-01
1  -2.80245	3.112644e-01	5.035103e-01
2  -2.79942	3.112644e-01	5.108919e-01
1  -1.70741	3.112644e-01	5.274357e-01
1  -1.43208	3.194233e-01	5.147637e-01
4  -2.30566	3.194233e-01	5.060990e-01
1  -2.79423	3.194233e-01	4.888436e-01
2  -2.52383	3.081250e-01	5.063917e-01
2  -2.86451	3.146023e-01	4.963314e-01
3  -2.87129	3.161083e-01	4.939923e-01
1  -2.91957	3.161083e-01	4.992825e-01
1  -2.66799	3.218179e-01	4.904147e-01
1  -2.49161	3.218179e-01	4.963649e-01
1  -2.56213	3.209318e-01	4.977411e-01
1  0.217252	3.209318e-01	5.220997e-01
2  0.464438	2.999908e-01	5.546241e-01
1  -0.272665	3.076929e-01	5.426617e-01
3  -1.74815	3.076929e-01	5.312676e-01
5  -1.35217	3.224486e-01	5.083498e-01
1  -2.08796	3.224486e-01	5.009473e-01
1  -2.49101	3.163356e-01	5.104417e-01
3  -2.58358	3.163356e-01	4.867077e-01
1  -2.53193	3.135595e-01	4.910194e-01
2  -2.78327	3.135595e-01	4.960396e-01
2  -2.90416	3.135595e-01	5.013158e-01
1  -2.35254	3.135595e-01	5.172694e-01
3  -2.12726	3.195532e-01	5.079602e-01
1  -1.59493	3.195532e-01	4.705749e-01
1  -1.60755	3.168325e-01	4.748005e-01
2  -2.16332	3.168325e-01	4.802353e-01
1  -2.33138	3.168325e-01	4.822552e-01
1  -0.620247	3.348909e-01	4.542079e-01
4  -0.874429	3.348909e-01	4.671842e-01
1  -0.805643	3.348909e-01	4.700671e-01
1  0.350867	3.399592e-01	4.621953e-01
1  0.962004	3.399592e-01	4.715066e-01
2  0.079371	3.364099e-01	4.770193e-01
1  -0.821036	3.322030e-01	4.835532e-01
1  -1.26323	3.322030e-01	4.761060e-01
1  -0.787886	3.346428e-01	4.723166e-01
4  -0.92018	3.346428e-01	4.616863e-01
3  -0.917723	3.346428e-01	4.615430e-01
1  -1.48389	3.314255e-01	4.665400e-01
3  -0.691717	3.314255e-01	4.529291e-01
1  0.5239	3.383654e-01	4.421503e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 876 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000138 	for  Omega_m
           0.000249 	for  b1
--> Not computing covariance matrix
1  0.515259	3.383654e-01	4.422519e-01
1  -0.802037	3.307042e-01	4.541510e-01
1  -0.43823	3.307042e-01	4.506332e-01
1  0.046121	3.339876e-01	4.455336e-01
1  -0.886338	3.339876e-01	4.576749e-01
1  -1.22046	3.320119e-01	4.607434e-01
2  -1.36393	3.320119e-01	4.646230e-01
1  -1.18894	3.320119e-01	4.601010e-01
2  0.0178628	3.384154e-01	4.501555e-01
1  0.50373	3.405623e-01	4.468209e-01
1  0.636447	3.405623e-01	4.440031e-01
2  0.173658	3.384865e-01	4.472272e-01
2  -1.79288	3.258965e-01	4.667812e-01
1  -1.94326	3.241492e-01	4.694951e-01
2  -2.30836	3.241492e-01	4.755929e-01
1  -2.01099	3.241492e-01	4.704174e-01
3  -1.39929	3.298493e-01	4.615642e-01
9  -0.864976	3.298493e-01	4.549616e-01
3  -0.578158	3.319364e-01	4.517201e-01
2  -1.04036	3.319364e-01	4.816876e-01
2  -1.36572	3.319364e-01	4.643557e-01
1  -1.0796	3.319364e-01	4.580737e-01
2  -1.64019	3.278001e-01	4.644980e-01
1  -1.47333	3.291676e-01	4.623739e-01
4  -1.8648	3.291676e-01	4.770348e-01
1  -1.82428	3.291676e-01	4.791752e-01
1  -1.53073	3.309943e-01	4.763381e-01
4  -1.38845	3.309943e-01	4.800891e-01
1  -1.38315	3.309943e-01	4.801978e-01
2  -2.11672	3.035969e-01	5.227501e-01
1  -1.16066	2.981831e-01	5.311585e-01
5  -0.749383	2.981831e-01	5.183442e-01
2  -2.24408	3.257517e-01	4.755262e-01
2  -2.32162	3.249834e-01	4.767194e-01
1  -2.50809	3.228031e-01	4.801056e-01
5  -1.96096	3.228031e-01	4.706316e-01
1  -2.08901	3.144065e-01	4.836729e-01
1  -2.89324	3.144065e-01	4.980856e-01
2  -2.30188	3.056374e-01	5.117052e-01
2  -1.47971	3.004323e-01	5.197895e-01
1  -1.26205	2.993499e-01	5.214706e-01
1  -1.34984	2.993499e-01	5.332005e-01
1  -2.37372	3.220214e-01	4.979883e-01
1  -2.62318	3.220214e-01	4.917188e-01
3  -2.81191	3.190797e-01	4.962878e-01
1  -2.15749	3.190797e-01	4.769073e-01
1  -2.13125	3.200519e-01	4.753973e-01
1  -2.78701	3.200519e-01	4.894297e-01
4  -2.81942	3.118011e-01	5.022444e-01
1  -2.90085	3.149551e-01	4.973457e-01
2  -2.81612	3.149551e-01	4.940129e-01
1  -2.82842	3.149551e-01	5.064404e-01
1  -2.24017	3.246319e-01	4.914109e-01
1  -2.40129	3.246319e-01	4.866450e-01
1  -2.776	3.200731e-01	4.937255e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 904 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000538 	for  Omega_m
           0.000130 	for  b1
--> Not computing covariance matrix
1  -2.79042	3.200731e-01	4.899678e-01
1  -2.44696	3.245640e-01	4.829928e-01
1  -2.35622	3.245640e-01	4.772039e-01
1  -2.75057	3.160217e-01	4.904713e-01
1  -2.91234	3.160217e-01	5.004645e-01
1  -2.77482	3.100861e-01	5.096834e-01
2  -2.19476	3.100861e-01	4.944527e-01
1  -1.43073	3.100861e-01	4.866302e-01
3  -1.72466	3.202602e-01	4.708283e-01
1  -1.70995	3.202602e-01	5.105151e-01
1  -1.76056	3.196436e-01	5.114728e-01
2  -2.69527	3.196436e-01	4.985823e-01
1  -2.31376	3.196436e-01	5.054506e-01
2  -1.3476	3.280809e-01	4.923462e-01
1  -1.99215	3.232572e-01	4.998380e-01
1  -2.20274	3.232572e-01	4.969173e-01
1  -1.69177	3.273345e-01	4.905846e-01
1  -1.11758	3.273345e-01	4.970693e-01
1  0.0790098	3.337141e-01	4.871608e-01
1  0.120998	3.337141e-01	4.875158e-01
5  0.778004	3.365530e-01	4.831066e-01
3  -0.52863	3.365530e-01	4.645113e-01
1  -2.80446	3.112022e-01	5.038849e-01
2  -2.78026	3.112022e-01	5.027335e-01
1  -2.76256	3.112022e-01	5.124125e-01
1  -2.23331	3.046393e-01	5.226057e-01
1  -2.04251	3.046393e-01	5.099894e-01
1  -2.71981	3.118264e-01	4.988267e-01
1  -2.79063	3.118264e-01	5.009667e-01
1  -2.45221	3.072824e-01	5.080242e-01
1  -1.79519	3.072824e-01	4.973221e-01
1  -1.75239	3.069239e-01	4.978789e-01
1  -1.72065	3.069239e-01	4.975272e-01
1  -2.03799	3.100220e-01	4.927153e-01
1  -1.24646	3.100220e-01	4.852564e-01
2  -1.4382	3.125214e-01	4.813745e-01
1  -0.434569	3.038389e-01	4.948597e-01
1  -2.06877	3.038389e-01	5.148050e-01
2  -2.80698	3.114502e-01	5.029835e-01
2  0.210831	2.934340e-01	5.309653e-01
1  1.97778	2.881586e-01	5.391587e-01
6  1.81111	2.881586e-01	5.432672e-01
1  1.72416	2.881586e-01	5.492561e-01
1  -2.73397	3.173323e-01	5.039451e-01
2  -2.89849	3.173323e-01	4.951562e-01
5  -2.12824	3.173323e-01	4.790575e-01
1  -2.10332	3.193309e-01	4.759534e-01
1  -1.41199	3.193309e-01	4.693218e-01
1  -1.33565	3.140522e-01	4.775204e-01
2  0.154052	3.140522e-01	4.677004e-01
1  3.57567	3.140522e-01	4.516986e-01
1  3.42943	3.165540e-01	4.478130e-01
3  3.3158	3.165540e-01	4.482716e-01
1  3.51811	3.278470e-01	4.307319e-01
2  2.69226	3.278470e-01	4.343748e-01
1  -1.34949	3.278470e-01	4.607304e-01
1  -1.27538	3.284960e-01	4.597223e-01
1  -1.96632	3.284960e-01	4.740126e-01
1  -2.83548	3.175714e-01	4.909801e-01
2  -2.81571	3.175714e-01	4.902521e-01
1  -2.79631	3.175714e-01	4.896217e-01
1  -2.79416	3.176848e-01	4.894455e-01
1  -1.79075	3.176848e-01	4.750826e-01
1  -1.73599	3.145152e-01	4.800056e-01
1  -0.98102	3.145152e-01	4.740053e-01
3  -1.06038	3.182481e-01	4.682075e-01
1  -0.463773	3.182481e-01	4.641354e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 936 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000430 	for  Omega_m
           0.000009 	for  b1
--> Not computing covariance matrix
3  -0.357437	3.230920e-01	4.566122e-01
2  -2.38083	3.230920e-01	4.769846e-01
1  -2.58213	3.230920e-01	4.864337e-01
1  -2.24264	3.263666e-01	4.813478e-01
1  -1.1322	3.263666e-01	4.592644e-01
1  -1.46333	3.145050e-01	4.776872e-01
2  -1.53561	3.145050e-01	4.782845e-01
1  -0.946138	3.145050e-01	4.737776e-01
5  -0.0469155	3.053960e-01	4.879252e-01
1  -0.894534	3.053960e-01	4.940973e-01
2  -1.31657	3.087018e-01	4.889628e-01
1  -0.779528	3.312885e-01	4.538825e-01
2  -0.115466	3.312885e-01	4.476413e-01
1  -1.01923	3.312885e-01	4.567789e-01
1  -1.83895	3.109636e-01	4.883464e-01
2  -1.29663	3.109636e-01	4.835445e-01
3  -2.82233	3.109636e-01	5.070969e-01
2  -2.92476	3.146702e-01	5.013400e-01
4  -2.27575	3.048248e-01	5.166314e-01
2  -2.69495	3.214823e-01	4.907598e-01
1  -2.74956	3.206718e-01	4.920186e-01
1  -2.7422	3.206718e-01	4.926167e-01
2  -2.61336	3.224279e-01	4.898893e-01
1  -2.49946	3.236984e-01	4.879160e-01
4  -2.37005	3.236984e-01	4.922097e-01
1  -2.33302	3.236984e-01	4.760143e-01
4  -2.59666	3.141974e-01	4.907708e-01
1  -2.60814	3.146848e-01	4.900137e-01
5  -2.92431	3.146848e-01	5.003251e-01
4  -2.91309	3.167471e-01	4.971221e-01
1  -2.76498	3.205484e-01	4.912181e-01
2  -1.90055	3.205484e-01	5.080047e-01
1  -2.00893	3.205484e-01	4.734062e-01
2  -1.85657	3.234732e-01	4.688636e-01
3  -2.00204	3.207333e-01	4.731190e-01
1  -2.40226	3.207333e-01	4.784475e-01
1  -2.41031	3.129202e-01	4.905825e-01
2  -2.80697	3.129202e-01	5.098952e-01
1  -2.88014	3.129202e-01	5.066309e-01
3  -2.85992	3.121753e-01	5.077878e-01
2  -0.824638	3.121753e-01	5.327149e-01
3  -2.09606	3.121753e-01	5.223477e-01
4  -1.31089	3.018152e-01	5.384385e-01
1  1.35792	2.901533e-01	5.565512e-01
3  2.35919	2.901533e-01	5.676917e-01
2  1.72018	2.924188e-01	5.641730e-01
2  -0.55565	3.065746e-01	5.421870e-01
1  -0.640514	3.082088e-01	5.396488e-01
1  -2.54875	3.082088e-01	5.067871e-01
3  -2.67933	3.098237e-01	5.042790e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 961 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000399 	for  Omega_m
           0.000044 	for  b1
--> Not computing covariance matrix
1  -2.58571	3.098237e-01	5.016751e-01
1  -2.75308	3.191768e-01	4.871483e-01
5  -2.7704	3.191768e-01	4.877551e-01
1  -2.78222	3.188418e-01	4.882754e-01
1  -1.89471	3.188418e-01	4.743822e-01
3  -1.32519	3.075795e-01	4.918743e-01
4  -0.769714	3.075795e-01	4.874219e-01
1  -2.58628	3.075795e-01	5.141522e-01
1  -0.828758	2.967797e-01	5.309258e-01
1  -0.693371	2.967797e-01	5.409787e-01
1  -2.05868	3.050184e-01	5.281828e-01
2  -2.19831	3.050184e-01	5.249996e-01
1  -2.04032	3.050184e-01	5.083224e-01
2  -2.47495	3.089091e-01	5.022794e-01
1  -1.95891	3.044403e-01	5.092202e-01
1  -2.23921	3.044403e-01	5.196898e-01
1  -2.59883	3.077480e-01	5.145525e-01
1  -2.41822	3.077480e-01	5.052042e-01
4  -1.66708	3.022300e-01	5.137745e-01
2  -2.79685	3.180292e-01	4.892361e-01
1  -2.72591	3.200453e-01	4.861048e-01
1  -2.75764	3.200453e-01	4.874391e-01
1  -2.85384	3.169142e-01	4.923021e-01
1  -2.90526	3.169142e-01	4.982013e-01
6  -2.91881	3.140860e-01	5.025939e-01
2  -1.81555	3.292259e-01	4.790794e-01
1  -2.89788	3.172339e-01	4.977048e-01
1  -2.59935	3.172339e-01	4.856298e-01
2  -2.34381	3.232999e-01	4.762084e-01
1  -1.68579	3.294571e-01	4.666454e-01
1  -1.82919	3.294571e-01	4.759065e-01
2  -2.35116	3.254630e-01	4.821099e-01
2  -2.9144	3.160874e-01	4.966716e-01
1  -2.79291	3.200742e-01	4.904796e-01
1  -1.17214	3.200742e-01	5.153137e-01
1  -0.394611	3.263206e-01	5.056121e-01
3  -0.0168107	3.263206e-01	5.080754e-01
1  -0.316784	3.243360e-01	5.111577e-01
1  0.156259	3.243360e-01	5.140113e-01
1  -0.556231	3.179179e-01	5.239796e-01
2  -1.55036	3.179179e-01	5.170273e-01
1  -2.13456	3.179179e-01	5.115753e-01
1  -2.16274	3.091269e-01	5.252290e-01
1  -2.68453	3.091269e-01	5.142204e-01
1  -2.58047	3.216585e-01	4.947570e-01
1  -1.32775	3.216585e-01	5.104708e-01
2  -1.56156	3.190600e-01	5.145066e-01
3  -1.75875	3.154863e-01	5.200571e-01
1  -2.82638	3.154863e-01	5.055317e-01
1  -2.7422	3.105874e-01	5.131404e-01
1  -2.68154	3.105874e-01	5.150872e-01
1  -2.75865	3.135693e-01	5.104558e-01
1  -2.62989	3.135693e-01	5.131239e-01
4  -2.61802	3.124439e-01	5.148718e-01
1  -2.62399	3.149268e-01	5.110156e-01
2  -2.87151	3.149268e-01	5.049804e-01
4  -2.08135	3.149268e-01	4.826173e-01
1  -2.86023	3.149268e-01	4.955171e-01
2  -2.86439	3.156764e-01	4.943528e-01
1  -2.84738	3.174947e-01	4.915286e-01
1  -2.38552	3.174947e-01	5.094822e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 991 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000612 	for  Omega_m
           0.000056 	for  b1
--> Not computing covariance matrix
2  -2.42826	3.107526e-01	5.199538e-01
1  -2.46171	3.120067e-01	5.180059e-01
1  -2.46194	3.120067e-01	4.934129e-01
1  -2.30203	3.236293e-01	4.753613e-01
1  -2.39852	3.236293e-01	4.775433e-01
1  -2.65277	3.191769e-01	4.844586e-01
1  -2.77452	3.191769e-01	4.879108e-01
2  -1.84964	3.292843e-01	4.722124e-01
1  -2.72372	3.203359e-01	4.861107e-01
3  -2.76279	3.203359e-01	4.931549e-01
2  -2.06727	3.274282e-01	4.821396e-01
2  -1.48925	3.311937e-01	4.762911e-01
1  -2.92323	3.149408e-01	5.015343e-01
2  -2.23562	3.149408e-01	5.163361e-01
1  -2.91771	3.149408e-01	5.022465e-01
1  -2.90966	3.161410e-01	5.003824e-01
1  -2.61496	3.161410e-01	5.088803e-01
2  -2.60663	3.114166e-01	5.162180e-01
3  -2.55561	3.100919e-01	5.182755e-01
1  -1.21222	3.100919e-01	5.331141e-01
1  -1.13369	3.079639e-01	5.364192e-01
5  0.118794	3.079639e-01	5.446148e-01
1  0.0670386	3.112490e-01	5.395125e-01
1  0.189365	3.112490e-01	5.401761e-01
1  0.196803	3.119601e-01	5.390717e-01
1  0.0194534	3.119601e-01	5.381115e-01
1  0.125492	3.151933e-01	5.330899e-01
1  1.26092	3.151933e-01	5.386526e-01
1  2.16337	3.234579e-01	5.258164e-01
1  1.92549	3.234579e-01	5.247938e-01
2  1.09665	3.160856e-01	5.362440e-01
1  2.10901	3.246124e-01	5.230007e-01
1  1.01738	3.246124e-01	5.179515e-01
2  0.278831	3.035048e-01	5.507346e-01
2  0.271451	3.035812e-01	5.506161e-01
1  0.212761	3.179049e-01	5.283692e-01
1  -2.83583	3.179049e-01	4.993491e-01
1  -0.126031	3.374374e-01	4.690123e-01
3  -0.0632322	3.374374e-01	4.701517e-01
2  -0.48004	3.355943e-01	4.730143e-01
1  -2.34573	3.242077e-01	4.906994e-01
1  -2.00325	3.242077e-01	4.968256e-01
1  -2.45529	3.086975e-01	5.209153e-01
1  -2.57324	3.086975e-01	5.054526e-01
2  -2.50544	3.079476e-01	5.066172e-01
2  -2.566	3.230901e-01	4.830987e-01
3  -0.310397	3.376739e-01	4.604479e-01
1  0.584467	3.376739e-01	4.410352e-01
3  -0.609443	3.304235e-01	4.522962e-01
1  -1.39705	3.304235e-01	4.826883e-01
1  -1.18047	3.316408e-01	4.807977e-01
3  -1.28136	3.316408e-01	4.789203e-01
1  -0.0502319	3.375505e-01	4.697417e-01
2  -0.243445	3.375505e-01	4.654551e-01
1  0.667047	3.375505e-01	4.401633e-01
1  0.478677	3.365631e-01	4.416968e-01
1  0.551117	3.365631e-01	4.410148e-01
1  -0.770226	3.272941e-01	4.554110e-01
1  -1.59285	3.272941e-01	4.920636e-01
3  -1.67188	3.267500e-01	4.929086e-01
5  -1.27662	3.267500e-01	4.604162e-01
1  -1.54295	3.234364e-01	4.655627e-01
1  -2.00379	3.234364e-01	4.707111e-01
1  -1.37212	3.296523e-01	4.610568e-01
2  -1.39788	3.296523e-01	4.614401e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1024 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000200 	for  Omega_m
           0.000045 	for  b1
--> Not computing covariance matrix
1  -1.75759	3.296523e-01	4.694455e-01
1  -1.51087	3.312776e-01	4.669213e-01
1  -0.823578	3.312776e-01	4.543765e-01
1  -1.1487	3.068068e-01	4.923832e-01
1  -0.239688	3.068068e-01	4.856374e-01
1  -0.812409	3.123646e-01	4.770053e-01
1  -1.00696	3.123646e-01	4.783794e-01
2  -0.446605	3.068330e-01	4.869709e-01
2  -1.09707	3.139203e-01	4.759633e-01
1  -1.11246	3.142496e-01	4.754517e-01
2  -2.62945	3.142496e-01	4.912413e-01
1  -2.09329	3.142496e-01	4.840191e-01
1  -2.11765	3.150751e-01	4.827369e-01
3  -2.2217	3.150751e-01	4.839090e-01
1  -2.09765	3.120550e-01	4.885998e-01
1  -2.14778	3.120550e-01	4.891686e-01
2  -2.22281	3.135775e-01	4.868039e-01
1  -2.25967	3.146728e-01	4.851027e-01
1  -2.52496	3.146728e-01	4.886810e-01
1  -2.34603	3.107744e-01	4.947358e-01
1  -2.80999	3.107744e-01	5.068494e-01
3  -2.71441	3.212842e-01	4.905261e-01
2  -2.66914	3.212842e-01	4.933162e-01
1  -2.59825	3.212842e-01	4.956548e-01
1  -1.95048	3.272748e-01	4.863506e-01
1  -2.05688	3.272748e-01	4.835348e-01
1  -2.84537	3.183225e-01	4.974390e-01
2  -2.84152	3.183225e-01	4.976582e-01
1  -2.13035	3.183225e-01	4.776196e-01
1  -1.97911	3.225412e-01	4.710674e-01
1  -1.55005	3.225412e-01	4.665229e-01
1  -1.66316	3.160253e-01	4.766431e-01
2  -2.75537	3.160253e-01	5.063330e-01
3  -1.79989	3.160253e-01	5.186805e-01
1  -1.41898	3.214148e-01	5.103097e-01
1  -2.4144	3.214148e-01	4.991347e-01
1  -2.7176	3.131604e-01	5.119550e-01
1  -1.86316	3.131604e-01	5.231550e-01
1  -0.759405	3.265408e-01	5.023733e-01
1  -1.63467	3.265408e-01	4.940762e-01
1  -2.55529	3.150571e-01	5.119120e-01
1  -2.89978	3.150571e-01	4.970841e-01
1  -2.86515	3.130911e-01	5.001376e-01
1  -2.35949	3.130911e-01	5.179051e-01
1  -2.26325	3.174083e-01	5.111999e-01
1  -2.89664	3.174083e-01	4.950200e-01
2  -2.36263	3.253405e-01	4.827000e-01
2  -2.88362	3.179033e-01	4.942511e-01
1  -2.75007	3.208350e-01	4.896978e-01
2  -2.74992	3.208350e-01	4.895175e-01
4  -0.733678	3.208350e-01	4.621008e-01
1  -2.03836	3.208350e-01	4.734209e-01
2  -2.08282	3.194658e-01	4.755474e-01
1  -1.69231	3.088280e-01	4.920696e-01
2  -1.9586	3.088280e-01	4.948947e-01
1  -0.0465247	3.088280e-01	4.796396e-01
1  -0.468934	3.234538e-01	4.569235e-01
2  -2.54897	3.234538e-01	4.839239e-01
1  -2.26029	3.234538e-01	4.745905e-01
2  -2.5142	3.158466e-01	4.864056e-01
1  -2.39447	3.213456e-01	4.778647e-01
3  -2.71573	3.213456e-01	4.895426e-01
1  -2.90275	3.172411e-01	4.959176e-01
1  -2.75846	3.172411e-01	5.035702e-01
1  -2.80376	3.151021e-01	5.068924e-01
3  -2.90045	3.151021e-01	4.970384e-01
1  -2.80585	3.196498e-01	4.899752e-01
1  -2.09468	3.196498e-01	4.754521e-01
1  -1.17418	3.046195e-01	4.987963e-01
1  -0.5662	3.046195e-01	4.936613e-01
3  -0.989973	3.076116e-01	4.890141e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1059 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000156 	for  Omega_m
           0.000059 	for  b1
--> Not computing covariance matrix
1  -2.53248	3.076116e-01	5.091402e-01
1  -2.49375	3.072215e-01	5.097461e-01
1  -1.49106	3.072215e-01	4.943466e-01
2  -1.68743	3.090013e-01	4.915823e-01
1  -1.99501	3.214046e-01	4.723182e-01
1  -2.71011	3.214046e-01	4.897793e-01
3  -2.75428	3.099103e-01	5.076315e-01
1  -2.75978	3.099103e-01	5.109244e-01
1  -2.76343	3.099715e-01	5.108294e-01
1  -2.7134	3.099715e-01	5.049444e-01
1  -2.89757	3.148437e-01	4.973772e-01
1  -2.43779	3.148437e-01	4.870818e-01
2  -2.27332	3.111386e-01	4.928363e-01
4  -2.15899	3.241037e-01	4.726997e-01
2  -1.95044	3.263631e-01	4.691905e-01
2  -1.85362	3.272558e-01	4.678040e-01
2  -2.37383	3.206495e-01	4.780646e-01
2  -2.20482	3.235120e-01	4.736186e-01
1  -1.48843	3.301258e-01	4.633465e-01
2  -0.970535	3.301258e-01	4.895272e-01
1  -1.60975	3.301258e-01	4.797148e-01
1  -2.90209	3.154891e-01	5.024477e-01
1  -2.91306	3.154891e-01	5.016682e-01
3  -1.84611	3.018170e-01	5.229030e-01
1  -1.62246	3.018170e-01	5.335179e-01
3  -2.1107	3.057050e-01	5.274793e-01
1  -1.98653	3.057050e-01	5.295079e-01
1  -2.17244	3.079845e-01	5.259675e-01
1  -2.49963	3.079845e-01	5.198347e-01
1  -2.72735	3.148394e-01	5.091880e-01
1  -1.51858	3.148394e-01	5.232331e-01
3  -1.52526	3.146096e-01	5.235900e-01
1  -1.0995	3.146096e-01	5.267497e-01
3  -1.00815	3.166451e-01	5.235883e-01
1  -2.88586	3.166451e-01	4.940810e-01
3  -2.86598	3.135344e-01	4.989124e-01
1  -1.92529	3.135344e-01	5.219633e-01
1  -0.948276	3.258019e-01	5.029100e-01
1  -0.398501	3.258019e-01	5.069375e-01
2  -1.4237	3.148792e-01	5.239021e-01
1  -1.3079	3.173631e-01	5.200443e-01
1  -2.54537	3.173631e-01	5.074530e-01
3  -2.60645	3.152438e-01	5.107446e-01
1  -2.90224	3.152438e-01	5.029138e-01
2  -2.80784	3.108405e-01	5.097527e-01
2  -2.89151	3.162450e-01	5.013587e-01
3  -2.32526	3.249339e-01	4.878637e-01
1  -1.53296	3.249339e-01	4.642156e-01
1  -1.79586	3.150398e-01	4.795825e-01
1  -2.78317	3.150398e-01	4.929553e-01
2  -2.52975	3.228377e-01	4.808441e-01
2  -2.33727	3.250469e-01	4.774128e-01
2  -2.36867	3.076819e-01	5.043833e-01
1  -2.32467	3.072621e-01	5.050353e-01
1  -1.91356	3.072621e-01	4.987692e-01
2  -1.8981	3.071293e-01	4.989754e-01
1  -2.23919	3.229552e-01	4.743955e-01
1  -0.466905	3.229552e-01	4.575139e-01
2  0.240916	3.309545e-01	4.450897e-01
1  -0.462821	3.230404e-01	4.573814e-01
2  -1.71365	3.230404e-01	4.676508e-01
2  -0.636561	3.230404e-01	5.122105e-01
2  1.15809	3.230404e-01	5.222246e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1091 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000236 	for  Omega_m
           0.000046 	for  b1
--> Not computing covariance matrix
1  -0.849037	3.230404e-01	4.601248e-01
2  -0.0559602	3.314305e-01	4.470938e-01
1  -0.41371	3.284933e-01	4.516556e-01
1  -1.81702	3.284933e-01	4.682136e-01
1  -2.06931	3.263499e-01	4.715426e-01
2  -1.86153	3.263499e-01	4.677187e-01
3  -2.07236	3.263499e-01	4.716118e-01
2  -1.94756	3.274583e-01	4.698904e-01
1  -2.33995	3.234400e-01	4.761314e-01
1  -2.55258	3.234400e-01	4.844878e-01
2  -2.31714	3.257830e-01	4.808487e-01
3  -2.87813	3.132765e-01	5.002732e-01
2  -2.80091	3.132765e-01	4.972191e-01
1  -2.90166	3.132765e-01	5.047002e-01
1  -2.75932	3.098309e-01	5.100516e-01
1  -2.72297	3.098309e-01	5.134225e-01
2  -2.66118	3.088634e-01	5.149252e-01
1  -2.6851	3.200457e-01	4.975574e-01
5  -0.20049	3.200457e-01	4.597422e-01
2  -0.185436	3.208823e-01	4.584428e-01
3  -0.200999	3.176640e-01	4.634414e-01
1  -2.08984	3.176640e-01	4.781291e-01
1  -2.0851	3.182678e-01	4.771913e-01
4  -2.84788	3.182678e-01	4.975018e-01
1  -2.81759	3.182678e-01	4.898510e-01
2  -2.77505	3.194907e-01	4.879516e-01
1  -2.47865	3.239751e-01	4.809867e-01
1  -2.43871	3.239751e-01	4.889650e-01
1  -2.82486	3.186831e-01	4.971842e-01
2  -2.40683	3.186831e-01	4.806567e-01
5  -2.51861	3.186831e-01	5.048096e-01
2  -2.07649	3.239388e-01	4.966468e-01
1  -2.64522	3.149136e-01	5.106642e-01
1  -2.41919	3.149136e-01	4.866945e-01
1  -2.08813	3.247505e-01	4.714163e-01
1  -2.40725	3.247505e-01	4.798886e-01
5  -2.82611	3.180460e-01	4.903017e-01
1  -2.23626	3.180460e-01	5.101435e-01
1  -2.33034	3.109857e-01	5.211091e-01
1  -2.81528	3.109857e-01	5.058006e-01
1  -2.83082	3.112981e-01	5.053154e-01
1  -2.79663	3.112981e-01	5.030873e-01
2  -2.6994	3.096993e-01	5.055704e-01
6  -2.84055	3.122755e-01	5.015692e-01
1  -2.76902	3.107875e-01	5.038802e-01
1  -2.81368	3.107875e-01	5.084973e-01
1  -2.58996	3.076202e-01	5.134166e-01
2  -1.87966	3.076202e-01	5.299131e-01
1  -2.58973	3.076202e-01	5.133061e-01
3  -2.85454	3.116812e-01	5.069988e-01
3  -2.79916	3.116812e-01	5.017818e-01
3  -2.7745	3.201551e-01	4.886206e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1116 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000132 	for  Omega_m
           0.000062 	for  b1
--> Not computing covariance matrix
6  -1.69034	3.201551e-01	4.706394e-01
1  -2.32276	3.201551e-01	4.777757e-01
1  -2.38156	3.174345e-01	4.820011e-01
1  -1.71052	3.174345e-01	4.747369e-01
1  -1.71086	3.176367e-01	4.744229e-01
1  -1.58656	3.176367e-01	4.733271e-01
1  -1.37371	3.240168e-01	4.634179e-01
2  -2.35068	3.240168e-01	4.765401e-01
1  -2.35058	3.240168e-01	4.913845e-01
1  -2.82494	3.169738e-01	5.023232e-01
2  -2.4712	3.169738e-01	4.839538e-01
1  -1.68874	3.169738e-01	5.177961e-01
1  -1.79861	3.134809e-01	5.232210e-01
3  -1.64085	3.134809e-01	5.245867e-01
1  -1.4602	3.180224e-01	5.175332e-01
1  -2.67985	3.180224e-01	5.034670e-01
1  -1.65334	3.282907e-01	4.875188e-01
3  -1.89078	3.282907e-01	4.697805e-01
1  -2.16655	3.259169e-01	4.734673e-01
1  -2.30109	3.259169e-01	4.811203e-01
3  -2.11877	3.274077e-01	4.788048e-01
1  -2.05771	3.274077e-01	4.826618e-01
2  -1.85113	3.288563e-01	4.804121e-01
1  -1.78314	3.293035e-01	4.797174e-01
1  0.727832	3.293035e-01	5.047310e-01
1  -0.363911	3.224185e-01	5.154244e-01
1  -2.10735	3.224185e-01	5.007827e-01
1  -1.97965	3.041661e-01	5.291313e-01
1  -2.13959	3.041661e-01	5.248848e-01
1  -1.90664	3.265846e-01	4.900656e-01
2  -2.2236	3.265846e-01	4.791030e-01
1  -2.21267	3.265846e-01	4.773168e-01
1  -0.790905	3.354221e-01	4.635909e-01
5  -0.662954	3.354221e-01	4.564914e-01
2  -1.57303	3.299934e-01	4.649231e-01
1  -2.30677	3.231862e-01	4.754955e-01
1  -2.57193	3.231862e-01	4.843259e-01
2  -2.51182	3.238668e-01	4.832690e-01
3  -2.8774	3.175191e-01	4.931278e-01
1  -2.79749	3.175191e-01	5.018035e-01
2  -2.76534	3.107863e-01	5.122607e-01
1  -2.55795	3.216523e-01	4.953842e-01
1  -2.6864	3.216523e-01	4.901540e-01
1  -2.92327	3.159296e-01	4.990422e-01
2  -2.24482	3.159296e-01	4.826717e-01
1  -1.55319	3.159296e-01	4.758642e-01
1  -1.3529	3.241398e-01	4.631125e-01
1  -1.8875	3.241398e-01	4.687832e-01
1  -2.15432	3.175285e-01	4.790516e-01
1  -2.89406	3.175285e-01	4.966148e-01
1  -2.62398	3.224499e-01	4.889710e-01
2  -1.53118	3.224499e-01	4.664429e-01
1  -2.53615	3.224499e-01	4.928897e-01
2  -2.26038	3.046433e-01	5.205460e-01
2  -2.84953	3.123781e-01	5.085326e-01
1  -2.82851	3.117154e-01	5.095619e-01
2  -2.83554	3.117154e-01	5.091328e-01
2  -2.44923	3.117154e-01	5.185549e-01
2  -2.12064	3.117154e-01	5.227298e-01
1  -2.67096	3.117154e-01	5.145977e-01
3  -2.34364	3.064057e-01	5.228444e-01
2  -2.36182	3.064057e-01	5.223370e-01
2  -2.43279	3.064057e-01	5.121489e-01
1  -0.843412	3.064057e-01	4.909667e-01
1  -1.60854	3.181677e-01	4.726986e-01
1  -1.60072	3.181677e-01	4.726305e-01
2  -1.14013	3.269895e-01	4.589290e-01
1  -1.29754	3.105621e-01	4.844430e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1151 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000087 	for  Omega_m
           0.000028 	for  b1
--> Not computing covariance matrix
1  -2.56318	3.105621e-01	4.989211e-01
1  -1.47032	3.315066e-01	4.663913e-01
1  -0.969351	3.315066e-01	4.562054e-01
3  -1.26825	3.293359e-01	4.595768e-01
2  -1.66665	3.293359e-01	4.659983e-01
1  -1.51223	3.293359e-01	4.855044e-01
1  -1.53897	3.291712e-01	4.857602e-01
2  -1.21495	3.291712e-01	4.589232e-01
1  -1.73822	3.291712e-01	4.674255e-01
2  -2.59409	3.142992e-01	4.905238e-01
4  -2.47074	3.114074e-01	4.950153e-01
2  -0.982098	3.001473e-01	5.125039e-01
2  -2.05159	3.067188e-01	5.022974e-01
1  -0.97228	3.339977e-01	4.599292e-01
1  0.226424	3.339977e-01	4.874323e-01
2  -0.846323	3.285190e-01	4.959414e-01
3  -1.84649	3.208070e-01	5.079194e-01
1  -2.12828	3.208070e-01	5.048620e-01
1  -2.01975	3.220065e-01	5.029990e-01
3  -1.53818	3.220065e-01	5.078536e-01
1  -1.97612	3.157372e-01	5.175908e-01
1  -1.91711	3.157372e-01	5.181544e-01
2  -1.61151	3.205970e-01	5.106064e-01
1  -1.81108	3.179527e-01	5.147134e-01
3  -2.71979	3.179527e-01	5.027506e-01
2  -2.78993	3.132749e-01	5.100160e-01
1  -2.7965	3.144494e-01	5.081918e-01
1  -2.87377	3.144494e-01	5.056380e-01
2  -2.83493	3.120900e-01	5.093025e-01
3  -2.87299	3.150607e-01	5.046885e-01
1  -1.90762	3.150607e-01	4.806042e-01
1  -1.40859	3.273133e-01	4.615742e-01
1  -1.18541	3.273133e-01	4.591897e-01
1  -1.47445	3.239273e-01	4.644486e-01
1  -2.09512	3.239273e-01	4.964118e-01
1  -2.47067	3.197265e-01	5.029362e-01
2  -2.76155	3.197265e-01	4.874378e-01
1  -2.13972	3.197265e-01	5.074044e-01
1  -2.37503	3.133719e-01	5.172741e-01
1  -2.90313	3.133719e-01	5.046114e-01
1  -2.85746	3.182159e-01	4.970880e-01
1  -1.71877	3.182159e-01	4.736098e-01
2  -1.60487	3.222325e-01	4.673714e-01
2  -1.70135	3.158463e-01	4.772902e-01
2  -1.71496	3.166943e-01	4.759731e-01
2  -1.6176	3.134501e-01	4.810118e-01
1  -1.67834	3.204152e-01	4.701939e-01
1  -2.55664	3.204152e-01	4.814999e-01
1  -2.45338	3.222848e-01	4.785961e-01
1  -2.63687	3.222848e-01	4.849856e-01
8  -2.81978	3.123445e-01	5.004243e-01
2  -2.88145	3.148756e-01	4.964932e-01
1  -2.83782	3.185365e-01	4.908073e-01
1  -2.80681	3.185365e-01	4.985205e-01
2  -2.87248	3.129973e-01	5.071236e-01
1  -2.52215	3.227694e-01	4.919461e-01
2  -1.60583	3.227694e-01	5.053045e-01
1  1.87829	3.227694e-01	5.261056e-01
1  1.54321	3.202353e-01	5.300413e-01
1  -0.655633	3.202353e-01	5.184976e-01
1  -0.74501	3.192734e-01	5.199916e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1181 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000122 	for  Omega_m
           0.000078 	for  b1
--> Not computing covariance matrix
5  -2.64181	3.192734e-01	4.841357e-01
2  -2.66736	3.183790e-01	4.855248e-01
1  -2.69172	3.163859e-01	4.886203e-01
1  -2.88692	3.163859e-01	5.012568e-01
1  -2.87263	3.170329e-01	5.002520e-01
2  -2.80026	3.170329e-01	5.029431e-01
2  -2.42836	3.170329e-01	5.098903e-01
1  -2.70811	3.170329e-01	5.052159e-01
1  -2.74671	3.154038e-01	5.077461e-01
1  -2.16217	3.154038e-01	5.163092e-01
1  -2.01996	3.185308e-01	5.114526e-01
1  -2.07479	3.185308e-01	4.767060e-01
1  -2.04294	3.146250e-01	4.827722e-01
1  -2.03342	3.146250e-01	5.190532e-01
1  -2.02622	3.149453e-01	5.185558e-01
2  -2.82429	3.149453e-01	5.065827e-01
1  -2.84231	3.149453e-01	4.948475e-01
1  -2.74389	3.201015e-01	4.868391e-01
1  -2.78781	3.201015e-01	4.924200e-01
1  -2.92191	3.160958e-01	4.986415e-01
1  -2.89791	3.160958e-01	4.953594e-01
2  -1.61245	3.308997e-01	4.723667e-01
1  -2.74274	3.104522e-01	5.041248e-01
1  -2.47427	3.104522e-01	5.195024e-01
2  -2.50134	3.161690e-01	5.106232e-01
1  -2.3543	3.082154e-01	5.229764e-01
2  -2.50141	3.082154e-01	5.054027e-01
2  -2.62671	3.082154e-01	5.102934e-01
1  -2.6151	3.082154e-01	5.095072e-01
1  -2.72334	3.212496e-01	4.892633e-01
1  -2.71887	3.212496e-01	4.903144e-01
1  -2.73662	3.209834e-01	4.907278e-01
1  -2.21809	3.209834e-01	5.032787e-01
3  -2.1926	3.212817e-01	5.028154e-01
1  -2.63605	3.212817e-01	4.945419e-01
1  -2.23109	3.254570e-01	4.880570e-01
1  -2.15274	3.254570e-01	4.727566e-01
1  -0.518872	3.362907e-01	4.559304e-01
3  0.576849	3.362907e-01	4.407480e-01
2  -0.0227351	3.326762e-01	4.463618e-01
1  -0.316875	3.305632e-01	4.496435e-01
1  -1.60954	3.305632e-01	4.767546e-01
3  -2.91296	3.165945e-01	4.984501e-01
3  -2.19605	3.165945e-01	5.136467e-01
2  -2.26149	3.125681e-01	5.199004e-01
1  -2.18104	3.169516e-01	5.130922e-01
1  -2.39701	3.169516e-01	4.829373e-01
1  -2.39388	3.161193e-01	4.842298e-01
2  -2.23907	3.161193e-01	4.822815e-01
1  -2.84764	3.161193e-01	4.930575e-01
1  -2.45429	3.077520e-01	5.060531e-01
1  -1.53134	3.077520e-01	4.933073e-01
1  -1.95442	3.218577e-01	4.713992e-01
2  -2.67145	3.218577e-01	4.898064e-01
1  -2.50263	3.218577e-01	4.797557e-01
1  -2.4247	3.230104e-01	4.779653e-01
2  -2.369	3.230104e-01	4.767377e-01
2  -1.79046	3.230104e-01	5.028318e-01
1  -2.58986	3.230104e-01	4.863585e-01
2  -2.92088	3.154070e-01	4.981678e-01
2  -2.78454	3.202472e-01	4.906502e-01
7  -2.92081	3.154829e-01	4.980498e-01
3  -2.82167	3.154829e-01	5.056793e-01
2  -2.64777	3.200195e-01	4.986333e-01
1  -2.43611	3.227105e-01	4.944538e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1214 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000046 	for  Omega_m
           0.000145 	for  b1
--> Not computing covariance matrix
2  -1.69878	3.227105e-01	4.678093e-01
2  -0.926379	3.227105e-01	4.610945e-01
1  -2.60356	3.227105e-01	4.884575e-01
1  -1.98158	3.282066e-01	4.799213e-01
4  -1.79152	3.282066e-01	4.672940e-01
1  -1.84238	3.282066e-01	4.843331e-01
3  -2.86863	3.154531e-01	5.041410e-01
2  -2.91686	3.154531e-01	4.976479e-01
2  -1.9423	3.154531e-01	5.184465e-01
1  -2.91353	3.154531e-01	4.973432e-01
1  -2.90971	3.146563e-01	4.985808e-01
3  -2.13532	3.146563e-01	4.837047e-01
3  -1.86345	3.246381e-01	4.682016e-01
1  -2.39076	3.246381e-01	4.786207e-01
1  -1.48834	3.315653e-01	4.678618e-01
1  -0.672271	3.315653e-01	4.527188e-01
1  -0.369875	3.335329e-01	4.496629e-01
1  -0.730097	3.335329e-01	4.541962e-01
1  -0.0311727	3.372946e-01	4.483537e-01
1  -0.345225	3.372946e-01	4.555954e-01
1  -2.27175	3.247634e-01	4.750582e-01
1  -2.15488	3.247634e-01	4.725876e-01
2  -2.49096	3.189219e-01	4.816604e-01
1  -2.40443	3.122155e-01	4.920763e-01
1  -2.812	3.122155e-01	5.102598e-01
1  -2.84302	3.142680e-01	5.070720e-01
2  -2.91453	3.142680e-01	5.000271e-01
1  -2.62819	3.142680e-01	4.911819e-01
1  -2.24164	3.250087e-01	4.745001e-01
5  -2.19864	3.250087e-01	4.735221e-01
2  -2.43929	3.218591e-01	4.784138e-01
1  -2.53975	3.197805e-01	4.816422e-01
1  -2.68613	3.197805e-01	4.849012e-01
1  -1.45304	3.015370e-01	5.132360e-01
4  -0.671412	3.015370e-01	5.039404e-01
6  -1.23426	3.015370e-01	5.100468e-01
1  -1.26731	3.015370e-01	5.104837e-01
3  -2.52063	3.121522e-01	4.939968e-01
3  -2.82601	3.121522e-01	5.013081e-01
2  -2.71083	3.100251e-01	5.046117e-01
5  -0.880588	2.976726e-01	5.237970e-01
2  -0.491925	2.976726e-01	5.171969e-01
1  -0.767815	2.976726e-01	5.420660e-01
1  0.482314	2.925713e-01	5.499891e-01
2  0.270472	2.925713e-01	5.410967e-01
1  0.384035	2.925713e-01	5.344705e-01
1  -2.26879	3.049074e-01	5.153107e-01
1  -2.09116	3.049074e-01	5.098144e-01
1  -2.67615	3.210954e-01	4.846721e-01
2  -2.31311	3.210954e-01	4.767540e-01
1  -2.47587	3.210954e-01	4.794883e-01
2  -2.04316	3.265036e-01	4.710885e-01
2  -2.58668	3.153978e-01	4.883376e-01
1  -2.57344	3.184217e-01	4.836409e-01
2  -2.5793	3.184217e-01	5.044208e-01
2  -2.86139	3.184217e-01	4.957345e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1241 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000160 	for  Omega_m
           0.000320 	for  b1
--> Not computing covariance matrix
1  -2.74969	3.184217e-01	4.874930e-01
1  -2.76892	3.175382e-01	4.888653e-01
1  -2.74657	3.175382e-01	5.031440e-01
2  -1.68516	3.285013e-01	4.861166e-01
1  -2.63018	3.198600e-01	4.995378e-01
4  -2.67396	3.198600e-01	4.984687e-01
1  -1.61717	3.198600e-01	4.703568e-01
1  -1.23633	3.263668e-01	4.602507e-01
1  -1.41744	3.263668e-01	4.620934e-01
1  -1.77455	3.210518e-01	4.703484e-01
1  -2.70679	3.210518e-01	4.860545e-01
1  -2.69826	3.211932e-01	4.858349e-01
1  -2.38827	3.211932e-01	4.778647e-01
1  -2.13478	3.088157e-01	4.970889e-01
2  -2.17279	3.088157e-01	4.975980e-01
1  -1.8304	3.088157e-01	5.293239e-01
1  -1.26419	3.025237e-01	5.390962e-01
1  -0.835083	3.025237e-01	5.433954e-01
1  -1.13629	3.053653e-01	5.389820e-01
2  -2.35467	3.053653e-01	5.177886e-01
1  -2.10243	3.053653e-01	5.080783e-01
2  -2.75108	3.133766e-01	4.956355e-01
1  -2.57254	3.099566e-01	5.009472e-01
5  -1.73567	3.099566e-01	4.897001e-01
1  -1.8411	3.112841e-01	4.876382e-01
1  0.0598945	3.112841e-01	4.736920e-01
1  -0.205673	3.155744e-01	4.670286e-01
1  1.53483	3.155744e-01	4.577785e-01
2  2.7231	3.048780e-01	4.743916e-01
4  2.62664	3.054306e-01	4.735333e-01
1  2.53063	3.060047e-01	4.726416e-01
1  -2.06262	3.060047e-01	5.049208e-01
1  -2.69705	3.170539e-01	4.877598e-01
1  -2.88004	3.170539e-01	4.997863e-01
1  -2.81918	3.110182e-01	5.091605e-01
3  -2.08955	3.110182e-01	4.908807e-01
1  -2.2933	3.180510e-01	4.799577e-01
1  -2.86529	3.180510e-01	4.924062e-01
1  -2.86908	3.132487e-01	4.998649e-01
2  -1.08052	3.132487e-01	4.771439e-01
1  -2.21648	3.132487e-01	4.874032e-01
1  -1.60339	3.062185e-01	4.983221e-01
1  -2.44372	3.062185e-01	5.179883e-01
2  -2.69259	3.090777e-01	5.135475e-01
1  -1.86991	3.281622e-01	4.839064e-01
1  -0.200964	3.281622e-01	5.019809e-01
1  -0.574443	3.258720e-01	5.055380e-01
2  -1.20368	3.258720e-01	5.005562e-01
2  -1.78615	3.258720e-01	4.943631e-01
2  -2.28219	3.258720e-01	4.836463e-01
1  -1.6025	3.258720e-01	4.644077e-01
3  -0.208127	3.002376e-01	5.042216e-01
1  0.109728	3.002376e-01	5.016587e-01
1  -0.0917262	3.011859e-01	5.001859e-01
2  -1.01927	3.011859e-01	5.418127e-01
1  -1.6917	3.011859e-01	5.209797e-01
1  -1.72631	3.013797e-01	5.206787e-01
1  -1.75909	3.013797e-01	5.224372e-01
2  -2.91246	3.136652e-01	5.033561e-01
2  -2.31865	3.254396e-01	4.850687e-01
4  -0.735341	3.351789e-01	4.699421e-01
2  -2.09654	3.272370e-01	4.822770e-01
2  -1.63238	3.303673e-01	4.774153e-01
1  -1.66443	3.301702e-01	4.777213e-01
1  -1.62663	3.301702e-01	4.789680e-01
1  -1.5322	3.307381e-01	4.780860e-01
1  -1.63774	3.307381e-01	4.708298e-01
1  -1.77657	3.298386e-01	4.722269e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1276 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000142 	for  Omega_m
           0.000520 	for  b1
--> Not computing covariance matrix
3  -1.71772	3.298386e-01	4.686337e-01
1  -2.63733	3.121516e-01	4.961042e-01
2  -2.79046	3.121516e-01	4.999482e-01
2  -2.64195	3.121516e-01	4.961970e-01
3  -2.6645	3.121516e-01	4.966649e-01
2  -2.73873	3.179956e-01	4.875884e-01
1  -2.75656	3.155836e-01	4.913346e-01
1  -2.84465	3.155836e-01	4.937864e-01
1  -2.19345	3.054918e-01	5.094604e-01
2  -1.87074	3.054918e-01	5.038536e-01
1  -2.36849	3.054918e-01	5.169683e-01
1  -2.38297	3.246789e-01	4.871679e-01
2  -2.4278	3.246789e-01	4.844556e-01
1  -2.17058	3.246789e-01	4.926064e-01
3  -2.1321	3.040268e-01	5.246820e-01
1  -2.17353	3.040268e-01	5.182816e-01
2  -1.74738	3.013165e-01	5.224912e-01
1  -2.82933	3.110900e-01	5.073115e-01
1  -2.76491	3.110900e-01	5.025366e-01
2  -2.83337	3.187447e-01	4.906478e-01
4  -2.69827	3.214299e-01	4.864773e-01
2  -2.70975	3.212508e-01	4.867555e-01
3  -2.88501	3.148809e-01	4.966489e-01
2  -2.48789	3.148809e-01	5.132349e-01
1  -2.39057	3.148809e-01	5.145618e-01
1  -2.39465	3.122657e-01	5.186235e-01
1  -2.86537	3.122657e-01	5.074283e-01
1  -2.47468	3.235370e-01	4.899224e-01
3  -2.39667	3.235370e-01	4.922127e-01
1  -2.79332	3.178509e-01	5.010439e-01
1  -2.45079	3.178509e-01	5.077964e-01
2  -2.22626	3.064551e-01	5.254958e-01
1  -0.455989	2.956832e-01	5.422262e-01
2  -0.0989184	2.956832e-01	5.218439e-01
3  -0.222651	2.956832e-01	5.237330e-01
1  -1.01066	2.989358e-01	5.186812e-01
1  -0.883277	2.989358e-01	5.166210e-01
1  -1.86951	3.042786e-01	5.083229e-01
1  -2.0018	3.042786e-01	5.107753e-01
1  -2.39188	3.247453e-01	4.789875e-01
1  -1.8018	3.247453e-01	4.673708e-01
1  -2.11255	3.171166e-01	4.792192e-01
3  -2.8266	3.171166e-01	4.910737e-01
1  -1.31174	3.326522e-01	4.669447e-01
1  -1.03628	3.326522e-01	4.784293e-01
1  0.334679	3.388705e-01	4.687713e-01
1  0.152382	3.388705e-01	4.655173e-01
5  -1.55679	3.305792e-01	4.783950e-01
1  -1.65702	3.305792e-01	4.738848e-01
1  -1.05051	3.339988e-01	4.685735e-01
1  0.0182969	3.339988e-01	4.457914e-01
1  -0.887305	3.270478e-01	4.565874e-01
1  -2.00462	3.270478e-01	4.861830e-01
2  -2.27133	3.249175e-01	4.894915e-01
1  -1.71489	3.290319e-01	4.831014e-01
3  -1.87532	3.290319e-01	4.718977e-01
4  -2.26666	3.258797e-01	4.767934e-01
2  -2.80315	3.173100e-01	4.901035e-01
2  -2.72016	3.200183e-01	4.858972e-01
1  -2.55022	3.093332e-01	5.024927e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1306 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000278 	for  Omega_m
           0.000586 	for  b1
--> Not computing covariance matrix
1  -2.64445	3.093332e-01	5.161624e-01
2  -2.62048	3.198193e-01	4.998759e-01
2  -2.11695	3.252573e-01	4.914299e-01
2  -2.61905	3.198420e-01	4.998407e-01
2  -2.41374	3.224800e-01	4.957433e-01
4  -2.09522	3.037003e-01	5.249111e-01
2  -2.78417	3.129397e-01	5.105608e-01
1  -2.79531	3.145763e-01	5.080191e-01
2  -2.1987	3.145763e-01	4.845688e-01
2  -2.53037	3.145763e-01	4.889491e-01
2  -2.86051	3.145763e-01	5.059811e-01
1  -2.87556	3.145763e-01	4.968442e-01
2  -1.88704	3.029446e-01	5.149098e-01
1  -2.00515	3.037058e-01	5.137276e-01
1  -1.81032	3.037058e-01	5.096797e-01
3  -1.12439	2.999182e-01	5.155624e-01
2  -1.25717	2.999182e-01	5.178697e-01
1  -0.678294	2.999182e-01	5.453119e-01
1  -1.44091	3.061816e-01	5.355839e-01
2  -1.83762	3.061816e-01	5.313552e-01
1  -2.20485	3.061816e-01	5.258441e-01
2  -2.36681	3.081633e-01	5.227663e-01
1  -2.50391	3.107836e-01	5.186966e-01
1  -2.64696	3.107836e-01	5.158648e-01
2  -2.58677	3.095287e-01	5.178139e-01
1  -2.25965	3.055152e-01	5.240475e-01
1  -1.9622	3.055152e-01	5.298892e-01
1  -1.84284	3.043923e-01	5.316331e-01
2  -2.06909	3.043923e-01	5.117428e-01
2  -1.77326	3.043923e-01	5.326545e-01
2  -2.0257	3.043923e-01	5.283883e-01
2  -1.76776	3.043923e-01	5.327318e-01
1  -2.04174	3.043923e-01	5.111088e-01
1  -1.20497	2.996183e-01	5.185236e-01
2  -1.36078	2.996183e-01	5.222996e-01
3  -1.45208	2.996183e-01	5.293464e-01
1  -2.82721	3.168150e-01	5.026374e-01
1  -0.306509	3.168150e-01	4.654949e-01
7  0.153985	3.096313e-01	4.766522e-01
1  0.633627	3.096313e-01	4.739433e-01
2  0.124623	3.186885e-01	4.598762e-01
6  0.816762	3.304600e-01	4.415934e-01
1  0.260444	3.240397e-01	4.515650e-01
1  -1.51231	3.240397e-01	4.647176e-01
1  -1.60275	3.225781e-01	4.669878e-01
1  -2.20151	3.225781e-01	4.740096e-01
1  -2.33909	3.196704e-01	4.785257e-01
1  -2.71319	3.196704e-01	4.857228e-01
1  -2.43175	3.083464e-01	5.033105e-01
2  -2.59457	3.083464e-01	5.170720e-01
1  -2.64343	3.083464e-01	5.105859e-01
1  -2.81338	3.108425e-01	5.067091e-01
1  -2.16336	3.108425e-01	5.233816e-01
1  -2.16348	3.108468e-01	5.233750e-01
1  -2.80661	3.108468e-01	5.058850e-01
4  -2.90405	3.171858e-01	4.960396e-01
1  -2.89742	3.174679e-01	4.956015e-01
1  -2.80951	3.174679e-01	5.015621e-01
1  -2.4708	3.228013e-01	4.932785e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1336 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000261 	for  Omega_m
           0.000600 	for  b1
--> Not computing covariance matrix
2  -2.26907	3.228013e-01	4.973042e-01
1  -2.58776	3.228013e-01	4.834502e-01
3  -2.82301	3.129769e-01	4.987088e-01
4  -1.95915	3.129769e-01	4.851589e-01
1  -2.8236	3.129769e-01	4.987299e-01
2  -2.83307	3.182528e-01	4.905357e-01
1  -2.84004	3.179967e-01	4.909335e-01
1  -2.37254	3.179967e-01	4.810775e-01
1  -2.23007	3.118328e-01	4.906510e-01
2  -2.35341	3.118328e-01	4.922525e-01
1  -1.58959	3.118328e-01	4.841027e-01
2  -1.74031	3.148704e-01	4.793850e-01
1  -1.70895	3.212620e-01	4.694579e-01
1  -0.302983	3.212620e-01	4.586510e-01
2  -0.128782	3.249495e-01	4.529238e-01
2  -0.324671	3.172225e-01	4.649249e-01
1  -0.337478	3.189870e-01	4.621844e-01
2  -1.67674	3.189870e-01	4.721016e-01
2  -0.681613	3.189870e-01	5.210017e-01
2  0.687982	3.189870e-01	5.286141e-01
1  -1.82164	3.189870e-01	5.123826e-01
1  -1.92254	3.085141e-01	5.286484e-01
1  -1.09137	3.085141e-01	5.360828e-01
2  -1.03602	3.074014e-01	5.378111e-01
4  -1.08864	3.154138e-01	5.253666e-01
2  -0.927054	3.181857e-01	5.210614e-01
4  -1.05277	3.161822e-01	5.241731e-01
2  -1.14136	3.100334e-01	5.337232e-01
1  0.617919	2.954418e-01	5.563860e-01
1  0.713768	2.954418e-01	5.572255e-01
1  -0.961222	3.155066e-01	5.260620e-01
1  -1.545	3.155066e-01	5.218053e-01
1  -1.5978	3.113229e-01	5.283031e-01
1  -2.83184	3.113229e-01	5.052598e-01
2  -2.86871	3.121963e-01	5.039034e-01
3  -1.2254	3.329371e-01	4.716898e-01
1  -1.18103	3.329371e-01	4.622463e-01
1  -1.54533	3.306863e-01	4.657421e-01
1  -1.50596	3.306863e-01	4.646581e-01
3  -2.53828	3.133211e-01	4.916288e-01
1  -2.90277	3.133211e-01	5.045981e-01
2  -2.91891	3.152267e-01	5.016384e-01
2  -2.75199	3.203776e-01	4.936383e-01
3  -2.6521	3.083415e-01	5.123322e-01
1  -1.8939	3.083415e-01	4.954712e-01
2  -1.76363	3.271434e-01	4.662690e-01
1  -1.43486	3.298179e-01	4.621151e-01
1  -0.2489	3.298179e-01	4.494885e-01
1  -0.529376	3.272083e-01	4.535416e-01
1  -1.67154	3.272083e-01	4.649138e-01
1  0.0702891	3.380451e-01	4.480826e-01
2  0.851338	3.380451e-01	4.385677e-01
1  -0.164126	3.380451e-01	4.536540e-01
1  -1.20252	3.326868e-01	4.619763e-01
1  -0.978675	3.326868e-01	4.792458e-01
3  -2.64998	3.197969e-01	4.992657e-01
3  -2.21288	3.197969e-01	5.063641e-01
2  -2.40616	3.160416e-01	5.121966e-01
1  -2.43952	3.143975e-01	5.147501e-01
1  -2.07645	3.143975e-01	5.190134e-01
1  -1.19251	3.254422e-01	5.018594e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1366 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000387 	for  Omega_m
           0.000550 	for  b1
--> Not computing covariance matrix
1  -1.69342	3.254422e-01	4.968739e-01
1  -1.92544	3.235433e-01	4.998232e-01
2  -2.52452	3.235433e-01	4.821565e-01
1  -2.39177	3.235433e-01	4.923073e-01
3  -2.29432	3.050165e-01	5.210822e-01
1  -2.28324	3.050165e-01	5.217815e-01
1  -2.73757	3.104843e-01	5.132891e-01
1  -2.43425	3.104843e-01	5.201251e-01
1  -2.48838	3.126950e-01	5.166916e-01
1  -2.87914	3.126950e-01	5.066211e-01
1  -2.70654	3.207619e-01	4.940920e-01
1  -2.61942	3.207619e-01	4.828046e-01
2  -2.56262	3.217625e-01	4.812506e-01
2  -2.69134	3.133942e-01	4.942478e-01
1  -2.4938	3.097957e-01	4.998367e-01
1  -2.69916	3.097957e-01	5.144459e-01
1  -2.5929	3.208601e-01	4.972613e-01
1  -2.73955	3.208601e-01	4.915303e-01
1  -2.44486	3.243803e-01	4.860629e-01
1  -2.43525	3.243803e-01	4.866446e-01
1  -2.56905	3.074254e-01	5.129781e-01
1  -2.26185	3.074254e-01	5.032717e-01
4  -2.2298	3.071321e-01	5.037272e-01
1  -2.01405	3.053720e-01	5.064611e-01
1  -0.670717	3.053720e-01	4.923928e-01
2  -1.01935	3.079620e-01	4.883701e-01
1  -1.0613	3.276509e-01	4.577903e-01
4  -1.32268	3.276509e-01	4.604882e-01
1  -1.50317	3.276509e-01	4.626277e-01
1  -1.0658	3.310707e-01	4.573163e-01
1  -1.16122	3.310707e-01	4.586623e-01
2  -0.87817	3.328976e-01	4.558249e-01
1  0.829995	3.413665e-01	4.426714e-01
1  1.45759	3.413665e-01	4.344097e-01
1  0.0103457	3.339903e-01	4.458660e-01
1  1.45223	3.339903e-01	4.351143e-01
1  1.03926	3.309646e-01	4.398137e-01
1  2.73872	3.309646e-01	4.307231e-01
2  4.04285	3.395548e-01	4.173812e-01
1  3.51293	3.365612e-01	4.220307e-01
1  0.777587	3.365612e-01	4.390131e-01
1  -0.197449	3.302363e-01	4.488365e-01
1  -1.46773	3.302363e-01	4.630778e-01
1  -2.43121	3.148609e-01	4.869582e-01
3  -2.91697	3.148609e-01	5.024405e-01
1  -2.91659	3.152321e-01	5.018639e-01
2  -2.76651	3.152321e-01	4.921888e-01
1  -1.44762	3.152321e-01	4.762255e-01
1  -1.29591	3.121267e-01	4.810486e-01
1  -2.18836	3.121267e-01	4.894831e-01
1  -2.30556	3.188260e-01	4.790782e-01
3  -1.96676	3.188260e-01	5.113384e-01
1  -2.0647	3.171261e-01	5.139787e-01
1  -2.90508	3.171261e-01	4.960195e-01
1  -2.71795	3.094469e-01	5.079464e-01
2  -2.47218	3.094469e-01	5.004925e-01
1  -2.7134	3.094469e-01	5.132320e-01
1  -2.75224	3.193254e-01	4.978893e-01
1  -2.75961	3.193254e-01	4.873354e-01
1  -1.46512	3.317393e-01	4.680547e-01
1  -1.04017	3.317393e-01	4.573100e-01
1  -2.03799	3.222674e-01	4.720213e-01
1  -2.64954	3.222674e-01	4.865200e-01
1  -2.73505	3.210339e-01	4.884358e-01
5  -2.47282	3.210339e-01	4.992308e-01
3  -0.863403	2.969992e-01	5.365603e-01
2  -0.612155	2.969992e-01	5.226122e-01
2  -0.814868	2.969992e-01	5.274626e-01
2  0.077772	2.969992e-01	5.520382e-01
1  0.236151	2.969992e-01	5.535101e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1401 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000305 	for  Omega_m
           0.000828 	for  b1
--> Not computing covariance matrix
2  -0.9339	3.051676e-01	5.408234e-01
1  -1.07876	3.169144e-01	5.225789e-01
1  -2.53251	3.169144e-01	4.849796e-01
1  -2.52539	3.177878e-01	4.836231e-01
1  -2.1935	3.177878e-01	5.111994e-01
2  -1.73782	3.232624e-01	5.026965e-01
1  -2.09841	3.193343e-01	5.087974e-01
1  -2.8165	3.193343e-01	4.901676e-01
2  -2.19832	3.267908e-01	4.785866e-01
1  -2.29224	3.259942e-01	4.798238e-01
4  -2.14144	3.259942e-01	4.878412e-01
1  -2.0604	3.259942e-01	4.896074e-01
4  -2.55673	3.211610e-01	4.971140e-01
2  -2.71945	3.103357e-01	5.139273e-01
3  -2.72801	3.183746e-01	5.014418e-01
3  -2.85983	3.183746e-01	4.922843e-01
1  -2.90107	3.145440e-01	4.982338e-01
4  -2.90289	3.145440e-01	4.983513e-01
3  -2.81582	3.145440e-01	5.075016e-01
2  -2.63632	3.089573e-01	5.161786e-01
1  -2.64113	3.198864e-01	4.992041e-01
2  -2.35719	3.198864e-01	4.785513e-01
1  -2.80384	3.198864e-01	4.917201e-01
1  -1.83427	3.293463e-01	4.770275e-01
6  -1.83924	3.293463e-01	4.719955e-01
6  -1.82117	3.293463e-01	4.708535e-01
1  -1.15488	3.293463e-01	4.582015e-01
3  -1.84428	3.211164e-01	4.709839e-01
2  -1.93522	3.211164e-01	4.719529e-01
1  -2.03428	3.211164e-01	4.730724e-01
1  -1.04455	3.313647e-01	4.571552e-01
1  -0.99245	3.313647e-01	4.564543e-01
2  -1.07336	3.308034e-01	4.573262e-01
4  -1.92954	3.220364e-01	4.709426e-01
2  -1.94639	3.130099e-01	4.849621e-01
2  -0.950755	3.316462e-01	4.560172e-01
1  -1.9973	3.141844e-01	4.831380e-01
1  -2.9181	3.141844e-01	5.028519e-01
1  -2.65674	3.084066e-01	5.118256e-01
1  -2.53243	3.084066e-01	5.054678e-01
1  -2.80125	3.126428e-01	4.988885e-01
3  -2.34722	3.126428e-01	4.903295e-01
2  -2.38644	3.200608e-01	4.788082e-01
1  -2.26866	3.112660e-01	4.924678e-01
1  -2.0399	3.112660e-01	4.897452e-01
1  -2.07698	3.224580e-01	4.723623e-01
3  -1.29211	3.224580e-01	5.088185e-01
1  -1.58154	3.194358e-01	5.135125e-01
1  -2.15803	3.194358e-01	5.078855e-01
3  -2.0113	3.212637e-01	5.050465e-01
3  -1.72932	3.212637e-01	5.079381e-01
1  -2.03939	3.092289e-01	5.266299e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1426 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000261 	for  Omega_m
           0.000526 	for  b1
--> Not computing covariance matrix
1  -1.97735	3.092289e-01	5.273292e-01
1  -1.89514	3.077413e-01	5.296396e-01
3  -1.87303	3.077413e-01	5.298880e-01
2  -0.764176	2.988065e-01	5.437651e-01
2  -1.12717	3.009316e-01	5.404645e-01
1  -1.38323	3.027163e-01	5.376927e-01
2  -0.863803	3.027163e-01	5.430531e-01
1  -1.29554	3.027163e-01	5.387270e-01
1  -1.6046	3.055088e-01	5.343898e-01
1  -2.30563	3.055088e-01	5.225422e-01
1  -2.72208	3.112039e-01	5.136970e-01
3  -2.83144	3.112039e-01	5.083508e-01
2  -1.56607	3.002433e-01	5.253744e-01
1  -2.84008	3.114015e-01	5.080440e-01
1  -2.62536	3.114015e-01	5.158573e-01
2  -2.43645	3.078533e-01	5.213680e-01
1  -2.31119	3.063836e-01	5.236507e-01
1  -1.68938	3.063836e-01	4.987696e-01
1  -2.09155	3.237855e-01	4.717419e-01
1  -2.37561	3.237855e-01	4.770408e-01
4  -2.68574	3.157817e-01	4.894719e-01
2  -2.11094	3.065297e-01	5.038416e-01
1  -2.06821	3.061803e-01	5.043843e-01
1  -0.670153	3.061803e-01	4.902387e-01
1  -1.16461	3.105040e-01	4.835233e-01
1  0.662376	3.105040e-01	4.719342e-01
1  4.38015	2.931453e-01	4.988948e-01
1  2.16896	2.931453e-01	5.116194e-01
2  2.48562	2.921842e-01	5.131121e-01
1  -0.436047	3.037319e-01	4.951769e-01
1  -1.27193	3.037319e-01	5.025648e-01
4  -1.90022	3.084593e-01	4.952224e-01
1  -1.13012	3.028955e-01	5.038639e-01
1  -1.66802	3.028955e-01	5.337883e-01
1  -1.93032	3.219197e-01	5.042408e-01
1  -2.6757	3.219197e-01	4.871648e-01
1  -2.91133	3.157917e-01	4.966824e-01
1  -2.5745	3.157917e-01	5.102394e-01
1  -2.00068	3.240106e-01	4.974742e-01
3  -2.46872	3.240106e-01	4.874380e-01
1  -2.784	3.199732e-01	4.937086e-01
4  -2.13166	3.199732e-01	5.069017e-01
6  -1.53282	3.199732e-01	5.127162e-01
2  -2.42335	3.199732e-01	4.794675e-01
1  -1.77842	3.199732e-01	5.105512e-01
4  -1.8513	3.069985e-01	5.307029e-01
1  -2.02849	3.103311e-01	5.255268e-01
1  -2.34796	3.103311e-01	4.959151e-01
1  -0.641671	2.988614e-01	5.137293e-01
1  -0.725293	2.988614e-01	5.443112e-01
1  -1.9741	3.129780e-01	5.223859e-01
1  -2.87352	3.129780e-01	5.070667e-01
1  -2.09821	3.034191e-01	5.219132e-01
1  -2.0455	3.034191e-01	5.258484e-01
1  -2.483	3.073390e-01	5.197602e-01
1  -1.49255	3.073390e-01	4.940426e-01
1  -2.07902	3.170392e-01	4.789768e-01
1  -2.89219	3.170392e-01	4.990260e-01
3  -2.52047	3.233143e-01	4.892798e-01
1  -2.56447	3.233143e-01	4.853470e-01
2  -1.77851	3.018684e-01	5.186557e-01
1  -1.56965	3.007092e-01	5.204561e-01
3  -1.60853	3.007092e-01	5.218952e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1459 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000022 	for  Omega_m
           0.000225 	for  b1
--> Not computing covariance matrix
2  -2.9258	3.152418e-01	4.993239e-01
1  -2.88136	3.180340e-01	4.949873e-01
1  -2.80894	3.180340e-01	5.000049e-01
2  -2.81154	3.179669e-01	5.001091e-01
2  -2.70965	3.094146e-01	5.133920e-01
1  -2.55131	3.221738e-01	4.935752e-01
2  -2.45744	3.221738e-01	4.958860e-01
2  -2.24231	3.221738e-01	4.996274e-01
1  -1.98112	3.221738e-01	5.029970e-01
1  -1.93072	3.226685e-01	5.022285e-01
1  -1.69816	3.226685e-01	5.046808e-01
1  -2.19159	3.108490e-01	5.230382e-01
1  -2.27783	3.108490e-01	5.219633e-01
1  -1.45187	3.016122e-01	5.363095e-01
2  -1.54219	3.016122e-01	5.347744e-01
1  -1.12269	3.016122e-01	5.406889e-01
1  -1.16559	3.019136e-01	5.402208e-01
1  -0.438235	3.019136e-01	5.470245e-01
2  -1.01991	3.145705e-01	5.273664e-01
2  -0.895339	3.171406e-01	5.233746e-01
1  -1.06608	3.119082e-01	5.315013e-01
1  -1.71072	3.119082e-01	5.264696e-01
1  -1.27359	3.211282e-01	5.121497e-01
1  -2.61544	3.211282e-01	4.826632e-01
3  -2.73261	3.141555e-01	4.934928e-01
2  -2.91888	3.141555e-01	5.010864e-01
2  -2.73801	3.141555e-01	4.936149e-01
5  -2.75364	3.141555e-01	4.939780e-01
1  -2.77564	3.161174e-01	4.909308e-01
1  -2.9124	3.161174e-01	5.001939e-01
1  -2.83238	3.188798e-01	4.959035e-01
1  -0.116806	3.188798e-01	4.609968e-01
1  -0.11565	3.193456e-01	4.602733e-01
1  1.79426	3.193456e-01	4.502350e-01
1  1.88994	3.241266e-01	4.428095e-01
2  0.244222	3.241266e-01	4.515555e-01
2  0.74103	3.241266e-01	4.486980e-01
1  -0.249772	3.241266e-01	4.546584e-01
1  -0.259499	3.135592e-01	4.710711e-01
1  -1.85459	3.135592e-01	4.829511e-01
1  -1.83317	3.218552e-01	4.700662e-01
1  -2.30934	3.218552e-01	4.995510e-01
2  -2.06195	3.040915e-01	5.271407e-01
1  -2.66857	3.138615e-01	5.119665e-01
1  -2.72754	3.138615e-01	4.940015e-01
1  -2.64156	3.117012e-01	4.973567e-01
3  -2.19427	3.117012e-01	5.219130e-01
1  -1.97626	3.070292e-01	5.291693e-01
3  -1.76985	3.070292e-01	5.315924e-01
1  -1.66121	3.056950e-01	5.336647e-01
1  -2.34791	3.056950e-01	5.131222e-01
1  -2.33777	3.056111e-01	5.132525e-01
1  -1.73849	3.056111e-01	5.328194e-01
3  -1.74316	3.056616e-01	5.327410e-01
2  -1.77183	3.056616e-01	5.323973e-01
1  -0.85101	3.056616e-01	5.410233e-01
1  -0.918562	3.065899e-01	5.395816e-01
4  -1.49495	3.065899e-01	5.347355e-01
1  -2.39172	3.065899e-01	5.095212e-01
3  -0.333685	2.955485e-01	5.266701e-01
1  0.130788	2.955485e-01	5.195357e-01
1  -0.801157	2.993388e-01	5.136487e-01
1  -0.527347	2.993388e-01	5.467610e-01
1  -0.7715	3.008489e-01	5.444156e-01
3  -1.54548	3.008489e-01	5.187766e-01
3  -2.79625	3.197572e-01	4.894093e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1491 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000072 	for  Omega_m
           0.000197 	for  b1
--> Not computing covariance matrix
2  -2.64118	3.197572e-01	4.995923e-01
1  -2.62853	3.197572e-01	4.998801e-01
1  -2.79609	3.136300e-01	5.093965e-01
1  -2.43361	3.136300e-01	5.160875e-01
3  -2.33496	3.094732e-01	5.225437e-01
2  -2.7362	3.094732e-01	5.105241e-01
1  -2.67246	3.094732e-01	5.054950e-01
2  -2.73047	3.209970e-01	4.875968e-01
5  -2.82346	3.120765e-01	5.014517e-01
2  -2.56875	3.120765e-01	5.162005e-01
3  -2.80075	3.120765e-01	5.005394e-01
3  -2.5692	3.231042e-01	4.834118e-01
3  -2.48967	3.231042e-01	4.797738e-01
1  -2.76231	3.165552e-01	4.899454e-01
1  -1.51329	3.165552e-01	4.744636e-01
1  -1.48868	3.203362e-01	4.685911e-01
1  -2.57158	3.203362e-01	4.993879e-01
1  -1.4402	3.298067e-01	4.846788e-01
1  -0.747194	3.298067e-01	4.928061e-01
1  -1.1192	3.276098e-01	4.962182e-01
2  -0.984987	3.276098e-01	4.974529e-01
4  -1.54666	3.276098e-01	4.915599e-01
2  -1.9831	3.276098e-01	4.838672e-01
1  -2.04842	3.276098e-01	4.733312e-01
2  -2.77143	3.176219e-01	4.888440e-01
1  -2.46804	3.087770e-01	5.025814e-01
1  -2.49945	3.087770e-01	5.032619e-01
1  -2.81013	3.160476e-01	4.919696e-01
1  -2.46772	3.160476e-01	4.853779e-01
1  -2.47048	3.168329e-01	4.841583e-01
1  -2.45533	3.168329e-01	4.839378e-01
1  -2.38065	3.204046e-01	4.783903e-01
1  0.646693	3.204046e-01	4.543431e-01
3  0.778374	3.243681e-01	4.481872e-01
1  -0.188836	3.243681e-01	4.539774e-01
1  -0.0729627	3.260383e-01	4.513835e-01
2  0.380057	3.260383e-01	4.485152e-01
1  -0.915827	3.260383e-01	4.576178e-01
1  -0.918149	3.260110e-01	4.576601e-01
4  -1.82448	3.260110e-01	4.671952e-01
1  -2.23999	3.260110e-01	4.760273e-01
1  -2.75519	3.134906e-01	4.954733e-01
1  -2.90982	3.134906e-01	5.034315e-01
1  -2.77387	3.100764e-01	5.087344e-01
2  -0.901059	3.100764e-01	4.825057e-01
1  -1.51746	3.100764e-01	4.874035e-01
1  -1.80485	3.149350e-01	4.798574e-01
2  -2.59913	3.149350e-01	4.893876e-01
2  -2.92523	3.149350e-01	4.998213e-01
3  -2.90745	3.149350e-01	5.031109e-01
1  -1.47415	3.309768e-01	4.781956e-01
1  -1.5194	3.309768e-01	4.768617e-01
1  -2.45161	3.241336e-01	4.874902e-01
3  -1.30031	3.241336e-01	5.044725e-01
1  -1.83486	3.072354e-01	5.307179e-01
2  -1.5975	3.072354e-01	5.331868e-01
1  -0.960912	3.072354e-01	5.385638e-01
1  0.0863499	3.261047e-01	5.092569e-01
1  -1.47419	3.261047e-01	4.972634e-01
1  -1.82915	3.233001e-01	5.016193e-01
1  -2.34909	3.233001e-01	4.941781e-01
1  -2.78448	3.124545e-01	5.110230e-01
1  -2.88013	3.124545e-01	5.061078e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1524 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000184 	for  Omega_m
           0.000064 	for  b1
--> Not computing covariance matrix
4  -2.89858	3.131721e-01	5.049933e-01
1  -2.77671	3.101225e-01	5.097298e-01
1  -2.63239	3.101225e-01	5.165311e-01
2  -2.72721	3.135009e-01	5.112838e-01
2  -2.58095	3.091837e-01	5.179892e-01
1  -2.71841	3.127640e-01	5.124283e-01
3  -2.70713	3.127640e-01	4.960648e-01
5  -2.68432	3.200421e-01	4.847609e-01
3  -2.71249	3.200421e-01	4.967281e-01
1  -1.90821	3.278383e-01	4.846194e-01
3  -2.06234	3.278383e-01	4.760625e-01
1  -2.87796	3.153431e-01	4.954693e-01
4  -2.5782	3.153431e-01	5.110272e-01
1  -2.92542	3.153431e-01	5.003893e-01
1  -2.68804	3.215620e-01	4.907305e-01
1  -2.3685	3.215620e-01	4.772841e-01
3  -2.39791	3.209876e-01	4.781762e-01
3  -1.20567	3.209876e-01	4.653970e-01
1  -1.12749	3.228461e-01	4.625104e-01
4  -2.55958	3.228461e-01	4.901665e-01
1  -2.39176	3.228461e-01	4.949213e-01
5  -1.6732	3.285709e-01	4.860298e-01
1  -1.36748	3.285709e-01	4.608256e-01
1  -1.93206	3.126752e-01	4.855140e-01
3  -1.86053	3.126752e-01	4.848086e-01
1  -1.6733	3.100452e-01	4.888934e-01
1  -2.76759	3.100452e-01	5.107407e-01
1  -2.64741	3.083126e-01	5.134316e-01
1  -2.64205	3.083126e-01	5.141898e-01
1  -2.43681	3.061151e-01	5.176029e-01
1  -1.90959	3.061151e-01	5.022926e-01
1  -2.51196	3.196740e-01	4.812336e-01
1  -2.81276	3.196740e-01	4.910067e-01
1  -1.74487	3.300134e-01	4.749481e-01
1  -1.57911	3.300134e-01	4.650953e-01
2  0.406402	3.404264e-01	4.489224e-01
1  -1.03737	3.334274e-01	4.597928e-01
1  -1.14354	3.334274e-01	4.634618e-01
1  -2.7043	3.190432e-01	4.858026e-01
1  -2.68311	3.190432e-01	5.006867e-01
1  -2.62961	3.089260e-01	5.164003e-01
1  -2.66353	3.089260e-01	5.149347e-01
2  -2.45894	3.228841e-01	4.932557e-01
1  -2.09393	3.261723e-01	4.881485e-01
1  -1.50248	3.261723e-01	4.967570e-01
1  -2.06545	3.213083e-01	5.043115e-01
1  -2.26969	3.213083e-01	5.016978e-01
1  -2.34439	3.203823e-01	5.031360e-01
1  -2.71355	3.203823e-01	4.857289e-01
2  -2.79011	3.134374e-01	4.965155e-01
2  -2.82567	3.163289e-01	4.920245e-01
3  -2.57578	3.094448e-01	5.027165e-01
3  -2.27351	3.094448e-01	5.234606e-01
1  -1.09148	2.992293e-01	5.393269e-01
1  -1.00894	2.992293e-01	5.407135e-01
1  -2.07194	3.077423e-01	5.274916e-01
3  -2.59101	3.077423e-01	5.115765e-01
3  -2.56497	3.074631e-01	5.120102e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1551 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000211 	for  Omega_m
           0.000094 	for  b1
--> Not computing covariance matrix
1  -1.51889	3.074631e-01	4.939600e-01
2  -1.76997	3.248809e-01	4.669076e-01
1  -2.01088	3.210196e-01	4.729047e-01
1  -2.63086	3.210196e-01	4.831035e-01
2  -1.39682	3.011950e-01	5.138940e-01
1  -1.95646	3.282462e-01	4.718795e-01
1  -1.95513	3.282462e-01	4.718247e-01
3  -0.954901	3.344780e-01	4.621459e-01
1  -0.852618	3.344780e-01	4.717915e-01
1  -2.77545	3.100963e-01	5.096598e-01
1  -2.73345	3.100963e-01	5.132220e-01
4  -2.8471	3.155310e-01	5.047812e-01
1  -2.85085	3.151233e-01	5.054144e-01
1  -2.81431	3.151233e-01	5.065600e-01
2  -2.37997	3.231429e-01	4.941043e-01
1  -2.29971	3.239261e-01	4.928879e-01
1  -1.2114	3.239261e-01	4.620594e-01
3  -1.40127	3.189968e-01	4.697154e-01
3  -1.85946	3.189968e-01	4.738157e-01
1  -1.81861	3.205992e-01	4.713269e-01
2  -2.52636	3.205992e-01	4.807704e-01
1  -2.75635	3.205992e-01	4.919051e-01
2  -2.76962	3.100411e-01	5.083034e-01
2  -2.81026	3.196465e-01	4.933848e-01
2  -2.74522	3.096620e-01	5.088923e-01
1  -2.92348	3.158745e-01	4.992433e-01
3  -2.87998	3.158745e-01	4.947086e-01
2  -2.7497	3.204758e-01	4.875621e-01
1  -2.85931	3.175970e-01	4.920333e-01
1  -0.23751	3.175970e-01	4.637727e-01
1  -0.245716	3.188812e-01	4.617781e-01
1  -0.426644	3.188812e-01	4.629101e-01
6  -0.368324	3.219527e-01	4.581396e-01
1  -0.253245	3.243338e-01	4.544414e-01
3  -2.20415	3.243338e-01	4.734804e-01
2  -2.38279	3.218259e-01	4.773756e-01
2  -2.49018	3.138748e-01	4.897249e-01
1  -2.51053	3.146024e-01	4.885948e-01
3  -2.35958	3.146024e-01	5.154477e-01
2  -2.34431	3.153946e-01	5.142173e-01
1  -1.66892	3.244075e-01	5.002189e-01
1  -2.46142	3.244075e-01	4.839247e-01
2  -2.02602	3.280783e-01	4.782234e-01
1  -1.75931	3.299021e-01	4.753907e-01
1  -1.76327	3.299021e-01	4.750043e-01
1  -1.41556	3.320118e-01	4.717278e-01
2  -0.948903	3.320118e-01	4.826681e-01
2  -1.42273	3.320118e-01	4.710282e-01
1  -0.921573	3.320118e-01	4.830348e-01
1  -1.60181	3.280685e-01	4.891593e-01
1  -1.97248	3.280685e-01	4.813958e-01
1  -2.27682	3.257244e-01	4.850365e-01
3  -2.30511	3.257244e-01	4.782745e-01
6  -1.29629	3.327593e-01	4.673482e-01
2  -2.85036	3.153231e-01	4.944293e-01
1  -2.76309	3.197703e-01	4.875221e-01
2  -2.28967	3.197703e-01	4.777317e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1581 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000423 	for  Omega_m
           0.000153 	for  b1
--> Not computing covariance matrix
1  -2.77145	3.197703e-01	4.879131e-01
2  -2.18446	3.052208e-01	5.105105e-01
2  -2.79817	3.191297e-01	4.889079e-01
1  -2.21828	3.265380e-01	4.774018e-01
1  -1.82547	3.265380e-01	4.915213e-01
2  -1.83285	3.264843e-01	4.916047e-01
1  -2.56365	3.190154e-01	5.032050e-01
1  -1.24609	3.190154e-01	5.170764e-01
1  -0.000803058	3.285513e-01	5.022657e-01
1  -0.650536	3.285513e-01	4.975057e-01
1  -1.94081	3.170425e-01	5.153806e-01
4  -1.37501	3.170425e-01	5.201796e-01
2  -2.74982	3.170425e-01	4.889720e-01
1  -2.67434	3.170425e-01	4.873071e-01
3  -2.6614	3.180042e-01	4.858135e-01
1  -1.86541	3.180042e-01	4.753084e-01
1  -1.54387	3.251840e-01	4.641572e-01
2  -2.37056	3.251840e-01	4.797504e-01
1  -1.75484	3.251840e-01	4.969493e-01
1  -2.50471	3.150517e-01	5.126861e-01
1  -2.91294	3.150517e-01	4.979991e-01
1  -2.6704	3.090884e-01	5.072611e-01
1  -2.67583	3.090884e-01	5.146170e-01
1  0.21303	2.927712e-01	5.399601e-01
1  0.745806	2.927712e-01	5.263535e-01
2  1.00706	2.919490e-01	5.276304e-01
2  0.119884	2.948882e-01	5.230655e-01
1  -1.13736	3.000773e-01	5.150060e-01
1  -1.52492	3.000773e-01	5.248173e-01
2  -2.07726	3.033270e-01	5.197700e-01
1  -2.75815	3.098084e-01	5.097034e-01
1  -1.414	3.098084e-01	4.871346e-01
1  -1.3836	3.094880e-01	4.876322e-01
3  -2.42023	3.094880e-01	5.211722e-01
4  -2.45128	3.172383e-01	5.091349e-01
2  -2.38685	3.185436e-01	5.071075e-01
1  -2.30409	3.198361e-01	5.051001e-01
1  -2.50359	3.198361e-01	5.020925e-01
1  -2.69592	3.147448e-01	5.100000e-01
1  -2.1987	3.147448e-01	5.171002e-01
1  -1.82796	3.212694e-01	5.069666e-01
1  -2.50614	3.212694e-01	4.978569e-01
4  -2.74944	3.168206e-01	5.047665e-01
2  -2.68619	3.102172e-01	5.150227e-01
2  -2.68669	3.102271e-01	5.150072e-01
3  -2.1987	3.244546e-01	4.929098e-01
3  -1.7119	3.244546e-01	4.996210e-01
1  -2.36786	3.108695e-01	5.207207e-01
1  -2.72423	3.108695e-01	5.137572e-01
2  -2.7875	3.131098e-01	5.102777e-01
2  -2.78159	3.159132e-01	5.059236e-01
2  -2.79629	3.144573e-01	5.081848e-01
4  -2.70808	3.182162e-01	5.023466e-01
3  -2.38484	3.061438e-01	5.210970e-01
1  -2.359	3.061438e-01	5.220318e-01
4  -2.37563	3.063105e-01	5.217727e-01
1  -2.47744	3.074242e-01	5.200430e-01
1  -1.5636	3.074242e-01	5.333360e-01
1  -1.18354	3.032596e-01	5.398043e-01
1  -2.0599	3.032596e-01	5.241103e-01
1  -2.57983	3.079101e-01	5.168874e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1611 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000336 	for  Omega_m
           0.000149 	for  b1
--> Not computing covariance matrix
1  -1.8333	3.079101e-01	5.301765e-01
2  -1.7392	3.065669e-01	5.322626e-01
1  -1.30869	3.024993e-01	5.385803e-01
1  -1.9589	3.024993e-01	5.239104e-01
1  -2.37235	3.055793e-01	5.191266e-01
1  -1.82641	3.055793e-01	5.029573e-01
2  -0.918408	3.002668e-01	5.112085e-01
1  -2.2356	3.092400e-01	4.972717e-01
1  -2.69944	3.092400e-01	5.080211e-01
1  -2.4597	3.066033e-01	5.121163e-01
1  -2.19523	3.066033e-01	5.050058e-01
1  -2.49603	3.228484e-01	4.797746e-01
3  -1.99855	3.228484e-01	4.710588e-01
1  -2.17753	3.176094e-01	4.791959e-01
1  -2.8938	3.176094e-01	4.954268e-01
1  -2.19171	3.267407e-01	4.812446e-01
1  -0.442882	3.267407e-01	5.041618e-01
2  -0.331614	3.274204e-01	5.031061e-01
2  -1.18117	3.210990e-01	5.129241e-01
4  -0.635568	3.254883e-01	5.061069e-01
1  -0.620678	3.255890e-01	5.059505e-01
2  -1.00552	3.255890e-01	5.030280e-01
2  -0.782734	3.255890e-01	5.047655e-01
1  -0.340168	3.255890e-01	5.078736e-01
2  1.48057	3.348159e-01	4.935429e-01
2  -0.349828	3.255251e-01	5.079728e-01
1  -0.839665	3.217976e-01	5.137622e-01
2  -2.68443	3.217976e-01	4.873474e-01
4  -2.30255	3.217976e-01	4.760582e-01
2  -2.50571	3.217976e-01	4.798355e-01
1  -2.40218	3.217976e-01	4.777382e-01
2  -2.52009	3.141681e-01	4.895880e-01
1  -1.5398	3.036595e-01	5.059094e-01
2  -2.0139	3.036595e-01	5.142293e-01
2  0.0691117	3.036595e-01	4.917758e-01
1  -0.580289	3.036595e-01	4.965088e-01
1  -1.74671	3.186337e-01	4.732517e-01
1  -2.40816	3.186337e-01	4.807377e-01
1  -2.38549	3.141409e-01	4.877156e-01
3  -2.6764	3.141409e-01	4.923448e-01
1  -2.6962	3.151836e-01	4.907253e-01
2  -1.88612	3.151836e-01	5.194693e-01
1  -2.63062	3.151836e-01	5.104395e-01
1  -2.31988	3.066893e-01	5.236325e-01
1  -2.4923	3.066893e-01	5.172215e-01
2  -2.82267	3.179599e-01	4.997165e-01
1  -2.76521	3.192387e-01	4.977304e-01
1  -2.8343	3.192387e-01	4.932620e-01
1  -2.91079	3.168741e-01	4.969345e-01
2  -2.2828	3.168741e-01	4.815792e-01
1  -2.14791	3.168741e-01	5.136130e-01
1  -1.86477	3.055077e-01	5.312668e-01
1  -1.34814	3.055077e-01	4.978173e-01
1  -1.59773	3.074209e-01	4.948457e-01
2  -1.73239	3.074209e-01	5.316709e-01
3  -2.56333	3.074209e-01	5.123084e-01
1  -2.71574	3.092432e-01	5.094782e-01
2  -2.47117	3.092432e-01	5.011130e-01
2  -2.71268	3.092432e-01	5.091008e-01
2  -2.4786	3.092432e-01	5.012593e-01
1  -2.68984	3.092432e-01	5.074188e-01
1  -2.75686	3.207181e-01	4.895966e-01
1  -2.07192	3.207181e-01	5.057465e-01
2  -2.1521	3.196963e-01	5.073334e-01
1  -1.38651	3.008561e-01	5.365950e-01
2  -1.67699	3.008561e-01	5.241730e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1644 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000198 	for  Omega_m
           0.000120 	for  b1
--> Not computing covariance matrix
1  -1.68557	3.008561e-01	5.255600e-01
1  -2.41794	3.059317e-01	5.176769e-01
1  -2.36473	3.059317e-01	5.122613e-01
2  -2.91485	3.152834e-01	4.977367e-01
1  -2.71316	3.096411e-01	5.065000e-01
1  -2.62361	3.096411e-01	5.168504e-01
2  -2.19323	3.047064e-01	5.245147e-01
1  -2.60092	3.192151e-01	5.019807e-01
1  -0.44367	3.192151e-01	4.625089e-01
1  -0.392845	3.217646e-01	4.585491e-01
1  0.35905	3.217646e-01	4.539760e-01
6  0.352604	3.167850e-01	4.617100e-01
2  0.374509	3.160701e-01	4.628204e-01
1  1.2669	3.064141e-01	4.778176e-01
1  -0.404419	3.064141e-01	4.877316e-01
2  -1.10981	3.138741e-01	4.761450e-01
4  -1.20984	3.189041e-01	4.683327e-01
1  0.0170525	3.037577e-01	4.918574e-01
1  0.407741	3.037577e-01	4.893160e-01
1  -0.60814	3.117123e-01	4.769613e-01
1  -2.60247	3.117123e-01	5.160001e-01
1  -2.47249	3.190872e-01	5.045458e-01
1  -2.61098	3.190872e-01	4.836480e-01
1  -1.85351	3.284610e-01	4.690891e-01
1  -1.72932	3.284610e-01	4.662942e-01
1  -2.41266	3.132281e-01	4.899532e-01
1  -2.87668	3.132281e-01	5.003391e-01
1  -2.89428	3.170324e-01	4.944305e-01
1  -2.88124	3.170324e-01	4.935264e-01
2  -2.84349	3.127369e-01	5.001980e-01
1  -2.39981	3.249942e-01	4.811606e-01
1  -2.27505	3.249942e-01	4.753398e-01
1  -2.68094	3.179320e-01	4.863084e-01
1  -2.88459	3.179320e-01	4.950722e-01
1  -2.92556	3.152945e-01	4.991686e-01
1  -2.88757	3.152945e-01	4.959982e-01
1  -2.83488	3.126435e-01	5.001158e-01
1  -2.48343	3.126435e-01	5.168372e-01
1  -2.46642	3.155357e-01	5.123450e-01
1  -2.85038	3.155357e-01	4.940642e-01
8  -2.74174	3.115411e-01	5.002685e-01
1  -2.83834	3.143709e-01	4.958733e-01
1  -2.39295	3.143709e-01	5.154172e-01
1  -1.40778	3.266139e-01	4.964021e-01
1  -1.65477	3.266139e-01	4.647702e-01
1  -1.61464	3.270027e-01	4.641663e-01
1  -1.65889	3.270027e-01	4.647537e-01
2  -1.02416	3.318826e-01	4.571746e-01
1  -1.08617	3.314740e-01	4.578092e-01
1  0.407756	3.314740e-01	4.435736e-01
1  1.33137	3.372745e-01	4.345645e-01
1  -0.168824	3.372745e-01	4.507510e-01
2  -0.888434	3.334554e-01	4.566827e-01
1  -1.15677	3.318123e-01	4.592347e-01
1  -1.39353	3.318123e-01	4.749022e-01
1  -1.5613	3.308395e-01	4.764130e-01
3  -1.5915	3.308395e-01	4.681726e-01
1  -1.93259	3.284834e-01	4.718320e-01
3  -1.59093	3.284834e-01	4.639225e-01
1  -2.30799	3.179113e-01	4.803426e-01
1  -1.0398	3.179113e-01	4.685852e-01
1  -0.680895	3.103847e-01	4.802750e-01
2  -2.07344	3.103847e-01	4.922234e-01
1  -2.79088	3.103847e-01	5.095392e-01
3  -2.77188	3.199302e-01	4.947137e-01
3  -2.78445	3.199302e-01	4.939224e-01
1  -1.8067	3.292148e-01	4.795020e-01
1  -1.31215	3.292148e-01	4.888060e-01
1  -1.25977	3.295262e-01	4.883224e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1679 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000119 	for  Omega_m
           0.000212 	for  b1
--> Not computing covariance matrix
1  -1.82162	3.295262e-01	4.754800e-01
1  -1.88061	3.291300e-01	4.760954e-01
1  -1.88126	3.291300e-01	4.760050e-01
1  -2.48591	3.241680e-01	4.837115e-01
1  -2.46304	3.241680e-01	4.866109e-01
3  -2.8897	3.176230e-01	4.967763e-01
1  -2.78872	3.176230e-01	4.893401e-01
1  -2.78833	3.143864e-01	4.943670e-01
1  -2.41864	3.143864e-01	4.876855e-01
2  -2.42807	3.147537e-01	4.871150e-01
2  -2.44184	3.154668e-01	4.860074e-01
1  -2.43854	3.152647e-01	4.863213e-01
1  -1.97764	3.152647e-01	4.809281e-01
1  -1.73991	3.106645e-01	4.880730e-01
1  -2.02771	3.106645e-01	4.910258e-01
3  -2.16486	3.128617e-01	4.876133e-01
1  -1.74312	3.128617e-01	4.833162e-01
3  -1.82299	3.146977e-01	4.804646e-01
2  -2.53711	3.146977e-01	5.128274e-01
1  -1.89442	3.146977e-01	4.811444e-01
5  -1.91486	3.194722e-01	4.737289e-01
1  -2.72356	3.194722e-01	4.861053e-01
1  -2.51814	3.230023e-01	4.806226e-01
1  -2.58268	3.230023e-01	4.876137e-01
1  -2.72823	3.211083e-01	4.905553e-01
3  -2.5225	3.211083e-01	4.980305e-01
1  -2.49047	3.215101e-01	4.974064e-01
1  -2.62945	3.215101e-01	4.938287e-01
3  -2.18165	3.259713e-01	4.868999e-01
1  -2.23727	3.259713e-01	4.850715e-01
1  -1.96821	3.280183e-01	4.818922e-01
2  -2.0408	3.280183e-01	4.770352e-01
3  -1.9828	3.280183e-01	4.721074e-01
1  -2.35887	3.246236e-01	4.773799e-01
2  -2.1001	3.246236e-01	4.716303e-01
1  -2.42965	3.246236e-01	4.808476e-01
2  -1.74744	3.300485e-01	4.724219e-01
2  -1.38719	3.322537e-01	4.689968e-01
1  -2.3024	3.258421e-01	4.789551e-01
1  -2.26617	3.258421e-01	4.766379e-01
2  -2.38498	3.246713e-01	4.784564e-01
1  -2.79848	3.171407e-01	4.901524e-01
1  -2.85321	3.171407e-01	5.008461e-01
1  -2.79134	3.107219e-01	5.108155e-01
1  -2.46079	3.107219e-01	5.194723e-01
1  -2.50778	3.145202e-01	5.135729e-01
1  -2.66345	3.145202e-01	4.913346e-01
1  -2.54863	3.115655e-01	4.959237e-01
3  -2.31582	3.115655e-01	5.205960e-01
1  -2.30425	3.110906e-01	5.213337e-01
1  -1.58357	3.110906e-01	5.287567e-01
1  -1.41508	3.070086e-01	5.350965e-01
2  -2.48911	3.070086e-01	5.188897e-01
2  -1.81514	3.070086e-01	5.311073e-01
1  -2.11021	3.070086e-01	5.022129e-01
1  -2.61442	3.142665e-01	4.909403e-01
1  -2.86884	3.142665e-01	5.061053e-01
2  -2.39802	3.058534e-01	5.191722e-01
1  -2.04488	3.030896e-01	5.234648e-01
1  -2.00447	3.030896e-01	5.177990e-01
3  -1.39482	2.996584e-01	5.231281e-01
1  -1.44894	2.996584e-01	5.259090e-01
2  -2.84644	3.184991e-01	4.966466e-01
1  -2.91796	3.147008e-01	5.025458e-01
1  -2.89107	3.147008e-01	5.044517e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1711 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000319 	for  Omega_m
           0.000446 	for  b1
--> Not computing covariance matrix
4  -2.4875	3.231536e-01	4.913233e-01
1  -2.76367	3.101432e-01	5.115304e-01
1  -2.30914	3.101432e-01	4.958509e-01
1  -1.87534	3.059576e-01	5.023517e-01
4  -1.05577	3.059576e-01	4.938896e-01
3  -2.42245	3.059576e-01	5.164029e-01
2  -2.91561	3.149084e-01	5.025011e-01
1  -1.52441	3.000296e-01	5.256100e-01
3  -1.04682	3.000296e-01	5.138918e-01
1  -1.77429	3.292227e-01	4.685506e-01
3  -1.35495	3.292227e-01	4.606975e-01
1  -2.11154	3.193784e-01	4.759872e-01
2  -2.80469	3.193784e-01	4.953888e-01
4  -0.941882	3.193784e-01	4.656400e-01
2  -2.76194	3.193784e-01	4.874143e-01
1  -2.8059	3.193784e-01	4.953135e-01
3  -2.51869	3.233518e-01	4.891423e-01
2  -2.34022	3.233518e-01	4.761344e-01
1  -2.5298	3.233518e-01	4.817890e-01
1  -2.83701	3.171695e-01	4.913910e-01
2  -2.28156	3.171695e-01	4.811048e-01
1  -2.88452	3.171695e-01	4.936713e-01
3  -2.63678	3.223800e-01	4.855785e-01
2  -2.62961	3.223800e-01	4.890846e-01
2  -0.552986	3.223800e-01	5.143189e-01
1  -1.57786	3.223800e-01	5.065612e-01
1  -1.31378	3.245927e-01	5.031246e-01
1  -2.42517	3.245927e-01	4.855778e-01
1  -0.852627	3.347332e-01	4.698281e-01
1  -0.900227	3.347332e-01	4.613907e-01
1  -2.70655	3.134482e-01	4.944494e-01
1  -2.83821	3.134482e-01	4.980138e-01
1  -2.39824	3.069160e-01	5.081593e-01
1  -2.33815	3.069160e-01	5.233210e-01
1  -1.58203	3.275699e-01	4.912425e-01
4  -0.634561	3.275699e-01	5.004693e-01
1  -2.09494	3.275699e-01	4.789560e-01
2  -2.31118	3.258141e-01	4.816829e-01
2  -2.64474	3.223438e-01	4.870728e-01
2  -2.15778	3.270850e-01	4.797091e-01
1  -2.62182	3.226328e-01	4.866241e-01
2  -2.6203	3.226328e-01	4.857376e-01
1  -2.38124	3.226328e-01	4.958678e-01
2  -2.17075	3.246381e-01	4.927532e-01
1  -2.11906	3.039421e-01	5.248973e-01
1  -1.91963	3.039421e-01	5.301214e-01
2  -2.31386	3.193257e-01	5.062283e-01
3  0.302668	3.362837e-01	4.798901e-01
1  -0.284321	3.362837e-01	4.726818e-01
1  -2.61946	3.208351e-01	4.966758e-01
1  -2.60426	3.208351e-01	4.823970e-01
2  -2.53214	3.220693e-01	4.804800e-01
1  -2.38834	3.087288e-01	5.011998e-01
1  -2.64368	3.087288e-01	5.155450e-01
1  -2.71881	3.099098e-01	5.137108e-01
3  -1.91599	3.099098e-01	4.916461e-01
1  -1.38704	3.053106e-01	4.987892e-01
1  -2.16737	3.053106e-01	5.096817e-01
1  -2.77737	3.125212e-01	4.984826e-01
1  -2.27021	3.125212e-01	5.198635e-01
1  -2.0258	3.197187e-01	5.086847e-01
1  -2.50959	3.197187e-01	4.811500e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1741 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000370 	for  Omega_m
           0.000204 	for  b1
--> Not computing covariance matrix
3  -2.40689	3.218869e-01	4.777824e-01
4  -2.29076	3.218869e-01	4.997437e-01
1  -1.92921	3.218869e-01	5.043387e-01
1  -2.29609	3.103124e-01	5.223156e-01
3  -0.192781	3.103124e-01	4.772624e-01
1  -0.580259	3.173859e-01	4.662762e-01
1  -0.480528	3.173859e-01	4.656336e-01
1  -0.383648	3.230451e-01	4.568441e-01
1  -0.0461897	3.230451e-01	4.546758e-01
1  -0.141407	3.189377e-01	4.610552e-01
1  -2.08756	3.189377e-01	4.762906e-01
1  -2.09965	3.164375e-01	4.801737e-01
3  -2.61207	3.164375e-01	4.870364e-01
1  -2.37131	3.230385e-01	4.767840e-01
2  -2.30276	3.230385e-01	4.959627e-01
1  -2.47017	3.230385e-01	4.923350e-01
1  -2.44092	3.062382e-01	5.184285e-01
2  -1.53795	3.062382e-01	4.975776e-01
1  -2.45278	3.062382e-01	5.167850e-01
2  -2.90295	3.154398e-01	5.024936e-01
1  -2.90252	3.141909e-01	5.044332e-01
1  -2.8997	3.141909e-01	4.990014e-01
1  -2.8353	3.119552e-01	5.024737e-01
2  -2.82845	3.119552e-01	5.021160e-01
1  -2.74518	3.119552e-01	5.125678e-01
2  -2.758	3.124737e-01	5.117625e-01
1  -2.28763	3.053557e-01	5.228179e-01
1  -1.28568	3.053557e-01	5.376639e-01
1  -1.51021	3.086910e-01	5.324836e-01
1  -1.84354	3.086910e-01	5.293180e-01
1  0.126172	2.949506e-01	5.506588e-01
3  -0.314444	2.949506e-01	5.421506e-01
2  -1.82552	3.025723e-01	5.303129e-01
2  -2.42775	3.082013e-01	5.215703e-01
1  -1.50843	3.005707e-01	5.334217e-01
1  -1.2986	3.005707e-01	5.377359e-01
1  -1.7227	3.235664e-01	5.020203e-01
1  -2.41318	3.235664e-01	4.916685e-01
1  -2.36814	3.240059e-01	4.909859e-01
1  -2.47401	3.240059e-01	4.871783e-01
1  -2.35174	3.054058e-01	5.160670e-01
2  -1.97526	3.054058e-01	5.296954e-01
3  -1.45004	3.054058e-01	5.360584e-01
1  -1.34135	3.043003e-01	5.377754e-01
1  -1.74075	3.043003e-01	5.331062e-01
4  -1.71556	3.040803e-01	5.334479e-01
1  -2.21525	3.148843e-01	5.166677e-01
1  -2.92611	3.148843e-01	5.003854e-01
1  -2.92364	3.159286e-01	4.987634e-01
1  -2.91089	3.159286e-01	4.964835e-01
1  -2.62861	3.086099e-01	5.078506e-01
1  -2.31081	3.086099e-01	5.002490e-01
2  -2.51867	3.215274e-01	4.801862e-01
1  -2.66329	3.153595e-01	4.897658e-01
1  -2.60787	3.153595e-01	5.105076e-01
1  -2.61865	3.145151e-01	5.118191e-01
1  -2.92184	3.145151e-01	5.003104e-01
1  -2.82953	3.112728e-01	5.053462e-01
2  -2.72542	3.112728e-01	5.135669e-01
1  -2.72679	3.112728e-01	5.006633e-01
1  -2.52647	3.234161e-01	4.818030e-01
1  -1.77689	3.234161e-01	5.018639e-01
1  -1.31157	3.269375e-01	4.963946e-01
1  -0.913603	3.269375e-01	5.000271e-01
2  -1.04227	3.260895e-01	5.013443e-01
2  -1.62289	3.213541e-01	5.086991e-01
1  -1.76992	3.196862e-01	5.112895e-01
1  -1.27905	3.196862e-01	5.153732e-01
2  -1.41371	3.069343e-01	5.351789e-01
1  -0.663586	3.002912e-01	5.454965e-01
2  -1.57013	3.002912e-01	5.292827e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1779 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000648 	for  Omega_m
           0.000397 	for  b1
--> Not computing covariance matrix
2  -1.46253	3.002912e-01	5.337784e-01
1  -1.24029	3.002912e-01	5.383583e-01
2  -0.59137	2.969363e-01	5.435689e-01
1  -0.342898	2.958353e-01	5.452790e-01
5  -0.370036	2.958353e-01	5.447670e-01
1  -2.35087	3.142083e-01	5.162309e-01
1  -1.92911	3.142083e-01	5.207942e-01
1  -1.65133	3.059463e-01	5.336264e-01
3  -1.17278	3.059463e-01	5.381796e-01
4  -1.41406	3.116936e-01	5.292530e-01
1  -1.34623	3.155465e-01	5.232690e-01
2  -1.67994	3.155465e-01	5.206217e-01
1  -2.86899	3.155465e-01	4.947470e-01
1  -2.86683	3.163982e-01	4.934243e-01
2  -1.93095	3.163982e-01	4.784967e-01
1  -2.37146	3.163982e-01	4.834716e-01
1  -1.60469	3.287604e-01	4.642713e-01
1  -1.90422	3.287604e-01	4.718355e-01
1  -2.67107	3.114308e-01	4.987509e-01
1  -2.82223	3.114308e-01	5.039142e-01
2  -2.5715	3.232331e-01	4.855834e-01
1  -2.87567	3.127790e-01	5.018202e-01
1  -2.63692	3.127790e-01	5.140952e-01
3  -2.59898	3.166967e-01	5.080104e-01
1  -2.27617	3.166967e-01	5.125195e-01
2  -1.76477	3.037304e-01	5.326581e-01
2  -2.17329	3.187083e-01	5.093952e-01
1  -2.30494	3.108349e-01	5.216237e-01
1  -2.79696	3.108349e-01	5.106250e-01
4  -2.87944	3.135420e-01	5.064205e-01
1  -2.7865	3.106189e-01	5.109606e-01
1  -2.79105	3.106189e-01	5.059810e-01
1  -2.70586	3.214996e-01	4.890815e-01
3  -2.57924	3.214996e-01	4.816763e-01
4  -2.73307	3.152552e-01	4.913749e-01
1  -2.73388	3.170726e-01	4.885521e-01
1  -1.67504	3.170726e-01	4.749982e-01
2  -0.609677	3.043458e-01	4.947648e-01
1  -0.409783	3.031816e-01	4.965731e-01
1  -1.52014	3.031816e-01	5.074147e-01
1  -1.87043	3.055039e-01	5.038078e-01
1  -1.40634	3.055039e-01	5.364215e-01
4  -1.31803	3.045745e-01	5.378650e-01
1  -1.70625	3.115005e-01	5.271079e-01
4  -2.40633	3.115005e-01	5.194427e-01
1  -2.79483	3.115005e-01	5.111420e-01
2  -2.77732	3.180604e-01	5.009535e-01
2  -2.63174	3.085366e-01	5.157455e-01
1  -2.52631	3.072494e-01	5.177447e-01
2  -2.46263	3.072494e-01	5.203109e-01
1  -2.31367	3.072494e-01	5.048624e-01
1  -2.37873	3.078755e-01	5.038899e-01
1  -2.26153	3.078755e-01	5.017637e-01
2  -2.66393	3.183772e-01	4.854530e-01
1  -2.5955	3.203606e-01	4.823726e-01
1  -2.73757	3.203606e-01	4.944861e-01
1  -2.88744	3.168610e-01	4.999214e-01
1  -2.67466	3.168610e-01	4.875701e-01
1  -2.66236	3.148111e-01	4.907540e-01
1  -2.88214	3.148111e-01	5.047123e-01
2  -2.13596	3.261947e-01	4.870319e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1809 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000613 	for  Omega_m
           0.000461 	for  b1
--> Not computing covariance matrix
2  -1.77054	3.288066e-01	4.829752e-01
1  -0.939763	3.335318e-01	4.756363e-01
4  -0.767697	3.335318e-01	4.547642e-01
1  -0.744786	3.335318e-01	4.544144e-01
2  -1.56894	3.276915e-01	4.634852e-01
1  -1.65246	3.269235e-01	4.646781e-01
4  -0.084942	3.269235e-01	4.505813e-01
1  -0.91969	3.269235e-01	4.569584e-01
1  -0.114094	3.332910e-01	4.470687e-01
1  0.0547491	3.332910e-01	4.883856e-01
2  -1.86894	3.207165e-01	5.079157e-01
1  -2.11217	3.171058e-01	5.135236e-01
1  -2.47567	3.171058e-01	5.090694e-01
1  -1.90816	3.242261e-01	4.980105e-01
3  -2.33673	3.242261e-01	4.763159e-01
1  -2.65177	3.187568e-01	4.848106e-01
1  -2.65911	3.187568e-01	4.849697e-01
3  -2.64946	3.190822e-01	4.844642e-01
1  -2.53053	3.190822e-01	5.036122e-01
1  -2.4965	3.084997e-01	5.200484e-01
3  -2.64489	3.084997e-01	5.094198e-01
1  -2.92414	3.151649e-01	4.990677e-01
1  -2.91052	3.151649e-01	4.975937e-01
1  -2.66148	3.090358e-01	5.071131e-01
1  -2.69032	3.090358e-01	5.135643e-01
1  -2.20642	3.256618e-01	4.877417e-01
1  -1.26829	3.256618e-01	5.005688e-01
1  -0.0512475	3.326014e-01	4.897906e-01
1  -0.960654	3.326014e-01	4.568236e-01
1  -2.24067	3.187116e-01	4.783966e-01
1  -2.20432	3.187116e-01	4.779512e-01
1  -2.21418	3.180161e-01	4.790313e-01
2  -1.40736	3.180161e-01	4.712393e-01
1  -2.45163	3.180161e-01	4.821761e-01
2  -2.44274	3.185325e-01	4.813741e-01
1  -2.42783	3.191633e-01	4.803944e-01
1  -2.83438	3.191633e-01	4.940462e-01
1  -2.89911	3.130125e-01	5.035994e-01
1  -2.74648	3.130125e-01	5.114687e-01
2  -2.67838	3.106402e-01	5.151532e-01
1  -2.28124	3.054360e-01	5.232361e-01
1  -1.88974	3.054360e-01	5.043141e-01
1  -2.38949	3.101839e-01	4.969400e-01
5  -2.02042	3.101839e-01	4.921134e-01
4  -0.821535	3.336089e-01	4.557309e-01
2  -1.78177	3.266666e-01	4.665133e-01
1  -2.26255	3.193859e-01	4.778213e-01
1  -2.0692	3.193859e-01	4.754960e-01
2  -1.88207	3.234523e-01	4.691803e-01
1  -2.09014	3.163972e-01	4.801379e-01
3  -2.91799	3.163972e-01	4.973623e-01
3  -2.92509	3.151464e-01	4.993049e-01
1  -2.50399	3.151464e-01	5.125257e-01
1  -1.4714	3.272256e-01	4.937649e-01
1  -1.83808	3.272256e-01	4.887204e-01
1  -2.72113	3.110942e-01	5.137750e-01
1  -2.71339	3.110942e-01	5.008416e-01
2  -2.63161	3.220199e-01	4.838723e-01
1  -2.8075	3.184861e-01	4.893608e-01
1  -2.84136	3.184861e-01	4.910001e-01
5  -2.87626	3.142733e-01	4.975432e-01
4  -2.91575	3.142733e-01	5.031781e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1839 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000259 	for  Omega_m
           0.000172 	for  b1
--> Not computing covariance matrix
3  -2.23031	3.142733e-01	4.855152e-01
1  -2.27023	3.161719e-01	4.825665e-01
1  -2.92051	3.161719e-01	4.987672e-01
2  -2.88903	3.126446e-01	5.042456e-01
1  -2.92638	3.150078e-01	5.005752e-01
2  -2.21046	3.150078e-01	4.839015e-01
1  -1.37328	3.150078e-01	4.760361e-01
1  -1.38421	3.205743e-01	4.673905e-01
2  -2.35272	3.205743e-01	4.778072e-01
1  -1.67058	3.205743e-01	4.699210e-01
3  -1.03655	3.069458e-01	4.910881e-01
1  -1.77369	3.069458e-01	4.980549e-01
1  -1.03024	3.020878e-01	5.056002e-01
2  -1.59647	3.020878e-01	5.131399e-01
7  -1.23725	3.020878e-01	5.394019e-01
1  -1.0258	3.006643e-01	5.416128e-01
1  -1.34774	3.006643e-01	5.370199e-01
1  -2.17677	3.077281e-01	5.260489e-01
1  -2.56716	3.077281e-01	5.100492e-01
3  -2.85552	3.187338e-01	4.929556e-01
1  -2.85032	3.187338e-01	4.920537e-01
1  -2.69351	3.216656e-01	4.875002e-01
1  -2.37883	3.216656e-01	4.773962e-01
1  -2.48399	3.141745e-01	4.890310e-01
2  -1.28971	3.141745e-01	4.769301e-01
4  -1.72553	3.141745e-01	4.805561e-01
2  -2.25703	3.141745e-01	4.860246e-01
2  -1.84813	3.141745e-01	4.816891e-01
1  -1.03132	3.141745e-01	4.750028e-01
1  -1.10754	3.165050e-01	4.713833e-01
1  -0.983116	3.165050e-01	4.704840e-01
1  -0.50313	3.090451e-01	4.820703e-01
3  -0.979393	3.090451e-01	4.854498e-01
4  -1.39872	3.151990e-01	4.758919e-01
1  -1.42257	3.197648e-01	4.688006e-01
1  -2.61005	3.197648e-01	4.830652e-01
2  -2.41271	3.096830e-01	4.987238e-01
2  -2.60106	3.127647e-01	4.939374e-01
1  -2.67639	3.163014e-01	4.884444e-01
1  -2.90498	3.163014e-01	5.003251e-01
1  -2.44921	3.062007e-01	5.160129e-01
1  -2.26965	3.062007e-01	5.080913e-01
4  -2.40245	3.073899e-01	5.062443e-01
1  -2.83646	3.155562e-01	4.935608e-01
1  -2.61974	3.155562e-01	5.099371e-01
2  -2.55219	3.176718e-01	5.066513e-01
1  -2.6333	3.132117e-01	5.135785e-01
1  -2.89546	3.132117e-01	5.053987e-01
7  -2.67148	3.213936e-01	4.926911e-01
2  -2.71148	3.213936e-01	4.878077e-01
3  -2.67961	3.213936e-01	4.851850e-01
1  -2.45922	3.242204e-01	4.807946e-01
2  -2.47022	3.242204e-01	4.855957e-01
2  -1.21715	3.242204e-01	5.049486e-01
1  -2.47882	3.242204e-01	4.827542e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1866 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000405 	for  Omega_m
           0.000307 	for  b1
--> Not computing covariance matrix
2  -2.89044	3.143232e-01	4.981259e-01
3  -2.89422	3.165487e-01	4.946694e-01
1  -2.8825	3.165487e-01	4.939893e-01
3  -2.88312	3.148356e-01	4.966500e-01
1  -2.78943	3.148356e-01	5.077395e-01
2  -2.49392	3.073402e-01	5.193809e-01
1  -2.46175	3.218722e-01	4.968107e-01
1  -1.94393	3.218722e-01	5.042161e-01
1  -2.11517	3.198875e-01	5.072986e-01
3  -2.76549	3.198875e-01	4.952386e-01
1  -2.42284	3.059582e-01	5.168729e-01
1  -2.32111	3.059582e-01	5.105780e-01
1  -2.13546	3.045211e-01	5.128100e-01
1  -2.16549	3.045211e-01	5.137409e-01
4  -2.56726	3.080332e-01	5.082862e-01
1  -1.82196	3.022691e-01	5.172386e-01
2  -1.83635	3.022691e-01	5.176933e-01
2  -1.56576	3.022691e-01	5.350112e-01
1  -1.92185	3.022691e-01	5.244772e-01
1  -2.46429	3.064516e-01	5.179811e-01
1  -2.47122	3.064516e-01	5.145054e-01
2  -1.69531	3.010245e-01	5.229346e-01
2  -2.6659	3.085358e-01	5.112684e-01
2  -2.43658	3.243648e-01	4.866836e-01
2  -2.85594	3.185192e-01	4.957627e-01
2  -2.91206	3.136322e-01	5.033528e-01
4  -2.61139	3.078883e-01	5.122741e-01
2  -2.92401	3.153607e-01	5.006683e-01
1  -2.80923	3.195488e-01	4.941636e-01
3  -2.7369	3.195488e-01	4.976457e-01
1  -2.57526	3.218892e-01	4.940107e-01
1  -2.4906	3.218892e-01	4.961444e-01
1  -2.57941	3.081813e-01	5.174348e-01
5  -2.6268	3.081813e-01	5.105988e-01
1  -2.48381	3.066894e-01	5.129159e-01
1  -2.49951	3.066894e-01	5.161372e-01
1  -2.87991	3.168764e-01	5.003155e-01
2  -2.84471	3.168764e-01	5.018747e-01
1  -2.55809	3.168764e-01	5.083040e-01
2  -2.60288	3.125815e-01	5.149746e-01
1  -2.19247	3.056026e-01	5.258138e-01
1  -1.85492	3.056026e-01	5.032598e-01
1  -2.49022	3.127087e-01	4.922229e-01
2  -2.84491	3.127087e-01	5.086521e-01
1  -1.69585	3.127087e-01	4.832012e-01
2  -1.72849	3.133245e-01	4.822448e-01
2  -1.59731	3.112103e-01	4.855284e-01
1  -1.70428	3.128598e-01	4.829666e-01
2  -2.09674	3.128598e-01	4.868531e-01
3  -2.61123	3.128598e-01	4.939022e-01
2  -2.67422	3.175076e-01	4.866836e-01
3  -2.57646	3.120979e-01	4.950856e-01
1  -2.85543	3.120979e-01	5.080643e-01
2  -1.58735	3.003190e-01	5.263587e-01
2  -2.82624	3.113128e-01	5.092836e-01
1  -2.66889	3.086318e-01	5.134476e-01
1  -2.6033	3.086318e-01	5.170801e-01
1  -1.23344	2.986060e-01	5.326517e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1896 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000407 	for  Omega_m
           0.000403 	for  b1
--> Not computing covariance matrix
3  0.0382881	2.986060e-01	5.078211e-01
1  -1.95716	3.123218e-01	4.865183e-01
1  -2.87728	3.123218e-01	5.060786e-01
1  -2.88514	3.174380e-01	4.981325e-01
1  -2.83928	3.174380e-01	5.005879e-01
2  -2.79833	3.185158e-01	4.989139e-01
1  -2.88223	3.142953e-01	5.054690e-01
1  -2.4687	3.142953e-01	5.145174e-01
1  -2.20719	3.202939e-01	5.052006e-01
3  -1.81457	3.202939e-01	5.094599e-01
1  -0.971218	2.995692e-01	5.416485e-01
1  -0.670965	2.995692e-01	5.453085e-01
1  -1.11587	3.025355e-01	5.407014e-01
1  -1.82677	3.025355e-01	5.302026e-01
1  -2.00565	3.038463e-01	5.281668e-01
1  -1.98424	3.038463e-01	5.124667e-01
2  -2.66585	3.101307e-01	5.027061e-01
1  -2.58727	3.090818e-01	5.043353e-01
2  -2.58334	3.090818e-01	5.042267e-01
1  -2.70211	3.090818e-01	5.094980e-01
1  -2.88987	3.177115e-01	4.960948e-01
2  -1.88028	3.177115e-01	4.758969e-01
2  -1.75947	3.177115e-01	4.747508e-01
2  -2.89008	3.177115e-01	4.948201e-01
1  -2.88893	3.177115e-01	4.963172e-01
1  -2.86888	3.120500e-01	5.051103e-01
1  -2.79278	3.120500e-01	5.110444e-01
4  -2.16338	3.040816e-01	5.234205e-01
1  -2.77108	3.175284e-01	5.025355e-01
1  -2.32896	3.175284e-01	4.811659e-01
1  -2.3217	3.157024e-01	4.840020e-01
2  -2.92166	3.157024e-01	4.979164e-01
1  -2.84043	3.157024e-01	4.934497e-01
2  -2.7395	3.117418e-01	4.996011e-01
2  -2.51874	3.085456e-01	5.045651e-01
1  -2.62613	3.220286e-01	4.836241e-01
2  -2.65275	3.220286e-01	4.851645e-01
1  -2.66423	3.220286e-01	4.888791e-01
1  -2.41598	3.247625e-01	4.846330e-01
2  -2.36355	3.247625e-01	4.874490e-01
1  -2.21271	3.247625e-01	4.737249e-01
2  -2.0469	3.264403e-01	4.711190e-01
1  -2.2241	3.246353e-01	4.739225e-01
3  -2.25135	3.246353e-01	4.745093e-01
2  -1.39485	3.315183e-01	4.638190e-01
1  -1.84667	3.283580e-01	4.687273e-01
1  -1.88918	3.283580e-01	4.698814e-01
1  -2.32815	3.243167e-01	4.761582e-01
2  -2.17552	3.243167e-01	4.729572e-01
1  -2.42514	3.243167e-01	4.793085e-01
1  -2.75112	3.126366e-01	4.974494e-01
1  -2.63027	3.126366e-01	4.947800e-01
1  -1.73779	3.295880e-01	4.684520e-01
1  -0.858704	3.295880e-01	4.924651e-01
1  -2.06456	3.202731e-01	5.069326e-01
1  -2.21253	3.202731e-01	5.051863e-01
1  -2.40068	3.100714e-01	5.210310e-01
1  -2.71624	3.100714e-01	5.046315e-01
1  -2.23922	3.051863e-01	5.122188e-01
1  -2.26016	3.051863e-01	5.129252e-01
2  -2.80535	3.113318e-01	5.033804e-01
2  -2.90254	3.165542e-01	4.952692e-01
1  -2.76848	3.106517e-01	5.044367e-01
1  -2.79767	3.106517e-01	5.063535e-01
2  -2.70768	3.092559e-01	5.085214e-01
1  -0.845503	2.971162e-01	5.273761e-01
1  -0.91593	2.971162e-01	5.311275e-01
1  -2.78609	3.104234e-01	5.104595e-01
1  -2.73227	3.104234e-01	5.038203e-01
1  -2.02576	3.281306e-01	4.763183e-01
2  -1.79694	3.281306e-01	4.673318e-01
1  -1.48306	3.281306e-01	4.905416e-01
1  -2.52155	3.181473e-01	5.060471e-01
2  -1.99408	3.181473e-01	5.125512e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1934 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000396 	for  Omega_m
           0.000333 	for  b1
--> Not computing covariance matrix
1  -2.87365	3.181473e-01	4.934030e-01
2  -2.72061	3.097172e-01	5.064963e-01
3  -2.21508	3.047192e-01	5.142588e-01
1  -2.10449	3.047192e-01	5.109869e-01
1  -2.20779	3.054962e-01	5.097801e-01
2  -1.52642	3.054962e-01	4.996731e-01
1  -2.01772	3.054962e-01	5.060536e-01
2  -2.33574	3.082687e-01	5.017476e-01
2  -2.658	3.194605e-01	4.843651e-01
3  -2.60627	3.206637e-01	4.824964e-01
1  -2.64727	3.206637e-01	4.965129e-01
1  -2.66394	3.088806e-01	5.148137e-01
1  -2.64538	3.088806e-01	5.071846e-01
2  -2.86983	3.181060e-01	4.928562e-01
2  -2.68231	3.093567e-01	5.064452e-01
4  -1.9518	3.286521e-01	4.764767e-01
2  -1.83666	3.294428e-01	4.752485e-01
2  -2.34343	3.255469e-01	4.812994e-01
2  -1.98608	3.284081e-01	4.768556e-01
1  -1.8392	3.294259e-01	4.752748e-01
1  -1.7902	3.294259e-01	4.785530e-01
1  -2.77532	3.202234e-01	4.928458e-01
1  -2.66128	3.202234e-01	4.840616e-01
5  -2.7556	3.161091e-01	4.904517e-01
1  -2.50244	3.161091e-01	5.107255e-01
3  -1.87819	3.034172e-01	5.304380e-01
1  -1.05572	3.034172e-01	5.014007e-01
1  -2.17561	3.188854e-01	4.773762e-01
1  -2.73198	3.188854e-01	4.866567e-01
1  -2.27816	3.069874e-01	5.051361e-01
1  -2.17216	3.069874e-01	5.264095e-01
1  -2.41965	3.119876e-01	5.186435e-01
1  -2.80654	3.119876e-01	5.010434e-01
1  -2.88645	3.155939e-01	4.954422e-01
1  -2.20366	3.155939e-01	4.827718e-01
1  -1.89875	3.246965e-01	4.686341e-01
1  -2.26589	3.246965e-01	4.905773e-01
1  -2.10561	3.260327e-01	4.885021e-01
1  -0.72774	3.260327e-01	5.039939e-01
2  -0.289828	3.286956e-01	4.998580e-01
2  -0.943896	3.245227e-01	5.063390e-01
1  -1.60662	3.178546e-01	5.166957e-01
1  -2.46859	3.178546e-01	5.075295e-01
2  -2.5318	3.113058e-01	5.177007e-01
1  -2.54817	3.155703e-01	5.110774e-01
1  -2.80353	3.155703e-01	4.925541e-01
2  -2.77382	3.183222e-01	4.882800e-01
3  -2.70851	3.201111e-01	4.855015e-01
1  -2.31887	3.201111e-01	4.777660e-01
1  -2.24602	3.121474e-01	4.901347e-01
1  -2.70966	3.121474e-01	4.976950e-01
2  -2.78198	3.177121e-01	4.890523e-01
1  -2.78359	3.144375e-01	4.941381e-01
1  -2.85706	3.144375e-01	4.963922e-01
2  -2.86573	3.152379e-01	4.951491e-01
3  -2.84894	3.139915e-01	4.970850e-01
1  -2.90054	3.139915e-01	5.047572e-01
1  -2.85498	3.119522e-01	5.079246e-01
3  -2.62184	3.119522e-01	5.153721e-01
3  -2.64013	3.130081e-01	5.137321e-01
1  -1.85241	3.130081e-01	4.840417e-01
2  -1.82807	3.223766e-01	4.694909e-01
1  -1.16711	3.058446e-01	4.951677e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1964 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000792 	for  Omega_m
           0.000537 	for  b1
--> Not computing covariance matrix
1  -1.97365	3.058446e-01	5.041100e-01
1  -1.65785	3.036570e-01	5.075076e-01
1  -2.02953	3.036570e-01	5.147007e-01
1  -1.69603	3.016151e-01	5.178722e-01
1  -1.44163	3.016151e-01	5.364731e-01
1  -1.89473	3.052013e-01	5.309032e-01
1  -1.89214	3.052013e-01	5.051797e-01
1  -2.43879	3.104283e-01	4.970614e-01
1  -1.29745	3.104283e-01	4.847432e-01
2  -0.20653	3.024886e-01	4.970747e-01
1  -0.668368	3.051825e-01	4.928907e-01
3  -2.21812	3.051825e-01	5.247080e-01
2  -2.26323	3.055962e-01	5.240655e-01
1  -2.19625	3.049890e-01	5.250085e-01
1  -2.18328	3.049890e-01	5.253696e-01
2  -2.46601	3.079941e-01	5.207022e-01
1  -2.14438	3.046538e-01	5.258902e-01
3  -2.10706	3.046538e-01	5.113675e-01
2  -1.94918	3.035709e-01	5.130495e-01
1  -2.80444	3.189469e-01	4.891683e-01
1  -2.64677	3.189469e-01	4.845251e-01
2  -2.68501	3.159309e-01	4.892093e-01
1  -0.135943	3.383034e-01	4.544616e-01
1  -0.0856453	3.383034e-01	4.524899e-01
1  -0.594427	3.358600e-01	4.562848e-01
2  -0.184224	3.358600e-01	4.487308e-01
1  -0.699061	3.358600e-01	4.635429e-01
1  -1.06988	3.339951e-01	4.664394e-01
3  -0.741714	3.339951e-01	4.549116e-01
1  -0.529581	3.351725e-01	4.530828e-01
1  -0.745691	3.351725e-01	4.696819e-01
1  -2.03409	3.277439e-01	4.812196e-01
1  -2.00239	3.277439e-01	4.719717e-01
2  -0.980052	3.342850e-01	4.618123e-01
4  -1.14732	3.333710e-01	4.632319e-01
3  -1.21414	3.329935e-01	4.638182e-01
3  -1.00225	3.329935e-01	4.580638e-01
1  -0.922702	3.334622e-01	4.573360e-01
1  0.268102	3.334622e-01	4.437064e-01
2  0.174482	3.328460e-01	4.446634e-01
1  -0.913876	3.162021e-01	4.705138e-01
1  -2.13997	3.162021e-01	5.150333e-01
4  -1.09141	3.270308e-01	4.982148e-01
1  -1.20088	3.263041e-01	4.993435e-01
2  -2.17459	3.263041e-01	4.853344e-01
1  -2.17634	3.263041e-01	4.743813e-01
1  -2.46862	3.231975e-01	4.792062e-01
1  -2.57466	3.231975e-01	4.855035e-01
4  -2.7546	3.207450e-01	4.893127e-01
2  -2.43175	3.247096e-01	4.831550e-01
1  -2.80225	3.198839e-01	4.906501e-01
3  -2.05451	3.198839e-01	4.747060e-01
2  -1.85499	3.108912e-01	4.886730e-01
1  -1.37935	3.063234e-01	4.957675e-01
1  -0.512268	3.063234e-01	4.887193e-01
1  -0.431767	3.057688e-01	4.895807e-01
1  -2.4003	3.057688e-01	5.164211e-01
1  -2.71451	3.091610e-01	5.111524e-01
1  -2.17792	3.091610e-01	4.967004e-01
2  -2.51127	3.170985e-01	4.843724e-01
3  -2.3161	3.225879e-01	4.758466e-01
3  -2.5169	3.225879e-01	4.928835e-01
1  -2.24843	3.251919e-01	4.888389e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1996 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000919 	for  Omega_m
           0.000597 	for  b1
--> Not computing covariance matrix
1  -1.60804	3.251919e-01	4.648492e-01
1  -1.68644	3.241972e-01	4.663942e-01
1  -1.6848	3.241972e-01	4.663762e-01
4  -1.74259	3.116765e-01	4.858227e-01
2  -1.83554	3.132706e-01	4.833468e-01
2  -1.39519	3.078767e-01	4.917244e-01
1  -1.45293	3.083923e-01	4.909235e-01
1  -1.77739	3.083923e-01	4.940673e-01
2  -2.21482	3.156895e-01	4.827337e-01
2  -1.99878	3.234977e-01	4.706064e-01
2  -1.86981	3.093262e-01	4.926169e-01
1  -2.15185	3.135195e-01	4.861040e-01
1  -1.22616	3.135195e-01	4.777012e-01
1  -1.10713	3.116409e-01	4.806190e-01
2  -1.00095	3.116409e-01	4.798350e-01
2  -0.252933	3.116409e-01	4.748381e-01
1  -0.561824	3.116409e-01	4.768038e-01
1  -0.741392	3.145544e-01	4.722787e-01
2  -0.4308	3.145544e-01	4.702611e-01
1  -0.967591	3.145544e-01	4.738374e-01
2  -1.02806	3.200373e-01	4.653216e-01
1  -1.01409	3.158942e-01	4.717565e-01
1  -2.92232	3.158942e-01	4.979481e-01
3  -2.53634	3.073021e-01	5.112929e-01
1  -2.56007	3.073021e-01	5.137663e-01
3  -2.86642	3.119903e-01	5.064849e-01
1  -2.52766	3.119903e-01	4.945035e-01
1  -1.34782	3.018695e-01	5.102226e-01
1  0.182228	3.018695e-01	4.960959e-01
2  0.659524	2.996519e-01	4.995401e-01
3  -1.28335	3.221591e-01	4.645831e-01
1  -1.68216	3.221591e-01	4.682015e-01
1  -1.75264	3.204429e-01	4.708670e-01
1  -2.00707	3.204429e-01	4.735072e-01
1  -2.05934	3.165843e-01	4.795003e-01
3  -2.38277	3.165843e-01	5.114248e-01
1  -1.69353	3.249039e-01	4.985031e-01
1  -1.816	3.249039e-01	4.970761e-01
2  -1.08758	2.986050e-01	5.379222e-01
2  -2.04968	3.048331e-01	5.282489e-01
1  -1.50232	3.271887e-01	4.935274e-01
2  -1.82738	3.271887e-01	4.673156e-01
1  -2.14912	3.271887e-01	4.780720e-01
1  -2.70886	3.213542e-01	4.871338e-01
1  -2.70454	3.213542e-01	4.867128e-01
1  -2.02029	3.281696e-01	4.761275e-01
1  -1.67853	3.281696e-01	4.652035e-01
3  -1.56781	3.290556e-01	4.638274e-01
2  -0.547289	3.290556e-01	4.523762e-01
1  -0.35773	3.290556e-01	4.508297e-01
1  -0.975035	3.191218e-01	4.662583e-01
1  -1.21731	3.191218e-01	4.680690e-01
2  -1.06529	3.234668e-01	4.613206e-01
1  -0.960251	3.113767e-01	4.800983e-01
1  -1.61235	3.113767e-01	4.852945e-01
1  -0.554374	3.029701e-01	4.983512e-01
1  -0.939627	3.029701e-01	5.017261e-01
1  -1.38042	3.057597e-01	4.973935e-01
7  -1.29059	3.057597e-01	4.965340e-01
2  -2.07075	3.158254e-01	4.809005e-01
2  -1.90938	3.118246e-01	4.871143e-01
1  -1.98075	3.130843e-01	4.851579e-01
1  -0.771381	3.130843e-01	4.752870e-01
1  -0.680786	3.250986e-01	4.566269e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2029 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000871 	for  Omega_m
           0.000606 	for  b1
--> Not computing covariance matrix
4  -0.633519	3.250986e-01	4.562738e-01
2  -1.36297	3.250986e-01	4.623884e-01
1  -0.218656	3.250986e-01	4.533538e-01
3  -0.211438	3.252025e-01	4.531924e-01
1  -1.508	3.252025e-01	4.637660e-01
1  -1.0367	3.296739e-01	4.568214e-01
1  -0.213374	3.296739e-01	4.975942e-01
3  -1.50297	3.203909e-01	5.120120e-01
2  -1.7563	3.203909e-01	5.097821e-01
2  -2.50856	3.203909e-01	4.805697e-01
1  -1.0951	3.203909e-01	4.653343e-01
1  -1.10061	3.162586e-01	4.717524e-01
1  -2.47204	3.162586e-01	5.108680e-01
1  -2.51009	3.143074e-01	5.138985e-01
1  -2.85588	3.143074e-01	4.966299e-01
2  -2.46349	3.242408e-01	4.812017e-01
1  -2.51951	3.081378e-01	5.062121e-01
1  -2.20549	3.081378e-01	5.000596e-01
1  -1.03823	3.004332e-01	5.120260e-01
1  -1.23458	3.004332e-01	5.148477e-01
1  -2.54997	3.102301e-01	4.996316e-01
3  -2.61333	3.102301e-01	5.010080e-01
1  -0.799016	2.980307e-01	5.199555e-01
1  0.968712	2.980307e-01	5.026255e-01
1  0.291524	3.009466e-01	4.980968e-01
2  0.644558	3.009466e-01	4.957020e-01
1  -1.33602	3.009466e-01	5.140606e-01
1  -2.68776	3.126862e-01	4.958273e-01
1  -2.88214	3.126862e-01	5.027716e-01
1  -2.69408	3.091479e-01	5.082671e-01
1  -2.22729	3.091479e-01	4.974133e-01
1  -2.10001	3.078470e-01	4.994338e-01
2  -1.90164	3.078470e-01	4.969326e-01
2  -1.7044	3.078470e-01	4.947696e-01
1  -2.30794	3.078470e-01	5.026516e-01
2  -2.61641	3.118723e-01	4.963998e-01
1  -2.67728	3.132824e-01	4.942096e-01
1  -1.52777	3.132824e-01	4.805779e-01
1  -1.61911	3.198013e-01	4.704530e-01
2  -0.538048	3.198013e-01	4.622469e-01
2  -2.09195	3.198013e-01	4.752342e-01
1  -2.78851	3.198013e-01	4.889224e-01
2  -2.13167	3.273144e-01	4.772535e-01
3  -1.55159	3.312831e-01	4.710895e-01
1  -1.29414	3.312831e-01	4.804868e-01
3  -2.14928	3.256326e-01	4.892629e-01
1  -2.09214	3.256326e-01	4.904408e-01
1  -1.47128	3.298800e-01	4.838439e-01
1  -1.39729	3.298800e-01	4.615507e-01
1  -1.52861	3.288792e-01	4.631052e-01
2  -1.83809	3.288792e-01	4.807021e-01
1  -1.23617	3.288792e-01	4.909025e-01
2  -1.67852	3.259533e-01	4.954467e-01
2  -2.47712	3.105560e-01	5.193610e-01
2  -2.53614	3.139562e-01	5.140801e-01
1  -2.50493	3.113983e-01	5.180529e-01
4  -2.66244	3.113983e-01	4.986436e-01
1  -2.60257	3.113983e-01	4.973720e-01
2  -2.6677	3.127247e-01	4.953119e-01
2  -2.56113	3.107228e-01	4.984211e-01
2  -2.73856	3.161699e-01	4.899609e-01
1  -2.0391	3.274484e-01	4.724438e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2059 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000803 	for  Omega_m
           0.000595 	for  b1
--> Not computing covariance matrix
5  -2.11509	3.274484e-01	4.783677e-01
4  -2.90149	3.166540e-01	4.951330e-01
3  -2.05628	3.278941e-01	4.776755e-01
1  -0.960934	3.278941e-01	4.968159e-01
1  -2.20008	3.136867e-01	5.188820e-01
1  -1.01754	3.136867e-01	5.289250e-01
1  -0.632132	3.037847e-01	5.443043e-01
1  -2.04719	3.037847e-01	5.269291e-01
1  -2.67628	3.119353e-01	5.142699e-01
1  -2.86202	3.119353e-01	5.047628e-01
1  -2.92642	3.151093e-01	4.998332e-01
1  -2.55942	3.151093e-01	4.884098e-01
1  -1.46318	3.030600e-01	5.071241e-01
1  -1.88839	3.030600e-01	5.142998e-01
1  -2.67928	3.100328e-01	5.034701e-01
2  -2.68418	3.100328e-01	5.150754e-01
3  -2.62731	3.100328e-01	5.019957e-01
1  -1.98601	3.041195e-01	5.111800e-01
2  -1.416	3.041195e-01	5.028497e-01
1  -2.18759	3.041195e-01	5.182608e-01
1  2.80393	2.856399e-01	5.469623e-01
1  2.70288	2.856399e-01	5.513381e-01
1  -0.888347	2.969690e-01	5.337424e-01
2  2.58039	2.969690e-01	5.686656e-01
2  -0.613203	2.969690e-01	5.432522e-01
2  -0.785931	2.969690e-01	5.393221e-01
1  -0.79709	2.969690e-01	5.389775e-01
1  -0.779059	2.968887e-01	5.391023e-01
4  -0.776959	2.968887e-01	5.391689e-01
1  -0.867999	2.968887e-01	5.342583e-01
1  -1.2422	2.985937e-01	5.316102e-01
3  -0.755312	2.985937e-01	5.164130e-01
1  -1.34168	3.014188e-01	5.120251e-01
1  -0.537034	3.014188e-01	5.031153e-01
4  -0.277336	3.001672e-01	5.050593e-01
6  -1.99285	3.136950e-01	4.840486e-01
1  -2.06648	3.178212e-01	4.776400e-01
1  1.03411	3.178212e-01	4.563814e-01
1  2.20835	3.346565e-01	4.302337e-01
1  0.95482	3.346565e-01	4.380661e-01
1  -0.316929	3.219102e-01	4.578630e-01
2  -2.03869	3.219102e-01	4.723449e-01
1  -2.45163	3.219102e-01	4.786432e-01
1  -2.60679	3.178820e-01	4.848996e-01
1  -2.85956	3.178820e-01	4.919782e-01
2  -2.82066	3.190817e-01	4.901149e-01
1  -2.25095	3.263365e-01	4.788472e-01
1  -2.20449	3.263365e-01	4.755408e-01
2  -2.41287	3.242849e-01	4.787272e-01
1  -2.40617	3.243583e-01	4.786133e-01
1  -2.23988	3.243583e-01	4.924751e-01
1  -2.64618	3.091986e-01	5.160202e-01
3  -2.47371	3.091986e-01	5.013052e-01
2  -2.69295	3.127446e-01	4.957978e-01
3  -0.867091	2.986796e-01	5.176429e-01
3  -1.25068	2.986796e-01	5.275861e-01
1  -2.79464	3.104434e-01	5.093151e-01
1  -2.20897	3.104434e-01	5.233022e-01
1  -2.24143	3.147284e-01	5.166469e-01
2  -1.45688	3.147284e-01	5.239163e-01
1  -0.414863	3.147284e-01	5.309067e-01
1  -0.0308021	3.200308e-01	5.226712e-01
1  -0.700253	3.200308e-01	5.186559e-01
1  -0.890112	3.060891e-01	5.403095e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2091 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000645 	for  Omega_m
           0.000527 	for  b1
--> Not computing covariance matrix
2  -2.35197	3.060891e-01	5.221662e-01
2  -1.55421	3.060891e-01	4.981842e-01
3  -1.48502	3.060891e-01	4.974723e-01
1  -1.71889	3.080017e-01	4.945017e-01
2  -0.927686	3.080017e-01	4.875646e-01
1  -0.908165	3.080017e-01	4.874164e-01
1  1.4346	2.961287e-01	5.058569e-01
2  0.852836	2.961287e-01	5.101617e-01
1  -0.681671	2.961287e-01	5.363239e-01
1  -1.5163	3.000403e-01	5.302487e-01
2  -1.53207	3.000403e-01	5.287628e-01
2  -1.52088	3.000403e-01	5.299144e-01
1  -1.49659	3.000403e-01	5.236422e-01
1  -2.70482	3.091070e-01	5.095602e-01
1  -2.62603	3.091070e-01	5.054117e-01
5  -2.87135	3.141901e-01	4.975170e-01
3  -2.0151	3.141901e-01	4.833098e-01
1  -2.06906	3.167435e-01	4.793439e-01
1  -2.78693	3.167435e-01	4.903226e-01
1  -2.78804	3.155237e-01	4.922172e-01
1  -1.95374	3.155237e-01	4.802270e-01
2  -1.97098	3.166675e-01	4.784505e-01
1  -1.86966	3.217327e-01	4.705834e-01
1  -2.48828	3.217327e-01	4.794636e-01
1  -1.39472	3.020913e-01	5.099697e-01
3  -1.61447	3.020913e-01	5.340238e-01
1  -2.43264	3.134833e-01	5.163304e-01
2  -1.86609	3.134833e-01	5.226029e-01
1  -2.76205	3.134833e-01	4.956613e-01
1  -2.77185	3.182285e-01	4.882912e-01
1  -2.69138	3.182285e-01	4.862124e-01
2  -1.94272	3.280911e-01	4.708944e-01
1  -1.29077	3.324771e-01	4.640823e-01
1  0.400189	3.324771e-01	4.936221e-01
1  -0.843584	3.255746e-01	5.043427e-01
1  -1.57876	3.255746e-01	4.977532e-01
1  -2.11445	3.206739e-01	5.053647e-01
3  -2.04365	3.206739e-01	5.061761e-01
2  -2.24148	3.177652e-01	5.106937e-01
1  -2.18049	3.188235e-01	5.090501e-01
2  -1.77599	3.188235e-01	5.131624e-01
1  -2.61462	3.188235e-01	5.027500e-01
4  -2.59919	3.093197e-01	5.175108e-01
1  -1.3429	3.299919e-01	4.854038e-01
1  -1.75673	3.299919e-01	4.727339e-01
2  -2.59894	3.088650e-01	5.055471e-01
1  -2.66019	3.096490e-01	5.043294e-01
4  -2.73347	3.096490e-01	5.123836e-01
2  -2.66257	3.096490e-01	5.156907e-01
2  -1.22142	3.096490e-01	5.336436e-01
2  0.570084	3.096490e-01	5.446383e-01
3  -1.37796	3.096490e-01	4.872035e-01
1  -1.7508	3.171903e-01	4.754908e-01
2  -2.67028	3.171903e-01	4.870221e-01
1  -2.88445	3.171903e-01	4.990762e-01
3  -2.91385	3.152038e-01	5.021616e-01
1  -2.79122	3.152038e-01	5.070422e-01
1  -2.79371	3.137401e-01	5.093155e-01
1  -2.88884	3.137401e-01	4.995347e-01
2  -2.02034	3.281628e-01	4.771341e-01
1  -2.32301	3.257308e-01	4.809113e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2121 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000764 	for  Omega_m
           0.000490 	for  b1
--> Not computing covariance matrix
1  -2.29947	3.257308e-01	4.779369e-01
1  -2.67157	3.213532e-01	4.847360e-01
1  -2.67077	3.213532e-01	4.929206e-01
1  -2.27936	3.254645e-01	4.865352e-01
1  -2.3525	3.254645e-01	4.813311e-01
3  -2.58918	3.082438e-01	5.080774e-01
1  -1.60671	3.082438e-01	5.321084e-01
1  -1.61086	3.083226e-01	5.319860e-01
1  -1.73897	3.083226e-01	5.307556e-01
2  -1.63693	3.067373e-01	5.332178e-01
2  -1.78027	3.091703e-01	5.294390e-01
1  -1.46707	3.207821e-01	5.114042e-01
1  -2.45094	3.207821e-01	4.792357e-01
1  -2.15771	3.084892e-01	4.983283e-01
1  -2.29819	3.084892e-01	5.004169e-01
2  -2.51349	3.112459e-01	4.961354e-01
5  -2.667	3.159174e-01	4.888798e-01
2  -2.90667	3.159174e-01	4.961626e-01
1  -2.49353	3.159174e-01	5.112305e-01
1  -1.77972	3.027644e-01	5.316591e-01
1  -1.82881	3.027644e-01	5.305960e-01
1  -2.57681	3.122910e-01	5.157997e-01
1  -2.17342	3.122910e-01	4.889436e-01
2  -1.47479	3.052500e-01	4.998794e-01
1  -2.28395	3.151964e-01	4.844312e-01
1  -2.92038	3.151964e-01	4.984553e-01
1  -2.91698	3.161627e-01	4.969545e-01
1  -2.64212	3.161627e-01	5.083587e-01
1  -2.4147	3.075172e-01	5.217864e-01
1  -2.55371	3.075172e-01	5.171190e-01
2  -2.84893	3.156412e-01	5.045012e-01
1  -2.62879	3.084431e-01	5.156808e-01
3  -2.64797	3.084431e-01	5.101053e-01
2  -1.55543	3.310270e-01	4.750291e-01
2  -2.00916	3.280748e-01	4.796144e-01
2  -2.38029	3.250826e-01	4.842616e-01
4  -2.36982	3.251785e-01	4.841127e-01
1  -2.8543	3.187690e-01	4.940677e-01
1  -2.42179	3.187690e-01	4.807697e-01
1  -2.34519	3.126706e-01	4.902414e-01
1  -2.26756	3.126706e-01	4.892466e-01
1  -1.91633	3.081390e-01	4.962849e-01
3  -2.55824	3.081390e-01	5.074248e-01
2  -2.71818	3.101805e-01	5.042540e-01
2  -2.80971	3.118360e-01	5.016829e-01
2  -2.89408	3.154172e-01	4.961207e-01
3  -2.82199	3.121191e-01	5.012432e-01
1  -2.33515	3.121191e-01	5.196156e-01
1  -2.02114	3.207773e-01	5.061682e-01
1  -1.66425	3.207773e-01	5.097122e-01
1  -1.49109	3.224988e-01	5.070384e-01
3  -1.90001	3.224988e-01	5.030340e-01
1  -0.503381	3.317356e-01	4.886879e-01
1  -1.08983	3.317356e-01	4.818215e-01
2  0.268422	3.380385e-01	4.720322e-01
1  -1.43642	3.297777e-01	4.848625e-01
1  -1.55625	3.297777e-01	4.827572e-01
1  -1.85693	3.278359e-01	4.857731e-01
3  -2.03833	3.278359e-01	4.739140e-01
2  -2.77632	3.132694e-01	4.965379e-01
2  -1.39288	3.321551e-01	4.672056e-01
1  -1.05855	3.340230e-01	4.643045e-01
1  -1.06474	3.340230e-01	4.654211e-01
2  -2.67825	3.213686e-01	4.850752e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2154 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000851 	for  Omega_m
           0.000504 	for  b1
--> Not computing covariance matrix
3  -2.85002	3.151304e-01	4.947642e-01
1  -2.70748	3.151304e-01	5.090882e-01
1  -2.65375	3.109289e-01	5.156136e-01
1  -2.80195	3.109289e-01	5.104366e-01
1  -2.81572	3.112420e-01	5.099504e-01
4  -2.8043	3.112420e-01	5.106293e-01
1  -2.75578	3.112420e-01	5.126395e-01
2  -2.75009	3.177428e-01	5.025428e-01
1  -2.79191	3.124063e-01	5.108311e-01
4  -2.77807	3.124063e-01	5.112572e-01
2  -2.66585	3.124063e-01	4.960507e-01
1  -2.83858	3.124063e-01	5.010283e-01
2  -2.66095	3.092897e-01	5.058688e-01
1  -2.86391	3.131681e-01	4.998451e-01
1  -2.73484	3.131681e-01	4.957330e-01
1  -2.3431	3.249534e-01	4.774286e-01
1  -2.34024	3.249534e-01	4.872366e-01
1  -2.53041	3.230810e-01	4.901447e-01
1  -2.55986	3.230810e-01	4.826584e-01
1  -2.738	3.204102e-01	4.868066e-01
1  -2.7606	3.204102e-01	4.881890e-01
1  -2.8049	3.118236e-01	5.015253e-01
1  -2.81148	3.118236e-01	5.104113e-01
1  -2.85259	3.137656e-01	5.073952e-01
1  -2.01452	3.137656e-01	5.207119e-01
1  -1.73035	3.198709e-01	5.112294e-01
1  -2.47309	3.198709e-01	5.025136e-01
3  -0.942481	3.316499e-01	4.842192e-01
2  -1.31987	3.316499e-01	4.622350e-01
1  -0.337998	3.316499e-01	4.494250e-01
2  0.658508	3.375580e-01	4.402487e-01
1  -1.3234	3.188875e-01	4.692468e-01
1  -2.80582	3.188875e-01	4.973413e-01
2  -2.52825	3.229090e-01	4.910954e-01
1  -2.33536	3.248195e-01	4.881279e-01
2  -2.39485	3.248195e-01	4.856280e-01
1  -2.31724	3.248195e-01	4.886899e-01
1  -2.85512	3.172610e-01	5.004295e-01
1  -2.49936	3.172610e-01	4.839506e-01
1  -2.47225	3.144592e-01	4.883022e-01
1  -2.616	3.144592e-01	4.905871e-01
2  -2.55432	3.202878e-01	4.815345e-01
1  -2.61928	3.146069e-01	4.903577e-01
1  -2.68848	3.146069e-01	4.916538e-01
3  -2.61886	3.201724e-01	4.830098e-01
1  -2.6626	3.201724e-01	4.841132e-01
2  -1.97326	3.048032e-01	5.079840e-01
2  -2.5899	3.108822e-01	4.985424e-01
1  -2.64057	3.206324e-01	4.833989e-01
2  -2.51777	3.206324e-01	4.805798e-01
1  -2.38136	3.206324e-01	5.019135e-01
1  -2.60499	3.113779e-01	5.162870e-01
1  -2.54029	3.113779e-01	5.174785e-01
5  -2.36259	3.197874e-01	5.044172e-01
1  -2.37917	3.197874e-01	4.789789e-01
2  1.01214	3.426290e-01	4.435026e-01
1  -0.0968636	3.378590e-01	4.509111e-01
2  0.688843	3.378590e-01	4.774743e-01
2  0.166809	3.378590e-01	4.715135e-01
1  0.628599	3.378590e-01	4.768900e-01
4  -1.18285	3.292318e-01	4.902893e-01
2  -2.19014	3.214646e-01	5.023529e-01
1  -2.09654	3.224583e-01	5.008096e-01
3  -2.34963	3.224583e-01	4.764940e-01
1  -2.10002	3.255382e-01	4.717104e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2186 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001115 	for  Omega_m
           0.000686 	for  b1
--> Not computing covariance matrix
1  -2.18565	3.255382e-01	4.735648e-01
1  -2.50024	3.215371e-01	4.797791e-01
1  -2.60315	3.215371e-01	4.823679e-01
1  -2.74559	3.181687e-01	4.875996e-01
2  -2.57926	3.181687e-01	5.050356e-01
2  -2.87452	3.181687e-01	4.936302e-01
3  -2.87043	3.181687e-01	4.961598e-01
1  -2.62956	3.081064e-01	5.117880e-01
2  -2.60499	3.081064e-01	5.096464e-01
1  -2.53571	3.081064e-01	5.188664e-01
1  -2.51285	3.078114e-01	5.193247e-01
3  -2.58468	3.078114e-01	5.104923e-01
1  -2.34274	3.055420e-01	5.140170e-01
3  -2.12776	3.055420e-01	5.078469e-01
1  -2.77769	3.143476e-01	4.941705e-01
1  -1.82617	3.143476e-01	4.811517e-01
5  -1.86952	3.159376e-01	4.786822e-01
2  -2.83439	3.159376e-01	5.043792e-01
2  0.123968	3.159376e-01	4.644550e-01
1  -0.379722	3.159376e-01	4.674555e-01
1  -0.188055	3.122954e-01	4.731123e-01
1  -2.76695	3.122954e-01	5.116771e-01
1  -2.75191	3.169031e-01	5.045208e-01
1  -0.404932	3.169031e-01	5.268963e-01
1  -0.199628	3.035762e-01	5.475949e-01
1  0.247833	3.035762e-01	5.504769e-01
2  -0.104459	3.109743e-01	5.389866e-01
2  0.0868245	3.165952e-01	5.302565e-01
2  1.66316	3.284578e-01	5.118321e-01
1  0.267455	3.188432e-01	5.267650e-01
1  -1.46359	3.188432e-01	5.157734e-01
1  0.440521	3.320033e-01	4.953338e-01
3  -1.41548	3.320033e-01	4.671810e-01
2  -2.62663	3.216739e-01	4.832240e-01
1  -1.55868	3.311316e-01	4.685347e-01
3  -1.54852	3.311316e-01	4.743073e-01
2  -2.37154	3.057770e-01	5.136868e-01
3  -2.83623	3.114558e-01	5.048668e-01
1  -2.70238	3.114558e-01	5.140707e-01
1  -2.70717	3.116054e-01	5.138384e-01
1  -2.4882	3.116054e-01	4.948009e-01
1  -2.45881	3.111204e-01	4.955542e-01
1  -2.58371	3.111204e-01	5.169393e-01
5  -2.25272	3.060644e-01	5.247919e-01
4  -1.87194	3.060644e-01	5.019581e-01
1  -2.0711	3.060644e-01	5.048434e-01
1  -2.40011	3.091788e-01	5.000063e-01
1  -2.69329	3.091788e-01	5.080113e-01
3  -2.87271	3.182754e-01	4.938830e-01
2  -2.8113	3.182754e-01	4.895977e-01
1  -2.2104	3.182754e-01	5.099394e-01
1  -2.19817	3.184839e-01	5.096155e-01
2  -2.79916	3.184839e-01	4.989845e-01
1  -2.6826	3.184839e-01	5.022256e-01
1  -2.30331	3.054488e-01	5.224711e-01
1  -2.29206	3.054488e-01	5.228901e-01
1  -2.47597	3.213568e-01	4.981827e-01
2  -1.85351	3.213568e-01	4.708124e-01
1  -2.48367	3.213568e-01	4.980321e-01
1  -2.15904	3.246524e-01	4.929135e-01
1  -2.43692	3.246524e-01	4.821939e-01
1  -2.84743	3.186283e-01	4.915502e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2216 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000873 	for  Omega_m
           0.000511 	for  b1
--> Not computing covariance matrix
3  -1.96974	3.186283e-01	5.117467e-01
3  -2.14432	3.118158e-01	5.223275e-01
1  -2.06585	3.118158e-01	4.887798e-01
2  -1.75798	3.081828e-01	4.944225e-01
4  -1.46349	3.289570e-01	4.621570e-01
1  -1.70416	3.268760e-01	4.653892e-01
5  -2.09701	3.268760e-01	4.730048e-01
1  -1.73601	3.296688e-01	4.686672e-01
1  -1.28986	3.296688e-01	4.599052e-01
4  -1.76283	3.253749e-01	4.665741e-01
4  -1.49754	3.279832e-01	4.625231e-01
1  -0.880815	3.324881e-01	4.555263e-01
2  -0.976115	3.324881e-01	4.569554e-01
2  -1.34607	3.324881e-01	4.684480e-01
2  2.3185	3.324881e-01	4.313657e-01
1  0.89795	3.324881e-01	4.395960e-01
1  0.98996	3.331355e-01	4.385905e-01
1  2.16163	3.331355e-01	4.316455e-01
1  1.20868	3.201985e-01	4.517386e-01
1  0.135133	3.201985e-01	4.575098e-01
1  0.216586	3.230690e-01	4.530515e-01
2  1.27913	3.230690e-01	4.472433e-01
1  2.78979	3.230690e-01	4.401810e-01
2  2.75859	3.188933e-01	4.466665e-01
1  2.82081	3.166560e-01	4.501413e-01
2  -2.48754	3.166560e-01	4.846851e-01
1  -2.36068	3.166560e-01	5.115635e-01
2  -2.42064	3.136695e-01	5.162020e-01
2  -2.14532	3.203364e-01	5.058473e-01
2  -0.248228	3.332682e-01	4.857623e-01
2  -2.20205	3.195796e-01	5.070227e-01
2  -1.20736	3.281099e-01	4.937739e-01
2  -1.87495	3.231909e-01	5.014138e-01
1  -0.992526	3.293950e-01	4.917779e-01
1  -1.43844	3.293950e-01	4.619394e-01
3  -2.21333	3.201393e-01	4.763149e-01
1  -2.77351	3.201393e-01	4.885088e-01
2  -2.88411	3.165667e-01	4.940576e-01
1  -2.15136	3.046475e-01	5.125699e-01
1  -2.11465	3.046475e-01	5.115866e-01
1  -2.57731	3.229221e-01	4.832034e-01
1  -2.27425	3.229221e-01	4.968338e-01
1  -2.19743	3.049042e-01	5.248183e-01
1  -1.45419	3.049042e-01	5.007358e-01
1  -0.1794	2.982993e-01	5.109942e-01
1  -1.14926	2.982993e-01	5.269558e-01
2  -2.59293	3.076966e-01	5.123604e-01
1  -2.76901	3.100009e-01	5.087815e-01
1  -2.49497	3.100009e-01	4.992473e-01
3  -2.7084	3.179522e-01	4.868978e-01
1  -2.3084	3.179522e-01	5.094747e-01
1  -2.42463	3.140280e-01	5.155695e-01
3  -2.53526	3.140280e-01	5.139780e-01
1  -2.53536	3.140028e-01	5.140171e-01
1  -2.48836	3.140028e-01	5.147187e-01
1  -2.35612	3.183522e-01	5.079636e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2244 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000780 	for  Omega_m
           0.000465 	for  b1
--> Not computing covariance matrix
11  -2.40374	3.183522e-01	5.073186e-01
2  -1.98637	3.234112e-01	4.994611e-01
1  -1.91135	3.240725e-01	4.984340e-01
1  -1.58174	3.240725e-01	5.020503e-01
1  -2.01097	3.197557e-01	5.087550e-01
2  -0.687434	3.197557e-01	5.193329e-01
1  -2.23702	3.197557e-01	5.061661e-01
2  -2.28253	3.190871e-01	5.072045e-01
1  -2.27684	3.080428e-01	5.243580e-01
2  -2.47834	3.080428e-01	5.204131e-01
2  -2.09876	3.080428e-01	5.269344e-01
3  -2.0857	3.080428e-01	5.271045e-01
1  -2.16867	3.095678e-01	5.247359e-01
1  -2.14431	3.095678e-01	5.250387e-01
1  -2.12316	3.172543e-01	5.131004e-01
1  -2.31591	3.172543e-01	5.108867e-01
2  -2.39929	3.127508e-01	5.178813e-01
3  -2.37222	3.156789e-01	5.133336e-01
2  -2.59883	3.156789e-01	5.100579e-01
1  -2.70217	3.156789e-01	4.899775e-01
1  -2.0945	3.267792e-01	4.727372e-01
1  -2.17743	3.267792e-01	4.760926e-01
3  -2.82727	3.171233e-01	4.910896e-01
1  -2.76485	3.171233e-01	4.892458e-01
1  -1.72861	3.030462e-01	5.111096e-01
2  -2.04216	3.030462e-01	5.229605e-01
1  -1.93758	3.030462e-01	5.283667e-01
2  -2.38421	3.069760e-01	5.222633e-01
2  -2.34963	3.065928e-01	5.228584e-01
2  -2.44477	3.205055e-01	5.012498e-01
2  -2.68806	3.144239e-01	5.106955e-01
2  -1.40047	2.997443e-01	5.334951e-01
5  -2.3067	3.061440e-01	5.235554e-01
1  -2.35837	3.061440e-01	5.220530e-01
1  -2.73468	3.162177e-01	5.064071e-01
1  -2.64179	3.162177e-01	5.082532e-01
2  -2.1238	3.237494e-01	4.965554e-01
2  -2.13092	3.236844e-01	4.966564e-01
1  -1.75888	3.266670e-01	4.920239e-01
1  -1.18713	3.266670e-01	4.984102e-01
1  -0.926223	3.283146e-01	4.958512e-01
1  -1.16869	3.283146e-01	4.935133e-01
5  -1.35536	3.271255e-01	4.953602e-01
3  -0.105826	3.271255e-01	5.054174e-01
1  -1.3438	3.091761e-01	5.332954e-01
3  -2.53466	3.091761e-01	5.026724e-01
1  -2.80987	3.155080e-01	4.928381e-01
1  -2.89656	3.155080e-01	4.961073e-01
1  -2.78657	3.199814e-01	4.891594e-01
3  -2.54249	3.199814e-01	5.009920e-01
1  -0.706662	3.333755e-01	4.801891e-01
4  0.491299	3.333755e-01	4.914856e-01
2  -1.00198	3.333755e-01	4.752149e-01
1  -1.18081	3.333755e-01	4.684696e-01
2  -0.78129	3.354192e-01	4.652954e-01
1  -1.08251	3.338969e-01	4.676596e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2274 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001049 	for  Omega_m
           0.000498 	for  b1
--> Not computing covariance matrix
3  -1.03655	3.338969e-01	4.617124e-01
2  -1.43104	3.018549e-01	5.114784e-01
1  -2.54263	3.110257e-01	4.972348e-01
1  -1.39013	3.110257e-01	4.841670e-01
3  -0.813222	3.058507e-01	4.922046e-01
2  -0.726778	3.058507e-01	4.915350e-01
1  -1.58484	3.058507e-01	4.992236e-01
6  -1.61681	3.060884e-01	4.988544e-01
1  -2.26296	3.137090e-01	4.870184e-01
1  -2.75635	3.137090e-01	4.950078e-01
3  -2.73791	3.131173e-01	4.959268e-01
1  -2.74144	3.131173e-01	5.114618e-01
4  -2.5978	3.092049e-01	5.175383e-01
2  -2.62921	3.097500e-01	5.166917e-01
1  -2.03176	3.254051e-01	4.923769e-01
3  -0.617224	3.254051e-01	5.064536e-01
1  -1.05355	3.220277e-01	5.116992e-01
1  -1.08036	3.220277e-01	5.115007e-01
1  -0.759054	3.007530e-01	5.445435e-01
1  -0.127215	3.007530e-01	5.500140e-01
1  -0.865329	3.137840e-01	5.297749e-01
1  -1.15444	3.137840e-01	5.278074e-01
5  -0.206239	3.248180e-01	5.106701e-01
2  -1.62587	3.248180e-01	4.994892e-01
1  -2.14724	3.248180e-01	4.925204e-01
2  -2.19267	3.244244e-01	4.931318e-01
1  -2.74761	3.119524e-01	5.125026e-01
2  -1.76522	3.119524e-01	5.259188e-01
4  -2.40673	3.119524e-01	5.188717e-01
1  -2.59181	3.119524e-01	5.159352e-01
2  -2.61178	3.133250e-01	5.138032e-01
2  -2.27764	3.214549e-01	5.011764e-01
1  -2.47871	3.091449e-01	5.202955e-01
1  -2.68359	3.091449e-01	5.076362e-01
4  -2.794	3.108302e-01	5.050187e-01
1  -2.85526	3.121331e-01	5.029951e-01
2  -2.6171	3.121331e-01	5.152594e-01
3  -2.85665	3.121331e-01	5.080031e-01
2  -2.7143	3.204577e-01	4.950738e-01
1  -2.3101	3.249972e-01	4.880232e-01
1  -2.39828	3.249972e-01	4.809612e-01
5  -2.88041	3.144398e-01	4.973585e-01
1  -2.92225	3.144398e-01	5.020448e-01
2  -2.90217	3.131363e-01	5.040693e-01
2  -2.88688	3.125629e-01	5.049598e-01
1  -2.238	3.045067e-01	5.174723e-01
1  -1.54538	3.045067e-01	5.355020e-01
1  -1.97723	3.123684e-01	5.232916e-01
3  -2.83659	3.123684e-01	5.091746e-01
1  -2.67554	3.203582e-01	4.967654e-01
1  -2.6624	3.203582e-01	4.840594e-01
2  -2.32863	3.249583e-01	4.769147e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2299 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000769 	for  Omega_m
           0.000330 	for  b1
--> Not computing covariance matrix
2  -2.3165	3.250827e-01	4.767215e-01
4  -2.65919	3.204249e-01	4.839558e-01
1  -2.69737	3.127562e-01	4.958664e-01
1  -2.89171	3.127562e-01	5.050072e-01
1  -2.92281	3.150352e-01	5.014676e-01
2  -2.46203	3.150352e-01	5.133256e-01
1  -2.69716	3.150352e-01	5.094669e-01
1  -2.64028	3.108395e-01	5.159834e-01
3  -2.27561	3.108395e-01	5.220031e-01
2  -2.30826	3.124855e-01	5.194466e-01
1  -2.29307	3.115162e-01	5.209520e-01
3  -2.76776	3.115162e-01	5.121475e-01
1  -2.77835	3.118378e-01	5.116480e-01
1  -2.6719	3.118378e-01	5.144615e-01
1  -2.49417	3.200212e-01	5.017513e-01
2  -2.77939	3.200212e-01	4.937758e-01
3  -2.75675	3.200212e-01	4.950785e-01
1  -2.29124	3.048464e-01	5.186474e-01
1  -1.78371	3.048464e-01	5.324844e-01
1  -2.17274	3.105619e-01	5.236072e-01
1  -1.2961	3.105619e-01	5.318206e-01
1  -1.24156	3.087393e-01	5.346515e-01
1  -1.76357	3.087393e-01	5.300773e-01
2  -1.21515	3.025833e-01	5.396384e-01
4  -1.69017	3.074539e-01	5.320737e-01
2  -1.09623	3.241256e-01	5.061801e-01
1  -1.39725	3.041015e-01	5.372805e-01
1  -1.74513	3.041015e-01	5.330339e-01
2  -2.24662	3.149873e-01	5.161268e-01
2  -2.1258	3.180748e-01	5.113313e-01
2  -0.750958	2.978592e-01	5.427291e-01
1  -1.8907	3.054599e-01	5.309242e-01
2  -1.04301	3.054599e-01	5.396871e-01
1  0.321597	3.054599e-01	5.489074e-01
3  0.355434	3.049897e-01	5.496376e-01
1  0.281638	3.049897e-01	5.492103e-01
1  1.08678	3.240327e-01	5.196337e-01
1  1.30505	3.240327e-01	5.206842e-01
1  1.47075	3.250768e-01	5.190624e-01
2  0.705968	3.250768e-01	5.152635e-01
4  0.197472	3.250768e-01	5.124617e-01
2  -1.89768	3.250768e-01	4.954843e-01
2  1.22472	3.250768e-01	5.178865e-01
1  0.810443	3.250768e-01	5.158090e-01
2  0.185916	3.204047e-01	5.230656e-01
1  -0.143767	3.166202e-01	5.289434e-01
1  -2.50004	3.166202e-01	5.097307e-01
1  -2.55004	3.138241e-01	5.140736e-01
1  -2.80231	3.138241e-01	5.089602e-01
1  -2.73055	3.178981e-01	5.026327e-01
1  -2.8852	3.178981e-01	4.954829e-01
4  -2.30101	3.051137e-01	5.153390e-01
1  -1.87169	3.021698e-01	5.199112e-01
1  -1.13793	3.021698e-01	5.064828e-01
1  -1.85535	3.069052e-01	4.991280e-01
1  -2.50366	3.069052e-01	5.123898e-01
1  -2.40868	3.060308e-01	5.137480e-01
2  -2.38533	3.060308e-01	5.207582e-01
2  -2.01332	3.060308e-01	5.290602e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2329 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000601 	for  Omega_m
           0.000249 	for  b1
--> Not computing covariance matrix
7  -2.38045	3.060308e-01	5.122814e-01
1  -2.59361	3.081025e-01	5.090638e-01
5  -2.44179	3.081025e-01	5.044026e-01
1  -2.81313	3.161712e-01	4.918707e-01
2  -2.88187	3.161712e-01	5.020380e-01
1  -2.86738	3.161712e-01	4.937417e-01
2  -2.10819	3.045857e-01	5.117357e-01
2  -2.82572	3.184797e-01	4.901563e-01
1  -2.4438	3.073618e-01	5.074239e-01
2  -1.9058	3.073618e-01	5.298111e-01
1  -1.56603	3.073618e-01	5.333719e-01
1  -1.53394	3.068886e-01	5.341071e-01
2  -1.96316	3.068886e-01	5.294162e-01
1  -2.05319	3.068886e-01	5.017668e-01
1  -1.93927	3.059646e-01	5.032018e-01
1  -2.18947	3.059646e-01	5.073519e-01
1  -2.80024	3.161263e-01	4.915694e-01
1  -2.65406	3.161263e-01	5.082144e-01
2  -2.47809	3.082418e-01	5.204601e-01
1  -1.15238	3.305558e-01	4.858032e-01
1  -0.998626	3.305558e-01	4.876872e-01
2  0.248388	3.365154e-01	4.784311e-01
1  0.456109	3.373797e-01	4.770885e-01
2  0.133916	3.373797e-01	4.733767e-01
1  0.610804	3.373797e-01	4.406525e-01
1  1.47989	3.414857e-01	4.342753e-01
2  0.753691	3.414857e-01	4.446668e-01
3  0.753332	3.414857e-01	4.446753e-01
1  -2.29777	3.208235e-01	4.767668e-01
2  -2.50676	3.208235e-01	4.802456e-01
5  -2.43423	3.208235e-01	4.789137e-01
2  -2.20372	3.243271e-01	4.734721e-01
1  -2.52953	3.158296e-01	4.866699e-01
2  -2.21377	3.158296e-01	4.824788e-01
1  -2.92171	3.158296e-01	4.998479e-01
1  -2.26024	3.259641e-01	4.841075e-01
1  -2.00282	3.259641e-01	4.700178e-01
3  -1.57354	3.295897e-01	4.643866e-01
1  -1.81404	3.295897e-01	4.751067e-01
1  -2.4636	3.243964e-01	4.831728e-01
1  0.304044	3.243964e-01	4.508696e-01
1  0.250025	3.148074e-01	4.657628e-01
2  -0.755027	3.148074e-01	4.719046e-01
1  -2.30688	3.148074e-01	4.854273e-01
2  -1.75863	3.071301e-01	4.973511e-01
1  -2.28723	3.198177e-01	4.776455e-01
1  -2.60541	3.198177e-01	5.002062e-01
1  -2.65396	3.096677e-01	5.159706e-01
1  -2.67825	3.096677e-01	5.048769e-01
1  -2.48375	3.241379e-01	4.824027e-01
1  -1.29437	3.241379e-01	5.045123e-01
1  -1.81419	3.070068e-01	5.311193e-01
1  -1.98182	3.070068e-01	5.291111e-01
2  -2.21195	3.138299e-01	5.185137e-01
4  -1.74224	3.044501e-01	5.330820e-01
2  -2.17029	3.104407e-01	5.237778e-01
1  -1.52378	3.026695e-01	5.358476e-01
2  -1.47322	3.026695e-01	5.365393e-01
2  -0.397351	3.026695e-01	5.468844e-01
1  -1.98007	3.026695e-01	5.243835e-01
1  -1.16241	2.981931e-01	5.313359e-01
1  -0.848337	2.981931e-01	5.417035e-01
4  -1.89266	3.051243e-01	5.309383e-01
1  -1.89081	3.051065e-01	5.309660e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2361 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000803 	for  Omega_m
           0.000322 	for  b1
--> Not computing covariance matrix
1  -2.26504	3.051065e-01	5.136246e-01
2  -2.59076	3.080918e-01	5.089878e-01
1  -2.8975	3.136707e-01	5.003231e-01
5  -1.74184	3.136707e-01	5.234075e-01
6  -1.64054	3.168019e-01	5.185442e-01
2  -1.74646	3.132634e-01	5.240401e-01
1  -1.12149	3.229045e-01	5.090659e-01
1  -2.36002	3.229045e-01	4.953529e-01
1  -2.02976	3.258389e-01	4.907955e-01
3  -1.26901	3.258389e-01	5.000578e-01
1  -2.13785	3.162802e-01	5.149039e-01
1  -2.92	3.162802e-01	4.981679e-01
2  -2.92493	3.146643e-01	5.006775e-01
1  -2.88185	3.124617e-01	5.040986e-01
1  -2.80432	3.124617e-01	4.995048e-01
1  -2.22852	3.054889e-01	5.103346e-01
1  -2.2938	3.054889e-01	5.122907e-01
1  -2.68763	3.094777e-01	5.060954e-01
2  -2.62709	3.094777e-01	5.167453e-01
1  -2.72763	3.094777e-01	5.085497e-01
2  -2.50114	3.068600e-01	5.126153e-01
2  -2.8454	3.189783e-01	4.937939e-01
1  -2.21184	3.044327e-01	5.163853e-01
2  -1.83398	3.044327e-01	5.317744e-01
1  -2.23789	3.044327e-01	5.199226e-01
3  -1.98367	3.026462e-01	5.226972e-01
1  -1.72712	3.026462e-01	5.129179e-01
1  -2.55886	3.227034e-01	4.817662e-01
1  -2.28964	3.227034e-01	4.753432e-01
1  -1.99348	3.261979e-01	4.699157e-01
2  -2.10545	3.261979e-01	4.877692e-01
1  -2.05836	3.261979e-01	4.888041e-01
1  -1.57922	3.294815e-01	4.837040e-01
2  -1.20618	3.294815e-01	4.891379e-01
2  -1.74323	3.294815e-01	4.683023e-01
2  -1.83305	3.294815e-01	4.747287e-01
1  -1.83371	3.294815e-01	4.744994e-01
2  -2.60484	3.085975e-01	5.069354e-01
1  -2.81334	3.194333e-01	4.901058e-01
2  -1.3622	3.194333e-01	5.152911e-01
1  -1.01032	3.194333e-01	5.178720e-01
3  -1.3322	3.119467e-01	5.294998e-01
1  -1.38433	3.119467e-01	5.290998e-01
3  -1.27461	3.164031e-01	5.221783e-01
1  -2.90276	3.164031e-01	4.953870e-01
4  -2.44058	3.067392e-01	5.103964e-01
1  -2.17335	3.269936e-01	4.789384e-01
1  -2.08373	3.269936e-01	4.843227e-01
2  -2.64518	3.216448e-01	4.926302e-01
1  -2.89715	3.162515e-01	5.010068e-01
2  -1.99112	3.162515e-01	5.164609e-01
2  -2.88835	3.162515e-01	5.015161e-01
1  -2.75057	3.162515e-01	5.059770e-01
1  -1.40876	3.299020e-01	4.847758e-01
1  -0.720231	3.299020e-01	4.927475e-01
3  -2.23	3.102891e-01	5.232093e-01
1  -2.76416	3.102891e-01	5.059686e-01
1  -2.91898	3.157349e-01	4.975105e-01
3  -2.63682	3.157349e-01	5.092974e-01
1  -1.68401	3.015030e-01	5.314017e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2391 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001076 	for  Omega_m
           0.000382 	for  b1
--> Not computing covariance matrix
2  -1.69226	3.015030e-01	5.185134e-01
1  -1.47083	3.015030e-01	5.136938e-01
1  -2.20635	3.063484e-01	5.061681e-01
1  -1.31546	3.063484e-01	4.951003e-01
2  -2.00512	3.150883e-01	4.815260e-01
1  -2.0065	3.151422e-01	4.814423e-01
4  -2.34985	3.151422e-01	4.853546e-01
2  -1.69081	3.151422e-01	4.784463e-01
1  -2.06882	3.151422e-01	5.177701e-01
2  -1.94502	3.180356e-01	5.132763e-01
1  -0.637754	3.290164e-01	4.962215e-01
2  -1.27506	3.290164e-01	4.899719e-01
1  -1.71396	3.290164e-01	4.831988e-01
1  -2.05114	3.266781e-01	4.868306e-01
1  -2.20975	3.266781e-01	4.801602e-01
2  -2.82739	3.115645e-01	5.036340e-01
1  -1.64024	3.306690e-01	4.739618e-01
1  -1.51438	3.306690e-01	4.648349e-01
1  -1.44789	3.311070e-01	4.641546e-01
1  0.67416	3.311070e-01	4.420069e-01
2  -0.0757847	3.161853e-01	4.651825e-01
2  0.227323	3.268806e-01	4.485711e-01
1  -0.0896717	3.211119e-01	4.575308e-01
1  0.221811	3.211119e-01	4.556817e-01
1  0.216055	3.208356e-01	4.561109e-01
1  -2.26336	3.208356e-01	4.762669e-01
1  -1.98824	3.091180e-01	4.944659e-01
1  -2.64522	3.091180e-01	5.060427e-01
1  -2.88836	3.143986e-01	4.978412e-01
6  -2.80728	3.143986e-01	5.079759e-01
3  -2.79028	3.143986e-01	5.084373e-01
3  -2.28053	3.052166e-01	5.226983e-01
1  -2.22529	3.052166e-01	5.116293e-01
1  -1.56509	3.010295e-01	5.181324e-01
1  -1.71306	3.010295e-01	5.269143e-01
2  -2.71741	3.096780e-01	5.134820e-01
1  -2.83136	3.169277e-01	5.022221e-01
1  -2.90858	3.169277e-01	4.975087e-01
3  -2.5491	3.072765e-01	5.124985e-01
1  -2.29907	3.072765e-01	5.044784e-01
1  -2.2757	3.255171e-01	4.761481e-01
1  -2.3294	3.255171e-01	4.787430e-01
1  -2.57955	3.228053e-01	4.829548e-01
1  -2.5443	3.228053e-01	4.910088e-01
1  -1.17453	3.326155e-01	4.757722e-01
1  -1.04109	3.326155e-01	4.785262e-01
2  -1.95801	3.270614e-01	4.871525e-01
1  -2.7584	3.183596e-01	5.006676e-01
1  -2.54061	3.183596e-01	4.831437e-01
1  -1.93546	3.272239e-01	4.693762e-01
2  -1.76225	3.272239e-01	4.899526e-01
1  -2.06997	3.272239e-01	4.834012e-01
2  -2.78379	3.197118e-01	4.950686e-01
2  -2.19201	3.262807e-01	4.848660e-01
1  -0.894863	2.970734e-01	5.302292e-01
1  -0.647564	2.970734e-01	5.228195e-01
2  -2.74141	3.114821e-01	5.004407e-01
3  -2.19756	3.266796e-01	4.768368e-01
1  -1.36656	3.266796e-01	4.613867e-01
1  -0.326811	3.343576e-01	4.494616e-01
2  -0.571995	3.343576e-01	4.777034e-01
1  -0.162137	3.343576e-01	4.476204e-01
1  -1.29386	3.254506e-01	4.614544e-01
1  -2.34396	3.254506e-01	4.833110e-01
2  -2.32737	3.255978e-01	4.830823e-01
2  -2.88331	3.126239e-01	5.032326e-01
1  -2.84878	3.189227e-01	4.934497e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2424 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000917 	for  Omega_m
           0.000302 	for  b1
--> Not computing covariance matrix
1  -2.72649	3.189227e-01	4.864791e-01
3  -1.92195	3.285291e-01	4.715590e-01
1  -1.0872	3.285291e-01	4.936496e-01
1  -1.97208	3.217928e-01	5.041120e-01
3  -2.01227	3.217928e-01	5.036561e-01
1  -1.83279	3.235115e-01	5.009868e-01
2  -2.46445	3.235115e-01	4.904015e-01
1  -2.54557	3.235115e-01	4.841788e-01
1  -2.81261	3.195466e-01	4.903368e-01
1  -2.42065	3.195466e-01	5.041822e-01
1  -2.07057	3.235347e-01	4.979881e-01
1  -0.831681	3.235347e-01	5.096616e-01
1  -1.55917	3.133229e-01	5.255220e-01
1  -1.86746	3.133229e-01	5.228523e-01
3  -1.75072	3.082861e-01	5.306753e-01
1  -2.32815	3.082861e-01	5.234027e-01
1  -1.76561	3.027778e-01	5.319579e-01
3  -1.58495	3.027778e-01	5.099220e-01
1  -2.03451	3.057901e-01	5.052434e-01
1  -1.86898	3.057901e-01	5.311264e-01
1  -2.19267	3.144849e-01	5.176221e-01
1  -1.67703	3.144849e-01	5.225663e-01
1  -1.05986	3.229564e-01	5.094089e-01
1  -2.51499	3.229564e-01	4.804613e-01
1  -2.77161	3.147696e-01	4.931765e-01
2  -2.89618	3.147696e-01	4.974511e-01
1  -1.90053	3.147696e-01	4.810701e-01
1  -1.80639	3.126138e-01	4.844184e-01
1  -2.8313	3.126138e-01	5.092821e-01
1  -2.8534	3.143426e-01	5.065970e-01
1  -2.02643	3.143426e-01	5.196155e-01
1  -1.97453	3.096512e-01	5.269019e-01
1  -1.28019	3.096512e-01	5.331876e-01
1  -1.20476	3.078349e-01	5.360086e-01
3  -1.27006	3.078349e-01	5.354817e-01
1  -0.998916	3.043158e-01	5.409473e-01
3  -1.14401	3.043158e-01	5.396640e-01
2  -0.615971	3.002595e-01	5.459641e-01
1  -0.39827	2.989601e-01	5.479824e-01
1  0.534391	2.989601e-01	5.556017e-01
2  -0.0279695	3.031239e-01	5.491347e-01
1  -0.413199	3.087427e-01	5.404078e-01
2  -2.54589	3.087427e-01	5.188587e-01
6  -2.44402	3.087427e-01	5.022073e-01
1  -1.31629	3.087427e-01	4.888601e-01
4  -1.52164	3.109697e-01	4.854013e-01
4  -1.6915	3.137211e-01	4.811280e-01
2  -1.31501	3.268312e-01	4.607661e-01
1  -1.72737	3.206492e-01	4.703676e-01
1  -2.12826	3.206492e-01	4.746923e-01
1  -2.19182	3.181419e-01	4.785866e-01
1  -1.70656	3.181419e-01	4.736098e-01
1  -1.66665	3.150084e-01	4.784766e-01
1  -1.08212	3.150084e-01	4.738258e-01
5  -1.10963	3.158877e-01	4.724601e-01
1  -2.92389	3.158877e-01	4.985364e-01
1  -2.8576	3.118391e-01	5.048246e-01
1  -2.59175	3.118391e-01	4.960121e-01
2  -2.55225	3.111453e-01	4.970895e-01
1  -2.66939	3.188650e-01	4.850997e-01
1  -2.04137	3.188650e-01	4.758791e-01
1  -1.94586	3.129780e-01	4.850224e-01
1  -2.88974	3.129780e-01	5.022052e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2456 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.001069 	for  Omega_m
           0.000321 	for  b1
--> Not computing covariance matrix
4  -2.78159	3.104798e-01	5.060854e-01
2  -2.78891	3.201693e-01	4.910361e-01
2  -2.92215	3.156683e-01	4.980269e-01
1  -2.8161	3.196465e-01	4.918480e-01
2  -2.17815	3.196465e-01	4.764452e-01
1  -2.31216	3.196465e-01	4.781776e-01
1  -1.82454	3.267355e-01	4.671674e-01
1  -1.83309	3.267355e-01	4.906836e-01
2  -2.0067	3.254224e-01	4.927231e-01
1  -1.37972	2.995081e-01	5.329718e-01
2  -1.27355	2.995081e-01	5.206845e-01
2  -0.843969	2.995081e-01	5.134619e-01
2  -0.752057	2.995081e-01	5.123245e-01
1  -1.11587	2.995081e-01	5.174780e-01
1  -1.50276	3.014654e-01	5.144381e-01
1  -1.79206	3.014654e-01	5.251956e-01
2  -0.944107	2.972143e-01	5.317982e-01
4  -2.85123	3.172073e-01	5.007462e-01
1  -2.87061	3.164111e-01	5.019828e-01
1  -2.73303	3.164111e-01	5.060376e-01
1  -2.60667	3.193720e-01	5.014389e-01
1  -2.72392	3.193720e-01	4.861564e-01
2  -2.65447	3.208834e-01	4.838090e-01
1  -2.76708	3.142400e-01	4.941272e-01
3  -1.25379	3.142400e-01	4.765299e-01
1  -1.16438	3.235992e-01	4.619937e-01
1  -2.23162	3.235992e-01	4.740511e-01
1  -0.729097	3.349058e-01	4.564903e-01
2  -0.877344	3.349058e-01	4.667604e-01
1  -0.555673	3.349058e-01	4.753270e-01
1  -0.99912	3.327269e-01	4.787112e-01
1  -1.28564	3.327269e-01	4.707956e-01
1  -1.71123	3.302237e-01	4.746833e-01
1  1.52192	3.302237e-01	5.066129e-01
1  -0.462609	3.144931e-01	5.310448e-01
1  0.182282	3.144931e-01	5.346590e-01
1  0.272644	3.161511e-01	5.320839e-01
2  -1.72329	3.161511e-01	5.191103e-01
2  -1.60868	3.161511e-01	5.200742e-01
1  -2.82898	3.161511e-01	5.040976e-01
1  -2.14151	3.256557e-01	4.893356e-01
1  -2.04702	3.256557e-01	4.911869e-01
1  -1.6329	3.007566e-01	5.298588e-01
1  -1.55412	3.007566e-01	5.327481e-01
5  -2.27141	3.061270e-01	5.244071e-01
2  -2.20702	3.061270e-01	5.257844e-01
1  -1.27576	3.061270e-01	5.371332e-01
2  -1.2207	3.054582e-01	5.381719e-01
1  -1.24834	3.057849e-01	5.376646e-01
1  -2.38375	3.057849e-01	5.143671e-01
3  -2.72007	3.212284e-01	4.903811e-01
2  -2.57803	3.212284e-01	4.963780e-01
1  -2.72246	3.212284e-01	4.899972e-01
1  -1.50649	3.001757e-01	5.226950e-01
1  -1.27251	3.001757e-01	5.376496e-01
1  -2.29372	3.095605e-01	5.230737e-01
1  -2.69195	3.095605e-01	5.058926e-01
1  -2.79703	3.112621e-01	5.032498e-01
1  -2.81984	3.112621e-01	5.096921e-01
3  -2.89124	3.153036e-01	5.034150e-01
1  -2.84072	3.153036e-01	5.054264e-01
5  -2.449	3.064721e-01	5.191430e-01
5  -2.25105	3.064721e-01	5.065711e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2486 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000822 	for  Omega_m
           0.000219 	for  b1
--> Not computing covariance matrix
2  -1.8278	3.033947e-01	5.113507e-01
2  -1.99573	3.045104e-01	5.096179e-01
1  -0.617459	2.973340e-01	5.207640e-01
3  -0.381056	2.973340e-01	5.472701e-01
1  -1.43952	3.040486e-01	5.368413e-01
1  -2.18576	3.040486e-01	5.195356e-01
2  -1.94943	3.024475e-01	5.220224e-01
3  -1.97299	3.025971e-01	5.217901e-01
3  -1.80156	3.025971e-01	5.147423e-01
1  -2.75209	3.113767e-01	5.011063e-01
1  -2.3363	3.113767e-01	4.931042e-01
1  -2.33583	3.221319e-01	4.763997e-01
2  -2.35538	3.221319e-01	4.979617e-01
1  -2.65048	3.221319e-01	4.854382e-01
3  -2.16387	3.270618e-01	4.777814e-01
1  -1.79824	3.270618e-01	4.900061e-01
1  -2.49394	3.206598e-01	4.999493e-01
1  -2.31968	3.206598e-01	5.027525e-01
3  -2.30522	3.069587e-01	5.240324e-01
1  -2.5185	3.069587e-01	5.168140e-01
1  -2.60366	3.079069e-01	5.153412e-01
1  -2.2668	3.079069e-01	5.017488e-01
2  -1.33686	3.014656e-01	5.117531e-01
4  -2.68739	3.156831e-01	4.896713e-01
2  -2.67008	3.144823e-01	4.915363e-01
2  -1.57296	3.306353e-01	4.664482e-01
1  -2.19959	3.257092e-01	4.740992e-01
1  -1.74062	3.257092e-01	4.661553e-01
1  -1.60373	3.270914e-01	4.640085e-01
1  -1.71235	3.270914e-01	4.654973e-01
2  -1.72084	3.074751e-01	4.959643e-01
2  -1.11919	3.032752e-01	5.024873e-01
1  -2.22157	3.142920e-01	4.853766e-01
1  -1.17766	3.142920e-01	5.267619e-01
2  -1.0761	3.073133e-01	5.376008e-01
1  -1.13482	3.084596e-01	5.358204e-01
2  -2.00696	3.084596e-01	5.277380e-01
1  -2.66162	3.084596e-01	5.123325e-01
1  -2.7086	3.209963e-01	4.928611e-01
1  -2.68627	3.209963e-01	4.850061e-01
1  -2.80412	3.136510e-01	4.964145e-01
2  -1.95326	3.136510e-01	4.837349e-01
1  -2.91308	3.136510e-01	5.029353e-01
1  -2.24387	3.261477e-01	4.835260e-01
1  -2.15599	3.261477e-01	4.867277e-01
3  -1.6979	3.293749e-01	4.817154e-01
1  -1.57358	3.293749e-01	4.641717e-01
2  -2.20167	3.232680e-01	4.736567e-01
2  -1.71286	3.058251e-01	5.007481e-01
2  -2.29501	3.119062e-01	4.913033e-01
1  -2.14583	3.097986e-01	4.945767e-01
1  -2.39992	3.097986e-01	4.981797e-01
1  -1.22108	3.010915e-01	5.117030e-01
4  -1.18619	3.010915e-01	5.112291e-01
2  -1.42497	3.010915e-01	5.148753e-01
3  -1.72627	3.010915e-01	5.263493e-01
1  -1.76025	3.012883e-01	5.260437e-01
1  -1.64691	3.012883e-01	5.318034e-01
4  -2.59485	3.108538e-01	5.169468e-01
1  -2.25513	3.059118e-01	5.246225e-01
2  -1.57914	3.059118e-01	4.989776e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2516 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000895 	for  Omega_m
           0.000464 	for  b1
--> Not computing covariance matrix
1  -2.17597	3.059118e-01	5.263193e-01
1  -2.55248	3.134703e-01	5.145798e-01
2  -2.85014	3.134703e-01	5.078196e-01
1  -2.89429	3.134703e-01	5.007270e-01
1  -2.71704	3.213419e-01	4.885013e-01
1  -1.89174	3.213419e-01	5.061363e-01
1  -2.01857	3.067911e-01	5.287359e-01
1  -2.49916	3.067911e-01	5.131401e-01
1  -2.92645	3.149703e-01	5.004366e-01
1  -1.6549	3.149703e-01	5.218877e-01
1  -1.57659	3.168698e-01	5.189374e-01
1  -2.8817	3.168698e-01	5.002350e-01
4  -1.79247	3.014758e-01	5.241441e-01
3  -2.87495	3.171390e-01	4.998169e-01
1  -2.89905	3.171390e-01	4.949321e-01
1  -2.1915	3.045513e-01	5.144826e-01
1  -2.19745	3.045513e-01	5.239045e-01
1  -2.33111	3.057130e-01	5.221003e-01
1  -1.41995	3.057130e-01	5.361417e-01
2  -0.462519	2.985904e-01	5.472041e-01
3  -0.903923	3.012623e-01	5.430544e-01
1  -1.59242	3.012623e-01	5.331422e-01
5  -2.4696	3.095584e-01	5.202571e-01
1  -0.852427	3.095584e-01	5.364297e-01
2  -0.477388	3.198512e-01	5.204434e-01
1  -0.874974	3.124891e-01	5.318778e-01
1  -2.76574	3.124891e-01	4.982345e-01
3  -2.72341	3.203109e-01	4.860861e-01
1  -2.62843	3.203109e-01	4.981866e-01
1  -1.21822	2.984909e-01	5.320764e-01
2  -1.20218	2.984909e-01	5.272994e-01
1  -1.00354	2.984909e-01	5.394516e-01
2  -0.514317	2.962064e-01	5.429998e-01
1  -1.78836	3.032779e-01	5.320167e-01
2  -1.59624	3.032779e-01	5.349997e-01
1  -2.06649	3.032779e-01	5.195100e-01
1  -2.53068	3.070234e-01	5.136927e-01
3  -2.298	3.070234e-01	5.241861e-01
1  -2.56487	3.152584e-01	5.113960e-01
1  -2.58461	3.152584e-01	5.110791e-01
2  -2.49233	3.096608e-01	5.197730e-01
1  -1.86823	3.251036e-01	4.957881e-01
1  -1.67525	3.251036e-01	4.656618e-01
1  -1.75966	3.108972e-01	4.877265e-01
1  -2.33924	3.108972e-01	4.943283e-01
1  -2.52176	3.180492e-01	4.832202e-01
3  -1.70565	3.180492e-01	5.154478e-01
1  -0.259214	3.295726e-01	4.975503e-01
2  -1.55214	3.295726e-01	4.837896e-01
1  -1.78913	3.295726e-01	4.773150e-01
1  -1.27003	3.326474e-01	4.725393e-01
1  -1.11883	3.326474e-01	4.768540e-01
3  -2.29314	3.249342e-01	4.888337e-01
1  -2.19824	3.249342e-01	4.910911e-01
1  -2.45614	3.224483e-01	4.949520e-01
1  -2.56565	3.224483e-01	4.817080e-01
2  -0.953408	2.987953e-01	5.184446e-01
1  -2.20645	3.061198e-01	5.070686e-01
4  -2.28988	3.061198e-01	5.089345e-01
1  -2.43754	3.061198e-01	5.153901e-01
5  -2.58707	3.075992e-01	5.130924e-01
2  -2.55813	3.075992e-01	5.171430e-01
1  -2.58835	3.075992e-01	5.137226e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2549 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000999 	for  Omega_m
           0.000441 	for  b1
--> Not computing covariance matrix
5  -2.60416	3.077759e-01	5.134481e-01
3  -2.49222	3.077759e-01	5.199129e-01
2  -2.54855	3.085352e-01	5.187335e-01
3  -2.54654	3.199495e-01	5.010055e-01
2  -2.48703	3.199495e-01	4.805446e-01
2  -1.59434	3.199495e-01	5.122497e-01
3  -2.6882	3.199495e-01	4.977895e-01
1  -2.84306	3.130656e-01	5.084811e-01
1  -2.25778	3.130656e-01	5.192001e-01
1  -1.74869	3.041864e-01	5.329909e-01
1  -2.18898	3.041864e-01	5.174819e-01
3  -2.49377	3.067091e-01	5.135639e-01
1  -1.99545	3.067091e-01	5.290855e-01
2  -2.12483	3.179258e-01	5.116643e-01
1  -1.563	3.241692e-01	5.019673e-01
2  -2.38116	3.241692e-01	4.898971e-01
1  -1.86755	3.241692e-01	4.685166e-01
2  -1.58899	3.272077e-01	4.637974e-01
2  -1.35721	3.291875e-01	4.607225e-01
3  -1.70001	3.086326e-01	4.926473e-01
1  -0.169533	3.086326e-01	4.808488e-01
1  0.203032	3.058642e-01	4.851485e-01
1  -1.86017	3.058642e-01	5.024582e-01
1  -2.21464	3.090514e-01	4.975079e-01
2  -2.70598	3.090514e-01	5.106163e-01
1  -2.46968	3.090514e-01	5.017015e-01
2  -2.42446	3.085416e-01	5.024933e-01
1  -2.70413	3.194501e-01	4.855507e-01
1  -2.82118	3.194501e-01	4.935447e-01
1  -2.92428	3.145370e-01	5.011756e-01
1  -2.87551	3.145370e-01	4.969259e-01
1  -2.43367	3.246245e-01	4.812586e-01
1  -2.33847	3.246245e-01	4.767322e-01
1  -2.70306	3.138999e-01	4.933890e-01
1  -2.91521	3.138999e-01	5.031991e-01
1  -2.61823	3.223558e-01	4.900659e-01
1  -2.63165	3.223558e-01	4.848806e-01
1  -2.49427	3.076125e-01	5.077792e-01
1  -2.55847	3.076125e-01	5.103499e-01
1  -2.88486	3.128765e-01	5.021740e-01
1  -2.62818	3.128765e-01	5.141303e-01
2  -2.54964	3.176863e-01	5.066600e-01
1  -2.58053	3.169116e-01	5.078632e-01
1  -1.38198	3.169116e-01	4.728017e-01
2  -1.15669	3.244730e-01	4.610577e-01
1  -1.36781	3.160739e-01	4.741029e-01
1  -2.65027	3.160739e-01	4.883071e-01
2  -1.70337	3.039090e-01	5.072009e-01
1  -1.52384	3.028063e-01	5.089135e-01
1  -1.01369	3.028063e-01	5.029778e-01
1  -1.25332	3.042325e-01	5.007628e-01
3  -1.77449	3.042325e-01	5.326262e-01
1  -2.24248	3.158324e-01	5.146099e-01
1  -2.92303	3.158324e-01	4.995555e-01
1  -2.89206	3.175401e-01	4.969031e-01
2  -2.67332	3.175401e-01	5.047682e-01
1  -2.66484	3.175401e-01	5.049380e-01
2  -2.6859	3.113458e-01	5.145587e-01
1  -1.53726	3.287337e-01	4.875527e-01
2  -1.91944	3.287337e-01	4.725361e-01
3  -1.84367	3.287337e-01	4.694093e-01
1  -2.56623	3.209947e-01	4.814292e-01
1  -2.70201	3.209947e-01	4.932082e-01
2  -2.63711	3.218751e-01	4.918407e-01
1  -2.73429	3.205075e-01	4.939649e-01
1  -2.2556	3.205075e-01	4.764816e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2581 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000965 	for  Omega_m
           0.000468 	for  b1
--> Not computing covariance matrix
2  -1.99913	3.095179e-01	4.935499e-01
1  -0.917928	3.017503e-01	5.056142e-01
2  -1.82156	3.017503e-01	5.217621e-01
1  -1.8095	3.017503e-01	5.277973e-01
2  -2.64878	3.194597e-01	5.002921e-01
1  -2.80083	3.142201e-01	5.084299e-01
2  -2.80494	3.142201e-01	5.083156e-01
1  -2.17541	3.142201e-01	5.182672e-01
1  -2.1828	3.128957e-01	5.203241e-01
1  1.7953	3.128957e-01	5.450852e-01
1  1.73342	3.091726e-01	5.508676e-01
1  -2.38632	3.091726e-01	5.219499e-01
2  -2.24578	3.203272e-01	5.046253e-01
3  -2.44507	3.168810e-01	5.099778e-01
2  -2.83167	3.168810e-01	5.023272e-01
1  -2.89086	3.168810e-01	4.942222e-01
1  -2.65352	3.091459e-01	5.062360e-01
3  -1.75118	3.091459e-01	5.297499e-01
2  -1.82311	3.119644e-01	5.253722e-01
1  1.0355	3.353463e-01	4.890568e-01
1  0.579038	3.353463e-01	4.857003e-01
2  0.230587	3.338152e-01	4.880784e-01
1  -2.11057	3.159659e-01	5.158008e-01
1  -1.5969	3.159659e-01	5.205237e-01
1  -1.61805	3.154222e-01	5.213682e-01
1  -1.89949	3.154222e-01	4.798743e-01
1  -1.77295	3.123718e-01	4.846120e-01
1  -2.8419	3.123718e-01	5.013025e-01
2  -2.89517	3.166512e-01	4.946559e-01
1  -2.84143	3.123594e-01	5.013218e-01
1  -2.84253	3.123594e-01	5.088955e-01
5  -2.41102	3.059547e-01	5.188430e-01
1  -1.16001	3.059547e-01	4.947973e-01
1  -0.777743	3.035034e-01	4.986045e-01
2  -1.10274	3.035034e-01	5.015831e-01
1  -0.764992	3.035034e-01	4.984953e-01
1  -1.81076	3.128322e-01	4.840063e-01
1  -2.19017	3.128322e-01	4.879686e-01
3  -2.1316	3.223680e-01	4.731582e-01
1  -2.62804	3.223680e-01	4.846382e-01
2  -2.33193	3.061786e-01	5.097827e-01
1  -2.84686	3.133057e-01	4.987132e-01
2  -2.78962	3.133057e-01	5.099876e-01
1  -2.3862	3.133057e-01	5.172298e-01
1  -2.11195	3.067506e-01	5.274109e-01
2  -2.13739	3.067506e-01	5.270177e-01
1  -2.33938	3.067506e-01	5.073802e-01
3  -1.90907	3.288786e-01	4.730121e-01
2  -1.91318	3.288786e-01	4.769647e-01
2  -1.83303	3.288786e-01	4.808697e-01
1  -1.66543	3.288786e-01	4.848262e-01
2  -1.51864	3.000091e-01	5.296647e-01
2  -1.34796	2.991250e-01	5.310378e-01
1  -2.65956	3.091524e-01	5.154638e-01
1  -2.71378	3.091524e-01	5.112574e-01
1  -2.06679	3.032270e-01	5.204604e-01
1  -2.06359	3.032270e-01	5.200525e-01
1  -2.11474	3.035760e-01	5.195105e-01
1  -1.6975	3.035760e-01	5.336271e-01
1  -2.28238	3.137708e-01	5.177931e-01
1  -2.90039	3.137708e-01	5.049197e-01
2  -2.87634	3.171728e-01	4.996360e-01
2  -2.64173	3.082402e-01	5.135095e-01
1  -2.8718	3.173363e-01	4.993820e-01
1  -2.35804	3.173363e-01	4.818310e-01
1  -2.32909	3.146432e-01	4.860137e-01
1  -2.69139	3.146432e-01	4.916418e-01
1  -2.64652	3.130663e-01	4.940910e-01
2  -2.74771	3.130663e-01	5.113733e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2616 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000600 	for  Omega_m
           0.000300 	for  b1
--> Not computing covariance matrix
1  -2.15208	3.130663e-01	4.870377e-01
1  -1.67264	3.273011e-01	4.649290e-01
1  2.17876	3.273011e-01	4.374306e-01
2  2.27991	3.285135e-01	4.355476e-01
2  2.64483	3.319506e-01	4.302092e-01
1  2.22724	3.121881e-01	4.609033e-01
1  -0.613667	3.121881e-01	4.760222e-01
1  -0.835645	3.180710e-01	4.668853e-01
1  -1.1526	3.180710e-01	4.691675e-01
1  -0.436985	3.297189e-01	4.510766e-01
1  -0.942671	3.297189e-01	4.912055e-01
1  -0.786985	3.305802e-01	4.898678e-01
2  -1.61226	3.305802e-01	4.765068e-01
1  -1.39645	3.305802e-01	4.819731e-01
3  -2.00368	3.266228e-01	4.881196e-01
2  -1.74873	3.266228e-01	4.923199e-01
1  -2.05253	3.266228e-01	4.714152e-01
1  -2.14524	3.257447e-01	4.727790e-01
1  -2.32137	3.257447e-01	4.810402e-01
1  -2.8977	3.140824e-01	4.991535e-01
2  -2.45485	3.140824e-01	5.150654e-01
2  -2.77252	3.140824e-01	4.945953e-01
1  -2.44434	3.140824e-01	5.152110e-01
1  -2.29083	3.084816e-01	5.239098e-01
1  -2.09077	3.084816e-01	5.267004e-01
2  -2.15337	3.097297e-01	5.247619e-01
2  -1.85297	3.054268e-01	5.314451e-01
2  -2.02894	3.075194e-01	5.281950e-01
1  -2.12719	3.091588e-01	5.256487e-01
1  -2.48343	3.091588e-01	5.201963e-01
2  -2.34391	3.207188e-01	5.022419e-01
3  -2.58365	3.114743e-01	5.165999e-01
1  -2.83242	3.114743e-01	5.090682e-01
2  -2.73912	3.096535e-01	5.118963e-01
2  -2.89698	3.152691e-01	5.031743e-01
1  -2.8147	3.110578e-01	5.097152e-01
1  -1.88762	3.110578e-01	5.260447e-01
1  -1.90179	3.120519e-01	5.245006e-01
1  -2.03479	3.120519e-01	5.231731e-01
1  -1.9331	3.171111e-01	5.153154e-01
1  -2.628	3.171111e-01	4.863194e-01
2  -2.59513	3.189403e-01	4.834784e-01
1  -2.46767	3.218231e-01	4.790010e-01
1  -1.66272	3.218231e-01	4.683739e-01
2  -1.75056	3.189621e-01	4.728175e-01
1  -1.74392	3.193505e-01	4.722143e-01
2  -2.78763	3.193505e-01	4.884777e-01
2  -2.47864	3.193505e-01	4.809898e-01
1  -2.67271	3.193505e-01	5.000507e-01
2  -2.68419	3.097378e-01	5.149805e-01
1  -2.35505	3.057419e-01	5.211868e-01
2  -2.1083	3.057419e-01	5.275304e-01
4  -2.01433	3.057419e-01	5.290823e-01
2  -2.39659	3.057419e-01	5.163115e-01
1  -2.06415	3.057419e-01	5.282869e-01
1  -2.27555	3.083634e-01	5.242153e-01
3  -2.63078	3.083634e-01	5.153344e-01
2  -2.7683	3.105438e-01	5.119479e-01
3  -2.73483	3.194093e-01	4.981785e-01
1  -1.59539	3.194093e-01	5.134543e-01
1  -1.57618	3.196494e-01	5.130813e-01
1  -2.76113	3.196494e-01	4.873987e-01
1  -1.66324	3.305457e-01	4.704752e-01
2  -1.44385	3.305457e-01	4.630054e-01
1  -1.0156	3.305457e-01	4.565568e-01
1  -1.59471	3.253730e-01	4.645907e-01
1  -0.674994	3.253730e-01	4.563107e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2649 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
 -> R-1 is 0.000554 	for  Omega_m
           0.000239 	for  b1
--> Not computing covariance matrix
2  -0.942124	3.190954e-01	4.660608e-01
2  -0.920078	3.162182e-01	4.705294e-01
4  0.459872	3.346879e-01	4.418432e-01
1  1.3899	3.396293e-01	4.341686e-01
2  0.848685	3.396293e-01	4.395185e-01
1  0.146982	3.396293e-01	4.536372e-01

#  9000 steps done, acceptance rate: 0.5898888888888889
Traceback (most recent call last):
  File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
Exception ignored in: 'classy.Class.__dealloc__'
Traceback (most recent call last):
  File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
In [62]:
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_fs_cobaya, samples_bao_fs_cosmosis, samples_bao_fs_montepython],
                 params=['Omega_m', 'b1'], markers={'Omega_m': cosmo['Omega_m'], 'b1': 0.5})

Wrap-up¶

  • compressed or full-shape likelihoods are defined only once, within desilike
  • bindings for Cobaya, CosmoSIS and MontePython are generated with a simple function call
  • for Cobaya, the generated likelihood can be straightforwardly imported
  • for CosmoSIS and MontePython, the descroption of nuisance parameters need be copied into the input config files